כור המצרף של ה-AI: האם מנהלים אוסטרלים מפספסים את הרכבת?

All right. Hello everybody. Thank you to All right. Hello everybody. Thank you to my panelists for joining me. We're going my panelists for joining me. We're going my panelists for joining me. We're going to have a really interesting to have a really interesting to have a really interesting conversation today about AI. Um I think conversation today about AI. Um I think conversation today about AI. Um I think most of us in this room and through the most of us in this room and through the most of us in this room and through the conversations today have moved past conversations today have moved past conversations today have moved past should we adopt AI. And the question is should we adopt AI. And the question is should we adopt AI. And the question is uh how do you actually build an uh how do you actually build an uh how do you actually build an organization where AI is doing real work organization where AI is doing real work organization where AI is doing real work not just sitting in a pilot delivering not just sitting in a pilot delivering not just sitting in a pilot delivering individual productivity um or used in individual productivity um or used in individual productivity um or used in just one siloed use case. And that's just one siloed use case. And that's just one siloed use case. And that's what we're here to talk about today. And what we're here to talk about today. And what we're here to talk about today. And I'm thrilled to have with me three I'm thrilled to have with me three I'm thrilled to have with me three leaders who are at the forefront of this leaders who are at the forefront of this leaders who are at the forefront of this in their respective domains. And before in their respective domains. And before in their respective domains. And before we get into a candid conversation on we get into a candid conversation on we get into a candid conversation on what it takes, I'd love for you all to what it takes, I'd love for you all to what it takes, I'd love for you all to please introduce yourselves. Helen, can please introduce yourselves. Helen, can please introduce yourselves. Helen, can we start with you? Sure. The things I we start with you? Sure. The things I we start with you? Sure. The things I list uh that I do are um chairing a list uh that I do are um chairing a list uh that I do are um chairing a couple of scaleup companies and edtech, couple of scaleup companies and edtech, couple of scaleup companies and edtech, Education Perfect, and Higher Up. Uh but Education Perfect, and Higher Up. Uh but Education Perfect, and Higher Up. Uh but broadly what I do these days is um help broadly what I do these days is um help broadly what I do these days is um help people uh steer their companies through people uh steer their companies through people uh steer their companies through uh digital scaling having worked in Seek uh digital scaling having worked in Seek uh digital scaling having worked in Seek and Etsy and VTO and a number of other and Etsy and VTO and a number of other and Etsy and VTO and a number of other digital companies over the years done a digital companies over the years done a digital companies over the years done a few rodeos and help other people with few rodeos and help other people with few rodeos and help other people with theirs. theirs. theirs. >> Hi everyone, I'm good. I'm the managing >> Hi everyone, I'm good. I'm the managing >> Hi everyone, I'm good. I'm the managing director for Australia New Zealand at director for Australia New Zealand at director for Australia New Zealand at zero and also our global chief strategy zero and also our global chief strategy zero and also our global chief strategy officer. So the MD role is all things go officer. So the MD role is all things go officer. So the MD role is all things go to market for zero in this part of the to market for zero in this part of the to market for zero in this part of the region and obviously from the strategy region and obviously from the strategy region and obviously from the strategy lens thinking about how AI but lens thinking about how AI but lens thinking about how AI but everything else uh how do we make sure everything else uh how do we make sure everything else uh how do we make sure we serve our customers well. we serve our customers well. we serve our customers well. >> Hi everyone, my name is Will Snell. I'm >> Hi everyone, my name is Will Snell. I'm >> Hi everyone, my name is Will Snell. I'm based here in Sydney. I work for Open AI based here in Sydney. I work for Open AI based here in Sydney. I work for Open AI and I lead some of our strategic and I lead some of our strategic and I lead some of our strategic accounts. Uh these will be large accounts. Uh these will be large accounts. Uh these will be large enterprises. It could be government. Uh enterprises. It could be government. Uh enterprises. It could be government. Uh it could be non for profofit ways to uh it could be non for profofit ways to uh it could be non for profofit ways to uh actually use AI to drive impact. So, actually use AI to drive impact. So, actually use AI to drive impact. So, it's really rare to have three such it's really rare to have three such it's really rare to have three such different vantage points on stage at one different vantage points on stage at one different vantage points on stage at one time and between the three of you, I time and between the three of you, I time and between the three of you, I think we're going to have a really think we're going to have a really think we're going to have a really interesting conversation. Um, we're interesting conversation. Um, we're interesting conversation. Um, we're going to get into the AI landscape and going to get into the AI landscape and going to get into the AI landscape and some really actionable takeaways uh for some really actionable takeaways uh for some really actionable takeaways uh for the leaders in the room. What I'm the leaders in the room. What I'm the leaders in the room. What I'm hearing uh from a lot of the the hearing uh from a lot of the the hearing uh from a lot of the the organizations that I speak to is that organizations that I speak to is that organizations that I speak to is that the technology is moving incredibly fast the technology is moving incredibly fast the technology is moving incredibly fast and probably faster than most and probably faster than most and probably faster than most organizations ability to absorb it. Um organizations ability to absorb it. Um organizations ability to absorb it. Um Will, I'd like to start with you. Um Will, I'd like to start with you. Um Will, I'd like to start with you. Um you're across enterprise AI deployments you're across enterprise AI deployments you're across enterprise AI deployments across the region. Um what's your honest

across the region. Um what's your honest across the region. Um what's your honest view? Where are most A&Z organizations view? Where are most A&Z organizations view? Where are most A&Z organizations sitting right now with AI? sitting right now with AI? sitting right now with AI? >> Just zooming out quickly. I think >> Just zooming out quickly. I think >> Just zooming out quickly. I think globally we do hear a lot of large globally we do hear a lot of large globally we do hear a lot of large companies say that they've understood companies say that they've understood companies say that they've understood that AI is this really large of that AI is this really large of that AI is this really large of disruptive factor that they need to um disruptive factor that they need to um disruptive factor that they need to um they need to lean into. then nearly all they need to lean into. then nearly all they need to lean into. then nearly all of them have some investments in AI of them have some investments in AI of them have some investments in AI different projects. Uh but very few feel different projects. Uh but very few feel different projects. Uh but very few feel satisfied with the results. Um and so if satisfied with the results. Um and so if satisfied with the results. Um and so if you then look at Australia, we hear the you then look at Australia, we hear the you then look at Australia, we hear the same thing in boardrooms and with uh same thing in boardrooms and with uh same thing in boardrooms and with uh senior leaders here. Uh everyone has senior leaders here. Uh everyone has senior leaders here. Uh everyone has acknowledged that AI will change acknowledged that AI will change acknowledged that AI will change Australian businesses, Australian Australian businesses, Australian Australian businesses, Australian landscape uh pretty dramatically and landscape uh pretty dramatically and landscape uh pretty dramatically and they're all investing and they do feel a they're all investing and they do feel a they're all investing and they do feel a little bit like they're stuck in PC little bit like they're stuck in PC little bit like they're stuck in PC purgatory. And one of the things that we purgatory. And one of the things that we purgatory. And one of the things that we often do is work with large often do is work with large often do is work with large organizations on on how to get out of organizations on on how to get out of organizations on on how to get out of that PC purgatory and how to also that PC purgatory and how to also that PC purgatory and how to also measure the impact. Um and so I think measure the impact. Um and so I think measure the impact. Um and so I think Australia's doing you know relatively Australia's doing you know relatively Australia's doing you know relatively well in terms of acknowledging you know well in terms of acknowledging you know well in terms of acknowledging you know the changes that we see. Uh but there's the changes that we see. Uh but there's the changes that we see. Uh but there's still more which is a global trend. still more which is a global trend. still more which is a global trend. There's still still more work to be done There's still still more work to be done There's still still more work to be done uh with regards to the sort of uh with regards to the sort of uh with regards to the sort of capability overhang. What we talk a lot capability overhang. What we talk a lot capability overhang. What we talk a lot about at the company is if we were to about at the company is if we were to about at the company is if we were to stop all model development today, which stop all model development today, which stop all model development today, which won't happen, but if if the entire won't happen, but if if the entire won't happen, but if if the entire industry was to stop, there'd still be industry was to stop, there'd still be industry was to stop, there'd still be years and years and years of economic years and years and years of economic years and years and years of economic impact with the models capability. impact with the models capability. impact with the models capability. >> Yep. >> Yep. >> Yep. >> And so that's largely a deployment um >> And so that's largely a deployment um >> And so that's largely a deployment um and uh sort of like a an investment and uh sort of like a an investment and uh sort of like a an investment issue. And so we work with large issue. And so we work with large issue. And so we work with large companies on how to clear that. companies on how to clear that. companies on how to clear that. >> I love PO purgatory. That's really >> I love PO purgatory. That's really >> I love PO purgatory. That's really interesting. I think a lot of us can interesting. I think a lot of us can interesting. I think a lot of us can relate to that. Um Helen, you're sitting relate to that. Um Helen, you're sitting relate to that. Um Helen, you're sitting across multiple boards with very across multiple boards with very across multiple boards with very different companies. Does what Will is different companies. Does what Will is different companies. Does what Will is describing now make sense for you? Does describing now make sense for you? Does describing now make sense for you? Does it align with what you're hearing? Uh it align with what you're hearing? Uh it align with what you're hearing? Uh not my personal experience, but that is not my personal experience, but that is not my personal experience, but that is a slice of the market and they're all a slice of the market and they're all a slice of the market and they're all digital first companies that I work digital first companies that I work digital first companies that I work with. Um I would say that was where a a with. Um I would say that was where a a with. Um I would say that was where a a number were middle of last year. But number were middle of last year. But number were middle of last year. But since December the adoption, the since December the adoption, the since December the adoption, the disappearance of skeptics, disappearance of skeptics, disappearance of skeptics, the um excitement about the productivity the um excitement about the productivity the um excitement about the productivity gains and revenue opportunities has gains and revenue opportunities has gains and revenue opportunities has utterly transformed. I've never seen utterly transformed. I've never seen utterly transformed. I've never seen such a speed um of transformation of of such a speed um of transformation of of such a speed um of transformation of of ways of working attitudes ways of working attitudes ways of working attitudes >> very hard for people to keep up but um >> very hard for people to keep up but um >> very hard for people to keep up but um it it's a very different place now in it it's a very different place now in it it's a very different place now in the companies I work with but it is in a the companies I work with but it is in a the companies I work with but it is in a digital um a digital context who should digital um a digital context who should digital um a digital context who should be damn good at adopting new be damn good at adopting new be damn good at adopting new technologies. So so I think it's technologies. So so I think it's technologies. So so I think it's probably that slice of the market I probably that slice of the market I probably that slice of the market I would say. would say. would say. >> Yeah. And we like to think that tech >> Yeah. And we like to think that tech >> Yeah. And we like to think that tech companies are at the forefront of all companies are at the forefront of all companies are at the forefront of all these things that are happening. Lots of these things that are happening. Lots of these things that are happening. Lots of people from tech companies on this people from tech companies on this people from tech companies on this stage. Um Angard Zero sits at the center stage. Um Angard Zero sits at the center stage. Um Angard Zero sits at the center of millions of businesses across A&Z.

of millions of businesses across A&Z. of millions of businesses across A&Z. What's the gap that you see between what What's the gap that you see between what What's the gap that you see between what customers say they want from AI and what customers say they want from AI and what customers say they want from AI and what they're actually getting? they're actually getting? they're actually getting? >> Yeah, I think if you think about our key >> Yeah, I think if you think about our key >> Yeah, I think if you think about our key customer, mostly small medium customer, mostly small medium customer, mostly small medium businesses, the the thing that we know businesses, the the thing that we know businesses, the the thing that we know for them and Zero's been empowering for for them and Zero's been empowering for for them and Zero's been empowering for many years is they're time poor. the many years is they're time poor. the many years is they're time poor. the last thing you're trying to do is manage last thing you're trying to do is manage last thing you're trying to do is manage your back office. You want to go serve your back office. You want to go serve your back office. You want to go serve customers. You started a small business customers. You started a small business customers. You started a small business or a medium business to go, you know, or a medium business to go, you know, or a medium business to go, you know, achieve your dreams. And so I think the achieve your dreams. And so I think the achieve your dreams. And so I think the the thing that they're all looking for the thing that they're all looking for the thing that they're all looking for is time efficiency back. Give me is time efficiency back. Give me is time efficiency back. Give me insights. Give me the knowledge I need. insights. Give me the knowledge I need. insights. Give me the knowledge I need. And I think the thing that's stopping And I think the thing that's stopping And I think the thing that's stopping them the most frankly is up to us as them the most frankly is up to us as them the most frankly is up to us as industry leaders, which is how do you industry leaders, which is how do you industry leaders, which is how do you provide that in context of the work provide that in context of the work provide that in context of the work they're doing. if they have another tool they're doing. if they have another tool they're doing. if they have another tool they have to go off to the side. There's they have to go off to the side. There's they have to go off to the side. There's always going to be trail blazers to your always going to be trail blazers to your always going to be trail blazers to your point that will happily have 50 Chrome point that will happily have 50 Chrome point that will happily have 50 Chrome tabs or you know open to go do what they tabs or you know open to go do what they tabs or you know open to go do what they need to do. But I think really and the need to do. But I think really and the need to do. But I think really and the way we think about it at Zero is like way we think about it at Zero is like way we think about it at Zero is like what is the most important insight we what is the most important insight we what is the most important insight we can use through all the technology that can use through all the technology that can use through all the technology that actually helps a small business owner actually helps a small business owner actually helps a small business owner make a decision, change the way they make a decision, change the way they make a decision, change the way they serve their customer, but in context and serve their customer, but in context and serve their customer, but in context and and let them just do what they want to and let them just do what they want to and let them just do what they want to do dayto-day. Um so that I think is the do dayto-day. Um so that I think is the do dayto-day. Um so that I think is the biggest gap at the moment. If it's like biggest gap at the moment. If it's like biggest gap at the moment. If it's like a lot of context switching, there's a a lot of context switching, there's a a lot of context switching, there's a new tool every single day. new tool every single day. new tool every single day. >> Should I be trying this or trying that? >> Should I be trying this or trying that? >> Should I be trying this or trying that? And it creates uh in their world, not And it creates uh in their world, not And it creates uh in their world, not Purgatory, but analysis paralysis of, Purgatory, but analysis paralysis of, Purgatory, but analysis paralysis of, >> you know, and then it's, oh, it's just >> you know, and then it's, oh, it's just >> you know, and then it's, oh, it's just all too hard. Let me go back to doing all too hard. Let me go back to doing all too hard. Let me go back to doing how I used to do it cuz now I'm spending how I used to do it cuz now I'm spending how I used to do it cuz now I'm spending more time trying to learn the new tool more time trying to learn the new tool more time trying to learn the new tool versus just actually adopting it. versus just actually adopting it. versus just actually adopting it. >> Yeah, for sure. So, it's nailing that >> Yeah, for sure. So, it's nailing that >> Yeah, for sure. So, it's nailing that specific use case that's going to move specific use case that's going to move specific use case that's going to move the needle for you and deciding on that. the needle for you and deciding on that. the needle for you and deciding on that. Do you think Do you think Do you think >> and and I think as platform players like >> and and I think as platform players like >> and and I think as platform players like ourselves providing it so it feels ourselves providing it so it feels ourselves providing it so it feels natural natural natural >> like why do they have to go learn AI? >> like why do they have to go learn AI? >> like why do they have to go learn AI? How about they just get the insight they How about they just get the insight they How about they just get the insight they want and then they can keep executing. want and then they can keep executing. want and then they can keep executing. >> Thank you. We've heard a lot through >> Thank you. We've heard a lot through >> Thank you. We've heard a lot through today about the gap between AI output today about the gap between AI output today about the gap between AI output and outcomes and I think that part of and outcomes and I think that part of and outcomes and I think that part of the conversation is really crucial. We the conversation is really crucial. We the conversation is really crucial. We ran a piece of research recently with ran a piece of research recently with ran a piece of research recently with over a thousand Australian business over a thousand Australian business over a thousand Australian business leaders and a couple of numbers came out leaders and a couple of numbers came out leaders and a couple of numbers came out of it that really stuck with me. Three

of it that really stuck with me. Three of it that really stuck with me. Three in five organizations said AI is already in five organizations said AI is already in five organizations said AI is already being used as an assistive tool across being used as an assistive tool across being used as an assistive tool across their business, but only one in five their business, but only one in five their business, but only one in five said it's fundamentally changed how said it's fundamentally changed how said it's fundamentally changed how their teams actually operate. And I their teams actually operate. And I their teams actually operate. And I think that gap between we're using it think that gap between we're using it think that gap between we're using it and it's actually changed how we work is and it's actually changed how we work is and it's actually changed how we work is something that I'd love for us to dig something that I'd love for us to dig something that I'd love for us to dig into uh in the next piece of this into uh in the next piece of this into uh in the next piece of this conversation. All three of you have a conversation. All three of you have a conversation. All three of you have a really unique view on this. You're really unique view on this. You're really unique view on this. You're across you know large scale enterprises. across you know large scale enterprises. across you know large scale enterprises. you're a lot you're across you know a you're a lot you're across you know a you're a lot you're across you know a lot of smaller companies you're across lot of smaller companies you're across lot of smaller companies you're across boards um let's talk about why this gap boards um let's talk about why this gap boards um let's talk about why this gap still exists for so many organizations still exists for so many organizations still exists for so many organizations and then what are the leadership and then what are the leadership and then what are the leadership decisions and moves that you've seen decisions and moves that you've seen decisions and moves that you've seen actually close it so Angad I want to actually close it so Angad I want to actually close it so Angad I want to come back to you zero started come back to you zero started come back to you zero started integrating AI into the product really integrating AI into the product really integrating AI into the product really early um when it comes to your internal early um when it comes to your internal early um when it comes to your internal use case what are the biggest areas that use case what are the biggest areas that use case what are the biggest areas that you've seen driving AI uh adoption or you've seen driving AI uh adoption or you've seen driving AI uh adoption or outcomes

outcomes outcomes >> I mean the way that we're thinking about >> I mean the way that we're thinking about >> I mean the way that we're thinking about driving that change is both top down and driving that change is both top down and driving that change is both top down and bottom up. So one, we're trying to give bottom up. So one, we're trying to give bottom up. So one, we're trying to give as many of our teams the tools they do as many of our teams the tools they do as many of our teams the tools they do need need need >> less on the PC, but just go run hard. At >> less on the PC, but just go run hard. At >> less on the PC, but just go run hard. At the end of the day, many teams know the end of the day, many teams know the end of the day, many teams know their context and know their work better their context and know their work better their context and know their work better than we're going to know centrally or than we're going to know centrally or than we're going to know centrally or top down. Um, make it very easy to top down. Um, make it very easy to top down. Um, make it very easy to procure those tools, set the right procure those tools, set the right procure those tools, set the right parameters, and then let them loose to parameters, and then let them loose to parameters, and then let them loose to make sure they can get more efficient. I make sure they can get more efficient. I make sure they can get more efficient. I think then it's upon us as leaders to do think then it's upon us as leaders to do think then it's upon us as leaders to do the harder thing, which is how do you the harder thing, which is how do you the harder thing, which is how do you reimagine the way work needs to get reimagine the way work needs to get reimagine the way work needs to get done? cuz that often requires you to go done? cuz that often requires you to go done? cuz that often requires you to go across multiple functions that in a across multiple functions that in a across multiple functions that in a business requires you to rethink how business requires you to rethink how business requires you to rethink how those functions should even operate and those functions should even operate and those functions should even operate and I think it's unfair to ask your I think it's unfair to ask your I think it's unfair to ask your employees to go do that natively bottom employees to go do that natively bottom employees to go do that natively bottom up. I think that's our job as leaders to up. I think that's our job as leaders to up. I think that's our job as leaders to say how would we fundamentally change say how would we fundamentally change say how would we fundamentally change this and so for us I think we're seeing this and so for us I think we're seeing this and so for us I think we're seeing use cases across whether it's marketing use cases across whether it's marketing use cases across whether it's marketing customer support sales the best bang for customer support sales the best bang for customer support sales the best bang for buck is where those teams are actually buck is where those teams are actually buck is where those teams are actually changing multiple steps in the process changing multiple steps in the process changing multiple steps in the process and just running the process completely and just running the process completely and just running the process completely differently using AI tools versus trying differently using AI tools versus trying differently using AI tools versus trying to sprinkle a bit of I checked you know to sprinkle a bit of I checked you know to sprinkle a bit of I checked you know a model to try and see if I could do a model to try and see if I could do a model to try and see if I could do this a little bit better. It was how this a little bit better. It was how this a little bit better. It was how could we actually change the way they could we actually change the way they could we actually change the way they create all our marketing content create all our marketing content create all our marketing content digitally? Start with that problem digitally? Start with that problem digitally? Start with that problem statement first, give them the right statement first, give them the right statement first, give them the right tools, and then let them rework the tools, and then let them rework the tools, and then let them rework the workflow. workflow. workflow. >> Yeah, absolutely. This is where AI moves >> Yeah, absolutely. This is where AI moves >> Yeah, absolutely. This is where AI moves from being an individual tool where from being an individual tool where from being an individual tool where you're just speeding up an individual you're just speeding up an individual you're just speeding up an individual process that you're doing to an process that you're doing to an process that you're doing to an institutional tool where it's changing institutional tool where it's changing institutional tool where it's changing the way you you fundamentally work. Um, the way you you fundamentally work. Um, the way you you fundamentally work. Um, Helen, from where you sit, what Helen, from where you sit, what Helen, from where you sit, what leadership decisions have you seen that leadership decisions have you seen that leadership decisions have you seen that have moved the needles for some of the have moved the needles for some of the have moved the needles for some of the companies that you work with? I think

companies that you work with? I think companies that you work with? I think it's not a leadership decision. My it's not a leadership decision. My it's not a leadership decision. My personal view I think it's a practice personal view I think it's a practice personal view I think it's a practice and it's and it's and it's from board down to call center operator from board down to call center operator from board down to call center operator not down but you [laughter] not down but you [laughter] not down but you [laughter] the full spectrum of roles touching it the full spectrum of roles touching it the full spectrum of roles touching it playing with it seeing its power I think playing with it seeing its power I think playing with it seeing its power I think that is the point of of complete that is the point of of complete that is the point of of complete transformation of most people's thinking transformation of most people's thinking transformation of most people's thinking about it as a tool I think we are for me about it as a tool I think we are for me about it as a tool I think we are for me it I the closest thing and it's not it it I the closest thing and it's not it it I the closest thing and it's not it was not as rapid in its introduction is was not as rapid in its introduction is was not as rapid in its introduction is the arrival of the internet and we do the arrival of the internet and we do the arrival of the internet and we do not even know where this ends. not even know where this ends. not even know where this ends. >> Yeah. But the most important thing is to >> Yeah. But the most important thing is to >> Yeah. But the most important thing is to get on email and work out what it can do get on email and work out what it can do get on email and work out what it can do for you. And you know like the early for you. And you know like the early for you. And you know like the early days of the internet work out start days of the internet work out start days of the internet work out start playing with it because the the use playing with it because the the use playing with it because the the use cases are emerging every day in every cases are emerging every day in every cases are emerging every day in every department in the organizations I'm department in the organizations I'm department in the organizations I'm working with. Every single department it working with. Every single department it working with. Every single department it starts in engineering gets tested it starts in engineering gets tested it starts in engineering gets tested it gets measured. They start to get excited gets measured. They start to get excited gets measured. They start to get excited in recent months in particular. Um but in recent months in particular. Um but in recent months in particular. Um but it's spreading very very rapidly. Um and it's spreading very very rapidly. Um and it's spreading very very rapidly. Um and so I think if a leadership decision is so I think if a leadership decision is so I think if a leadership decision is involved, it's give people space to involved, it's give people space to involved, it's give people space to start using these technologies. start using these technologies. start using these technologies. Take the AI component of every software Take the AI component of every software Take the AI component of every software you use. Play with it yourself directly you use. Play with it yourself directly you use. Play with it yourself directly because because the power will be in the because because the power will be in the because because the power will be in the use cases you imagine. I I personally use cases you imagine. I I personally use cases you imagine. I I personally don't think it's a leadership decision. don't think it's a leadership decision. don't think it's a leadership decision. And I think it's a it's an individual And I think it's a it's an individual And I think it's a it's an individual keeping up to then collectively keeping up to then collectively keeping up to then collectively transform every organization. It's my transform every organization. It's my transform every organization. It's my personal pick. personal pick. personal pick. >> Yeah, that's really interesting. And you >> Yeah, that's really interesting. And you >> Yeah, that's really interesting. And you know, we talk internally about employees know, we talk internally about employees know, we talk internally about employees and their AI fluency and their ability and their AI fluency and their ability and their AI fluency and their ability to contribute to the organization using to contribute to the organization using to contribute to the organization using AI. And that's a really fundamental AI. And that's a really fundamental AI. And that's a really fundamental skill now that we hold really really skill now that we hold really really skill now that we hold really really valuable at HubSpot. Um, and we often valuable at HubSpot. Um, and we often valuable at HubSpot. Um, and we often talk about that when we're hiring or talk about that when we're hiring or talk about that when we're hiring or promoting. we talk about, you know, what promoting. we talk about, you know, what promoting. we talk about, you know, what have they done to lead with AI and where have they done to lead with AI and where have they done to lead with AI and where are they creating uh a difference that are they creating uh a difference that are they creating uh a difference that others maybe aren't? And that kind of others maybe aren't? And that kind of others maybe aren't? And that kind of aligns with what you're saying. Um Will, aligns with what you're saying. Um Will, aligns with what you're saying. Um Will, can you share your observations on can you share your observations on can you share your observations on what's working for the companies that what's working for the companies that what's working for the companies that you work with and where you're seeing an you work with and where you're seeing an you work with and where you're seeing an impact? [snorts] impact? [snorts] impact? [snorts] >> Sure. I think the companies that are

>> Sure. I think the companies that are >> Sure. I think the companies that are seeing the the biggest impact are the seeing the the biggest impact are the seeing the the biggest impact are the ones that are have a high level of ones that are have a high level of ones that are have a high level of conviction. They have board support and conviction. They have board support and conviction. They have board support and they have very bold leadership making they have very bold leadership making they have very bold leadership making um decisions about using the tool and um decisions about using the tool and um decisions about using the tool and engendering a culture of of fun of of engendering a culture of of fun of of engendering a culture of of fun of of testing of um of permission for people testing of um of permission for people testing of um of permission for people to use it. We do some pretty detailed to use it. We do some pretty detailed to use it. We do some pretty detailed surveys on deployments of AI with our surveys on deployments of AI with our surveys on deployments of AI with our biggest customers. Uh and the number one biggest customers. Uh and the number one biggest customers. Uh and the number one sort of differentiator from uh you know sort of differentiator from uh you know sort of differentiator from uh you know like a meaningful successful project to like a meaningful successful project to like a meaningful successful project to one that is sort of me off the charts is one that is sort of me off the charts is one that is sort of me off the charts is full leadership buyin. full leadership buyin. full leadership buyin. >> And so you know one example I think of a >> And so you know one example I think of a >> And so you know one example I think of a lot is CBA with Matt Common. You know he lot is CBA with Matt Common. You know he lot is CBA with Matt Common. You know he is an avid AI user. The culture at the is an avid AI user. The culture at the is an avid AI user. The culture at the at the entire bank is that everyone is at the entire bank is that everyone is at the entire bank is that everyone is is given access to to the tools. Um, and is given access to to the tools. Um, and is given access to to the tools. Um, and it's one I think what is different about it's one I think what is different about it's one I think what is different about this technology is that it's not like this technology is that it's not like this technology is that it's not like you set up a quarterly check-in, you say you set up a quarterly check-in, you say you set up a quarterly check-in, you say how you going with AI and you're done. how you going with AI and you're done. how you going with AI and you're done. It needs to permeate the way that these It needs to permeate the way that these It needs to permeate the way that these organizations work. So, I've come across organizations work. So, I've come across organizations work. So, I've come across many organizations where, you know, in many organizations where, you know, in many organizations where, you know, in some meetings they'll start with their some meetings they'll start with their some meetings they'll start with their use case, the personal use case of AI use case, the personal use case of AI use case, the personal use case of AI that week, which is a really kind of that week, which is a really kind of that week, which is a really kind of engaging way of people to share how engaging way of people to share how engaging way of people to share how they're using the tools. um a lot of they're using the tools. um a lot of they're using the tools. um a lot of celebrating of use cases uh that we work celebrating of use cases uh that we work celebrating of use cases uh that we work with in New Zealand and one of the with in New Zealand and one of the with in New Zealand and one of the procurement team members you made an procurement team members you made an procurement team members you made an incredible breakthrough in terms of the incredible breakthrough in terms of the incredible breakthrough in terms of the onboarding of of um of vendors using onboarding of of um of vendors using onboarding of of um of vendors using chat GBT chat GBT chat GBT >> and she was supported in front of the >> and she was supported in front of the >> and she was supported in front of the entire company by the CEO. So I think entire company by the CEO. So I think entire company by the CEO. So I think the more that the tool you people are the more that the tool you people are the more that the tool you people are using it like if you're if you don't using it like if you're if you don't using it like if you're if you don't think if you're a leader you don't think think if you're a leader you don't think think if you're a leader you don't think that people are using the tool you're that people are using the tool you're that people are using the tool you're probably mistaken and in fact you know probably mistaken and in fact you know probably mistaken and in fact you know I've been in so many rooms where leaders I've been in so many rooms where leaders I've been in so many rooms where leaders will say like oh I've heard about open will say like oh I've heard about open will say like oh I've heard about open claw and then their entire tech team be claw and then their entire tech team be claw and then their entire tech team be like yeah we're using it like I've got like yeah we're using it like I've got like yeah we're using it like I've got five open claws at home and do you know five open claws at home and do you know five open claws at home and do you know what I mean and so people are using it what I mean and so people are using it what I mean and so people are using it and so it's about bringing that and so it's about bringing that and so it's about bringing that excitement and the guardrails into an excitement and the guardrails into an excitement and the guardrails into an environment that people feel they have environment that people feel they have environment that people feel they have the permission to do it. Um and then um the permission to do it. Um and then um the permission to do it. Um and then um as was mentioned making sure that as was mentioned making sure that as was mentioned making sure that there's like a framework for what does there's like a framework for what does there's like a framework for what does everyone using the tool look like and everyone using the tool look like and everyone using the tool look like and then what are the priorities for the then what are the priorities for the then what are the priorities for the company so that how do you build towards company so that how do you build towards company so that how do you build towards your northstar as a company with AI. your northstar as a company with AI. your northstar as a company with AI. >> Yeah. Really nice. So interestingly >> Yeah. Really nice. So interestingly >> Yeah. Really nice. So interestingly Helen you talked about bottom up you and Helen you talked about bottom up you and Helen you talked about bottom up you and and Angad talked more about top down you and Angad talked more about top down you and Angad talked more about top down you know you talked about bottom up as well. know you talked about bottom up as well. know you talked about bottom up as well. It's a bit of a combination of the two. It's a bit of a combination of the two. It's a bit of a combination of the two. Um, and I think the other thing that's

Um, and I think the other thing that's Um, and I think the other thing that's really important, which you almost all really important, which you almost all really important, which you almost all mentioned, is um, the ability to measure mentioned, is um, the ability to measure mentioned, is um, the ability to measure outcomes. So, what are we hoping to outcomes. So, what are we hoping to outcomes. So, what are we hoping to achieve? What's the outcome we're achieve? What's the outcome we're achieve? What's the outcome we're looking for in 3 months, 6 months, 12 looking for in 3 months, 6 months, 12 looking for in 3 months, 6 months, 12 months? You know, how much will that months? You know, how much will that months? You know, how much will that change over the next couple of weeks, change over the next couple of weeks, change over the next couple of weeks, let alone months is something none of us let alone months is something none of us let alone months is something none of us know. Um, and measuring not just the AI know. Um, and measuring not just the AI know. Um, and measuring not just the AI strategy, but the business outcomes that strategy, but the business outcomes that strategy, but the business outcomes that are attached to it. Um, so I guess you are attached to it. Um, so I guess you are attached to it. Um, so I guess you know the question is how do you know know the question is how do you know know the question is how do you know that your approach is working and when that your approach is working and when that your approach is working and when you're unsure of what you're working you're unsure of what you're working you're unsure of what you're working towards and so how you know you know towards and so how you know you know towards and so how you know you know measuring that measuring that outcome measuring that measuring that outcome measuring that measuring that outcome making sure that you're really clear on making sure that you're really clear on making sure that you're really clear on what you're trying to achieve and that what you're trying to achieve and that what you're trying to achieve and that you're taking your teams along that you're taking your teams along that you're taking your teams along that journey is really important and I think journey is really important and I think journey is really important and I think that brings me to what I want to dig that brings me to what I want to dig that brings me to what I want to dig into next which is um into next which is um into next which is um getting your organization aligned around getting your organization aligned around getting your organization aligned around a slightly different challenge. a slightly different challenge. a slightly different challenge. So getting the outcome is one thing, but So getting the outcome is one thing, but So getting the outcome is one thing, but how do we get organizational alignment how do we get organizational alignment how do we get organizational alignment around this and how do we build the around this and how do we build the around this and how do we build the internal business case? So I'd like to internal business case? So I'd like to internal business case? So I'd like to go behind the scenes and ask each of you go behind the scenes and ask each of you go behind the scenes and ask each of you about the internal work, the selling about the internal work, the selling about the internal work, the selling that has to happen before the technology that has to happen before the technology that has to happen before the technology even gets involved. Um, and so maybe even gets involved. Um, and so maybe even gets involved. Um, and so maybe it's board signoff, maybe it's bringing it's board signoff, maybe it's bringing it's board signoff, maybe it's bringing a skeptical leadership team along, maybe a skeptical leadership team along, maybe a skeptical leadership team along, maybe it's getting people on the ground to it's getting people on the ground to it's getting people on the ground to actually use the technology and try new actually use the technology and try new actually use the technology and try new things and be creative. So Helen, you've

things and be creative. So Helen, you've things and be creative. So Helen, you've described yourself in a way that I described yourself in a way that I described yourself in a way that I adore, which is at a bit as a bit of a adore, which is at a bit as a bit of a adore, which is at a bit as a bit of a honeybee, cross-pollinating between honeybee, cross-pollinating between honeybee, cross-pollinating between different companies. Um, what's one different companies. Um, what's one different companies. Um, what's one thing that you keep seeing that is thing that you keep seeing that is thing that you keep seeing that is effective in shifting people that are effective in shifting people that are effective in shifting people that are skeptical about AI? Well, certainly um skeptical about AI? Well, certainly um skeptical about AI? Well, certainly um that's how it felt 6 months ago that um that's how it felt 6 months ago that um that's how it felt 6 months ago that um you know, I would speak a lot about the you know, I would speak a lot about the you know, I would speak a lot about the examples I've seen. So, you know, one of examples I've seen. So, you know, one of examples I've seen. So, you know, one of uh my native AI companies I work with, uh my native AI companies I work with, uh my native AI companies I work with, um the CEO, you know, 6 months ago for um the CEO, you know, 6 months ago for um the CEO, you know, 6 months ago for sure, maybe longer, cloned a or created sure, maybe longer, cloned a or created sure, maybe longer, cloned a or created a virtual CEO of himself, trained it, um a virtual CEO of himself, trained it, um a virtual CEO of himself, trained it, um and his team could ask it questions when and his team could ask it questions when and his team could ask it questions when he wasn't available. Um an example like he wasn't available. Um an example like he wasn't available. Um an example like that or the CTO I met who decided not to that or the CTO I met who decided not to that or the CTO I met who decided not to hire a team. It's a small company. hire a team. It's a small company. hire a team. It's a small company. Admittedly, it's not zero, [laughter] Admittedly, it's not zero, [laughter] Admittedly, it's not zero, [laughter] but um it's a small company. And his but um it's a small company. And his but um it's a small company. And his decision was I've got my eight agents. decision was I've got my eight agents. decision was I've got my eight agents. They're working really well. I'm going They're working really well. I'm going They're working really well. I'm going to see how I go without it. Um those to see how I go without it. Um those to see how I go without it. Um those examples were were sort of early 6 examples were were sort of early 6 examples were were sort of early 6 months ago where I I just talked months ago where I I just talked months ago where I I just talked everywhere. I think in the early days of everywhere. I think in the early days of everywhere. I think in the early days of a new technology, everyone's a new technology, everyone's a new technology, everyone's experimenting and it's it's the cross experimenting and it's it's the cross experimenting and it's it's the cross fertilization that's sharing. There's fertilization that's sharing. There's fertilization that's sharing. There's not there's not the Gartner report yet not there's not the Gartner report yet not there's not the Gartner report yet [snorts] [snorts] [snorts] on adoption. You guys have obviously on adoption. You guys have obviously on adoption. You guys have obviously done some research within your done some research within your done some research within your companies. Awesome. Please share it as companies. Awesome. Please share it as companies. Awesome. Please share it as much as you can because there's not much as you can because there's not much as you can because there's not enough. And I've found I'm sharing enough. And I've found I'm sharing enough. And I've found I'm sharing examples across the people I work with. examples across the people I work with. examples across the people I work with. Um but I have to say in more recent Um but I have to say in more recent Um but I have to say in more recent months that's less of an issue in a months that's less of an issue in a months that's less of an issue in a digital company because people are digital company because people are digital company because people are playing and the results are starting to playing and the results are starting to playing and the results are starting to be profound. So I do also just think you be profound. So I do also just think you be profound. So I do also just think you know these are top down things you can know these are top down things you can know these are top down things you can do. share examples, find benchmarks, do. share examples, find benchmarks, do. share examples, find benchmarks, look externally. It's an important time look externally. It's an important time look externally. It's an important time to look externally as a leader in an to look externally as a leader in an to look externally as a leader in an organization, but also get them using it organization, but also get them using it organization, but also get them using it because they're going to work it out because they're going to work it out because they're going to work it out pretty fast. I mean, we've got great pretty fast. I mean, we've got great pretty fast. I mean, we've got great data, be it 20%, 30% data, be it 20%, 30% data, be it 20%, 30% velocity improvements in engineering, velocity improvements in engineering, velocity improvements in engineering, you know, the data starts speaking for you know, the data starts speaking for you know, the data starts speaking for itself pretty quickly. Will, you've itself pretty quickly. Will, you've itself pretty quickly. Will, you've talked about dual strategy, top down uh talked about dual strategy, top down uh talked about dual strategy, top down uh strategic bets and bottom up access. strategic bets and bottom up access. strategic bets and bottom up access. What happens when those two things are What happens when those two things are What happens when those two things are not in sync inside an organization? not in sync inside an organization? not in sync inside an organization? >> I've seen a few different versions of >> I've seen a few different versions of >> I've seen a few different versions of it. it. it. >> Yeah, >> Yeah, >> Yeah, >> I would say they don't have to be >> I would say they don't have to be >> I would say they don't have to be perfectly in sync. However, it's very perfectly in sync. However, it's very perfectly in sync. However, it's very difficult to pick these massive bets. If difficult to pick these massive bets. If difficult to pick these massive bets. If you think of just going top down, pick you think of just going top down, pick you think of just going top down, pick these massive bets as an organization these massive bets as an organization these massive bets as an organization and bring your organization along with and bring your organization along with and bring your organization along with you if they're not involved in it. And you if they're not involved in it. And you if they're not involved in it. And um you know some things you know you can um you know some things you know you can um you know some things you know you can reimagine you know customer service reimagine you know customer service reimagine you know customer service experience with AI but if you want to experience with AI but if you want to experience with AI but if you want to reimagine your company you need to bring reimagine your company you need to bring reimagine your company you need to bring your your team along. Um so I think some your your team along. Um so I think some your your team along. Um so I think some organizations especially digital natives organizations especially digital natives organizations especially digital natives are very good at planning um the use of are very good at planning um the use of are very good at planning um the use of the technology and the tool. Zero does a the technology and the tool. Zero does a the technology and the tool. Zero does a great job of it. So I think there are great job of it. So I think there are great job of it. So I think there are examples of that for sure. The challenge examples of that for sure. The challenge examples of that for sure. The challenge is is that it's moving so quickly and we is is that it's moving so quickly and we is is that it's moving so quickly and we all you know these organizations they all you know these organizations they all you know these organizations they need to bring their teams along with need to bring their teams along with need to bring their teams along with them that if you don't have a tool that them that if you don't have a tool that them that if you don't have a tool that people use we obviously you know talk people use we obviously you know talk people use we obviously you know talk quite fondly of chatbt um because it's quite fondly of chatbt um because it's quite fondly of chatbt um because it's the one it's the most popular one that the one it's the most popular one that the one it's the most popular one that people are using in their personal lives people are using in their personal lives people are using in their personal lives but if you don't give people an actual but if you don't give people an actual but if you don't give people an actual tool to use it's very difficult to work tool to use it's very difficult to work tool to use it's very difficult to work out also how you can um bring them along out also how you can um bring them along out also how you can um bring them along and what I would say is and what I would say is and what I would say is >> the technology is changing so quick that >> the technology is changing so quick that >> the technology is changing so quick that we actually had some companies that we we actually had some companies that we we actually had some companies that we did these very custom engagements with did these very custom engagements with did these very custom engagements with two years ago. We would never do that two years ago. We would never do that two years ago. We would never do that now. That would just be a function of now. That would just be a function of now. That would just be a function of chat GPT with an MCP server or you know chat GPT with an MCP server or you know chat GPT with an MCP server or you know I think about like you know the HubSpot I think about like you know the HubSpot I think about like you know the HubSpot connector that we have. There could have connector that we have. There could have connector that we have. There could have been a version of that a year or two ago been a version of that a year or two ago been a version of that a year or two ago that people would have hacked together that people would have hacked together that people would have hacked together and it could have worked but like now we and it could have worked but like now we and it could have worked but like now we don't need to do that anymore. It's a don't need to do that anymore. It's a don't need to do that anymore. It's a function of chat GBT. So, I think having function of chat GBT. So, I think having function of chat GBT. So, I think having a playground where you can have these a playground where you can have these a playground where you can have these powerful AI experiences that you don't powerful AI experiences that you don't powerful AI experiences that you don't need to custom build is really important need to custom build is really important need to custom build is really important because where you put your time and because where you put your time and because where you put your time and energy is really important, especially energy is really important, especially energy is really important, especially when you get those 20 30% gains in the when you get those 20 30% gains in the when you get those 20 30% gains in the engineering team. engineering team. engineering team. >> Yeah, absolutely. Um, and I'll share a >> Yeah, absolutely. Um, and I'll share a >> Yeah, absolutely. Um, and I'll share a little bit about what it looked like for little bit about what it looked like for little bit about what it looked like for us at HubSpot as well. So um about a

us at HubSpot as well. So um about a us at HubSpot as well. So um about a year ago, a year and a half ago, we gave year ago, a year and a half ago, we gave year ago, a year and a half ago, we gave uh a lot of our organization access to a uh a lot of our organization access to a uh a lot of our organization access to a bunch of different AI tools and we you bunch of different AI tools and we you bunch of different AI tools and we you know we encouraged AI fluency and we know we encouraged AI fluency and we know we encouraged AI fluency and we created tiger teams and we created some created tiger teams and we created some created tiger teams and we created some you know some experts in the field and you know some experts in the field and you know some experts in the field and we sent people off to build a lot of we sent people off to build a lot of we sent people off to build a lot of stuff and to be as creative as possible. stuff and to be as creative as possible. stuff and to be as creative as possible. Um we shared wins, we formed some habits Um we shared wins, we formed some habits Um we shared wins, we formed some habits and we thought about what are those use and we thought about what are those use and we thought about what are those use cases for us internally that are really cases for us internally that are really cases for us internally that are really going to be meaningful for us. And then going to be meaningful for us. And then going to be meaningful for us. And then this year we've shifted and we're this year we've shifted and we're this year we've shifted and we're focused now on outcomes more than focused now on outcomes more than focused now on outcomes more than efficiency. So rather than rewrite this efficiency. So rather than rewrite this efficiency. So rather than rewrite this email for me so it doesn't, you know, email for me so it doesn't, you know, email for me so it doesn't, you know, look snarky to my boss, you know, let's look snarky to my boss, you know, let's look snarky to my boss, you know, let's create a a use case that's really create a a use case that's really create a a use case that's really creating an outcome for us as an creating an outcome for us as an creating an outcome for us as an organization and really driving results. organization and really driving results. organization and really driving results. Um, and what we're finding is that once Um, and what we're finding is that once Um, and what we're finding is that once adoption's happened inside an adoption's happened inside an adoption's happened inside an organization, um, people don't ask organization, um, people don't ask organization, um, people don't ask necessarily, should I use AI? It's more necessarily, should I use AI? It's more necessarily, should I use AI? It's more how could this be done better with AI? how could this be done better with AI? how could this be done better with AI? How can AI form part of this workflow? How can AI form part of this workflow? How can AI form part of this workflow? Uh how can I automate part of this so I Uh how can I automate part of this so I Uh how can I automate part of this so I can go and focus on something that's can go and focus on something that's can go and focus on something that's more meaningful for me. Um and that's more meaningful for me. Um and that's more meaningful for me. Um and that's where it gets really exciting. But I where it gets really exciting. But I where it gets really exciting. But I don't think that happens without don't think that happens without don't think that happens without leadership modeling it first. Um and so leadership modeling it first. Um and so leadership modeling it first. Um and so when leadership does then you start when leadership does then you start when leadership does then you start building teams where humans and AI can building teams where humans and AI can building teams where humans and AI can really work together and complement the really work together and complement the really work together and complement the work that each other does and we can do work that each other does and we can do work that each other does and we can do the things that are innately human and the things that are innately human and the things that are innately human and important. important. important. Um all right let's talk a little bit Um all right let's talk a little bit Um all right let's talk a little bit very briefly about the human and AI very briefly about the human and AI very briefly about the human and AI agent teams. Um, we've talked a bit agent teams. Um, we've talked a bit agent teams. Um, we've talked a bit about building conviction and getting about building conviction and getting about building conviction and getting people to uh change how they work and to people to uh change how they work and to people to uh change how they work and to lean into a place where humans and AI, lean into a place where humans and AI, lean into a place where humans and AI, you know, specialize in what they do you know, specialize in what they do you know, specialize in what they do best. Um, and I want to stay on that best. Um, and I want to stay on that best. Um, and I want to stay on that human moment for a second and zoom in on human moment for a second and zoom in on human moment for a second and zoom in on it. Uh, because once AI is doing real it. Uh, because once AI is doing real it. Uh, because once AI is doing real work in your team, your job as a leader work in your team, your job as a leader work in your team, your job as a leader actually changes and you're not just actually changes and you're not just actually changes and you're not just managing people anymore. So, what does managing people anymore. So, what does managing people anymore. So, what does that actually look like, Angad? When AI that actually look like, Angad? When AI that actually look like, Angad? When AI is doing real work alongside your people is doing real work alongside your people is doing real work alongside your people as a genuine team member, how does your as a genuine team member, how does your as a genuine team member, how does your role as a leader change? role as a leader change? role as a leader change? >> Yeah, look, I mean, I think it's if we

>> Yeah, look, I mean, I think it's if we >> Yeah, look, I mean, I think it's if we even go back to your previous comment on even go back to your previous comment on even go back to your previous comment on how do you measure the return? Uh, you how do you measure the return? Uh, you how do you measure the return? Uh, you said an important thing Megan around said an important thing Megan around said an important thing Megan around just like measure the business outcome. just like measure the business outcome. just like measure the business outcome. >> So, I think it's very easy when there's >> So, I think it's very easy when there's >> So, I think it's very easy when there's a new tool or tech to say what's the a new tool or tech to say what's the a new tool or tech to say what's the latest leaderboard or scoreboard of some latest leaderboard or scoreboard of some latest leaderboard or scoreboard of some very finite metric. At the end of the very finite metric. At the end of the very finite metric. At the end of the day, what's your business goal that day, what's your business goal that day, what's your business goal that you're trying to solve doesn't change? you're trying to solve doesn't change? you're trying to solve doesn't change? And so, is it enabling you to get to And so, is it enabling you to get to And so, is it enabling you to get to that business goal faster, better, more that business goal faster, better, more that business goal faster, better, more effectively? And if it isn't, and I effectively? And if it isn't, and I effectively? And if it isn't, and I think that's the same when it comes to think that's the same when it comes to think that's the same when it comes to then how are using AI as a teammate to then how are using AI as a teammate to then how are using AI as a teammate to your point, if it's assisting you, if your point, if it's assisting you, if your point, if it's assisting you, if you're assuming that and as a good you're assuming that and as a good you're assuming that and as a good leader that you can outsource everything leader that you can outsource everything leader that you can outsource everything to that agent to that agent to that agent >> and you think you're going to get a >> and you think you're going to get a >> and you think you're going to get a great outcome, you're probably not, great outcome, you're probably not, great outcome, you're probably not, right? Just like we used to hire highly right? Just like we used to hire highly right? Just like we used to hire highly talented, skilled people that you talented, skilled people that you talented, skilled people that you trained, they would give you output. You trained, they would give you output. You trained, they would give you output. You would coach them, you would guide them. would coach them, you would guide them. would coach them, you would guide them. I I think it's no different. Uh context I I think it's no different. Uh context I I think it's no different. Uh context is critical in any AI environment. How is critical in any AI environment. How is critical in any AI environment. How much information can you give a team much information can you give a team much information can you give a team member to give you the best work? It's member to give you the best work? It's member to give you the best work? It's the same with AI tools. The most content the same with AI tools. The most content the same with AI tools. The most content you can give it context or problem, you can give it context or problem, you can give it context or problem, multiple conversations. And so I would multiple conversations. And so I would multiple conversations. And so I would encourage people that if you're trying encourage people that if you're trying encourage people that if you're trying to create this team of agents and to create this team of agents and to create this team of agents and humans, treat them like a team member. humans, treat them like a team member. humans, treat them like a team member. Obviously there's inherent differences. Obviously there's inherent differences. Obviously there's inherent differences. It is not just a human being. But but It is not just a human being. But but It is not just a human being. But but they need the same things. They need they need the same things. They need they need the same things. They need great context. They need to know what great context. They need to know what great context. They need to know what outcome you want. And they need to know outcome you want. And they need to know outcome you want. And they need to know how and when they what output you want how and when they what output you want how and when they what output you want delivered. If you give that clarity, delivered. If you give that clarity, delivered. If you give that clarity, it's going to work much better. it's going to work much better. it's going to work much better. >> Yeah. And they need access to all the >> Yeah. And they need access to all the >> Yeah. And they need access to all the information that you would provide to an information that you would provide to an information that you would provide to an onboarding team member. And you need to onboarding team member. And you need to onboarding team member. And you need to allow the time for that onboarding to allow the time for that onboarding to allow the time for that onboarding to take place because it's not a short take place because it's not a short take place because it's not a short process. Um we have a customer um can I process. Um we have a customer um can I process. Um we have a customer um can I build and Mark Deacon there speaks about build and Mark Deacon there speaks about build and Mark Deacon there speaks about um how his team of trained agents and um how his team of trained agents and um how his team of trained agents and that they on average spend about two that they on average spend about two that they on average spend about two weeks on boarding an agent and then have weeks on boarding an agent and then have weeks on boarding an agent and then have a robust feedback cycle of three to four a robust feedback cycle of three to four a robust feedback cycle of three to four weeks for each of those agents to sort weeks for each of those agents to sort weeks for each of those agents to sort of really manage them effectively. Um of really manage them effectively. Um of really manage them effectively. Um will is there anything that you want to will is there anything that you want to will is there anything that you want to add on on the idea of humans and AI add on on the idea of humans and AI add on on the idea of humans and AI working together? working together? working together? >> The thing is now is that we have so much >> The thing is now is that we have so much >> The thing is now is that we have so much AI generated content out there and AI generated content out there and AI generated content out there and systems and agents that what we do as systems and agents that what we do as systems and agents that what we do as people is really important because you people is really important because you people is really important because you know I can't write as good an email as know I can't write as good an email as know I can't write as good an email as Chatt. [laughter] Um so I think what Chatt. [laughter] Um so I think what Chatt. [laughter] Um so I think what happens is the companies that really happens is the companies that really happens is the companies that really also adopt AI really celebrate all the also adopt AI really celebrate all the also adopt AI really celebrate all the stuff that AI can't do. And so you know stuff that AI can't do. And so you know stuff that AI can't do. And so you know like um it's very easy now to send a like um it's very easy now to send a like um it's very easy now to send a report that summarizes everything in report that summarizes everything in report that summarizes everything in your slack like that's not difficult. So your slack like that's not difficult. So your slack like that's not difficult. So what becomes really important is working what becomes really important is working what becomes really important is working with the team getting that report with the team getting that report with the team getting that report refining it you know having influence in refining it you know having influence in refining it you know having influence in organization. And I think these things organization. And I think these things organization. And I think these things will never change. And I think what will never change. And I think what will never change. And I think what happens is that people just think that happens is that people just think that happens is that people just think that these tools will just like automate these tools will just like automate these tools will just like automate companies completely. And I think that companies completely. And I think that companies completely. And I think that some of the auto like that is probably some of the auto like that is probably some of the auto like that is probably where the future will go in some level. where the future will go in some level. where the future will go in some level. But then our ability as humans to drive But then our ability as humans to drive But then our ability as humans to drive change decision-m to work with the board change decision-m to work with the board change decision-m to work with the board you know it will this technology will you know it will this technology will you know it will this technology will permeate all parts of organizations and permeate all parts of organizations and permeate all parts of organizations and yet we're still going to be core to yet we're still going to be core to yet we're still going to be core to organizations. So I think we should lean organizations. So I think we should lean organizations. So I think we should lean into what we do best. into what we do best. into what we do best. >> Yeah. I like what you said there about >> Yeah. I like what you said there about >> Yeah. I like what you said there about what humans do with the out with the what humans do with the out with the what humans do with the out with the outcomes because it's the decisions that outcomes because it's the decisions that outcomes because it's the decisions that you make off the back of that report you make off the back of that report you make off the back of that report that chat GPD gives you that's more that chat GPD gives you that's more that chat GPD gives you that's more important than anything. important than anything. important than anything. >> Yeah. >> Yeah. >> Yeah. >> Um okay let's talk about the data that's

>> Um okay let's talk about the data that's >> Um okay let's talk about the data that's the foundation for AI. Um the foundation for AI. Um the foundation for AI. Um not in a technical sense obviously but not in a technical sense obviously but not in a technical sense obviously but in a practical sense of like do you have in a practical sense of like do you have in a practical sense of like do you have the foundations in place that are the foundations in place that are the foundations in place that are actually going to make AI work? We ran a actually going to make AI work? We ran a actually going to make AI work? We ran a piece of research recently um with a piece of research recently um with a piece of research recently um with a thousand Australian business leaders and thousand Australian business leaders and thousand Australian business leaders and 44% said access to relevant business 44% said access to relevant business 44% said access to relevant business context and data was most important for context and data was most important for context and data was most important for AI agents to operate efficiently. And in AI agents to operate efficiently. And in AI agents to operate efficiently. And in my experience, this is where a lot of my experience, this is where a lot of my experience, this is where a lot of organizations can run into trouble. organizations can run into trouble. organizations can run into trouble. There's actually a distinction that's There's actually a distinction that's There's actually a distinction that's worth making here. Data is what worth making here. Data is what worth making here. Data is what happened. Eg a deal closed, a customer happened. Eg a deal closed, a customer happened. Eg a deal closed, a customer churned, a campaign ran. Uh context is churned, a campaign ran. Uh context is churned, a campaign ran. Uh context is what that data means. So why the deal what that data means. So why the deal what that data means. So why the deal closed, what made the customer leave, closed, what made the customer leave, closed, what made the customer leave, why your what your team learned along why your what your team learned along why your what your team learned along the way, and that's where the gap lives. the way, and that's where the gap lives. the way, and that's where the gap lives. Um, Angard Zero's whole AI thesis is Um, Angard Zero's whole AI thesis is Um, Angard Zero's whole AI thesis is built on being a trusted system of built on being a trusted system of built on being a trusted system of record. And you've talked publicly about record. And you've talked publicly about record. And you've talked publicly about the shift from system of record to the shift from system of record to the shift from system of record to system of action. Um, what has to be system of action. Um, what has to be system of action. Um, what has to be true inside an organization before that true inside an organization before that true inside an organization before that shift is possible? shift is possible? shift is possible? >> Yeah, I think you mentioned obviously >> Yeah, I think you mentioned obviously >> Yeah, I think you mentioned obviously data is a critical foundation. Uh but I data is a critical foundation. Uh but I data is a critical foundation. Uh but I think for any system to become the think for any system to become the think for any system to become the system of action uh you also have system of action uh you also have system of action uh you also have context of the workflow to your point. context of the workflow to your point. context of the workflow to your point. You know there's one thing to know what You know there's one thing to know what You know there's one thing to know what is in my bank statement. It's another is in my bank statement. It's another is in my bank statement. It's another thing to know how many times is that the thing to know how many times is that the thing to know how many times is that the same thing? same thing? same thing? >> How often does that need to then >> How often does that need to then >> How often does that need to then interact with different members of my interact with different members of my interact with different members of my team? What does my accountant and team? What does my accountant and team? What does my accountant and bookkeeper do with this information? Uh bookkeeper do with this information? Uh bookkeeper do with this information? Uh they have pattern recognition. And so they have pattern recognition. And so they have pattern recognition. And so you know the next thing you need to do you know the next thing you need to do you know the next thing you need to do on that data is trust. And to get trust on that data is trust. And to get trust on that data is trust. And to get trust we've talked about it just in that we've talked about it just in that we've talked about it just in that previous conversation. It's how do you previous conversation. It's how do you previous conversation. It's how do you have the right human in the loop at the have the right human in the loop at the have the right human in the loop at the right time? What level do you want to be right time? What level do you want to be right time? What level do you want to be automated and what level do you want to automated and what level do you want to automated and what level do you want to go in your workflow go in your workflow go in your workflow to a human to cross-check something to to a human to cross-check something to to a human to cross-check something to then trigger the next action? So we then trigger the next action? So we then trigger the next action? So we think it's critical to build that trust think it's critical to build that trust think it's critical to build that trust uh with the human in the loop and to do uh with the human in the loop and to do uh with the human in the loop and to do that I think you know we have we have that I think you know we have we have that I think you know we have we have the benefit but I think any company the benefit but I think any company the benefit but I think any company that's in this system of record space that's in this system of record space that's in this system of record space has this opportunity which is you have has this opportunity which is you have has this opportunity which is you have years and years of context of how that years and years of context of how that years and years of context of how that information is used how it gets information is used how it gets information is used how it gets manipulated how it gets used to make manipulated how it gets used to make manipulated how it gets used to make decisions to your point um and that's decisions to your point um and that's decisions to your point um and that's all the additional context you need to all the additional context you need to all the additional context you need to build on top of the raw data build on top of the raw data build on top of the raw data >> absolutely Helen can you share what the >> absolutely Helen can you share what the >> absolutely Helen can you share what the companies that you work with have had to companies that you work with have had to companies that you work with have had to manage uh in terms of data foundations manage uh in terms of data foundations manage uh in terms of data foundations and what advice you would have. Look, I and what advice you would have. Look, I and what advice you would have. Look, I think this is a journey that was already think this is a journey that was already think this is a journey that was already happening. Data um you know machine happening. Data um you know machine happening. Data um you know machine learning is 15 years old, data lakes and learning is 15 years old, data lakes and learning is 15 years old, data lakes and so on were already um incredibly so on were already um incredibly so on were already um incredibly important and the engineering of those important and the engineering of those important and the engineering of those to give access. Um I think uh the to give access. Um I think uh the to give access. Um I think uh the difference now is the autonomy of the difference now is the autonomy of the difference now is the autonomy of the agents working with that data that agents working with that data that agents working with that data that potentially is fully automated and no potentially is fully automated and no potentially is fully automated and no one is checking that it makes sense. Um one is checking that it makes sense. Um one is checking that it makes sense. Um I I think there's a lot of talk about I I think there's a lot of talk about I I think there's a lot of talk about the data being important, the context the data being important, the context the data being important, the context being important. I think on top of all being important. I think on top of all being important. I think on top of all that is is judgment which at the moment that is is judgment which at the moment that is is judgment which at the moment is more the human piece. I think it will is more the human piece. I think it will is more the human piece. I think it will become an autonomous piece as well and become an autonomous piece as well and become an autonomous piece as well and then we'll need to check the judgments then we'll need to check the judgments then we'll need to check the judgments >> and have checks and balances on those >> and have checks and balances on those >> and have checks and balances on those judgments. But at the moment it is um it judgments. But at the moment it is um it judgments. But at the moment it is um it is where most of most organizations are is where most of most organizations are is where most of most organizations are still keeping the human judgment over uh still keeping the human judgment over uh still keeping the human judgment over uh those those calls. Um I think that will those those calls. Um I think that will those those calls. Um I think that will change and I think that's where it gets change and I think that's where it gets change and I think that's where it gets very dangerous if you haven't got your very dangerous if you haven't got your very dangerous if you haven't got your data data data um engineering strong to the point of um engineering strong to the point of um engineering strong to the point of you know it's correct you know um the you know it's correct you know um the you know it's correct you know um the logic of of the entire organization logic of of the entire organization logic of of the entire organization uh and can leave things autonomously uh and can leave things autonomously uh and can leave things autonomously making the right judgments yeah it's making the right judgments yeah it's making the right judgments yeah it's much more critical now much more critical now much more critical now >> yeah I think so so the data in the >> yeah I think so so the data in the >> yeah I think so so the data in the context layer the human over the top context layer the human over the top context layer the human over the top making the judgment making the judgment making the judgment at the moment. at the moment. at the moment. >> Yeah. At the moment. Exactly. Yeah. And >> Yeah. At the moment. Exactly. Yeah. And >> Yeah. At the moment. Exactly. Yeah. And and some of those judgments, right? It and some of those judgments, right? It and some of those judgments, right? It doesn't have to make all of the judgment doesn't have to make all of the judgment doesn't have to make all of the judgment calls, but it's a trust question like calls, but it's a trust question like calls, but it's a trust question like you said and you know where where we you said and you know where where we you said and you know where where we trust AI to go ahead and make the trust AI to go ahead and make the trust AI to go ahead and make the decision in maybe those non-critical use decision in maybe those non-critical use decision in maybe those non-critical use cases and then where we require a human cases and then where we require a human cases and then where we require a human in the in the cases where it's much more in the in the cases where it's much more in the in the cases where it's much more important. Well, and regulation is also important. Well, and regulation is also important. Well, and regulation is also not caught up at all. So at the moment not caught up at all. So at the moment not caught up at all. So at the moment there's a lot of regulated I mean there's a lot of regulated I mean there's a lot of regulated I mean accounting is regulated legal is accounting is regulated legal is accounting is regulated legal is regulated there's a huge number of regulated there's a huge number of regulated there's a huge number of industries where you you given the industries where you you given the industries where you you given the regulation need to ensure there's some regulation need to ensure there's some regulation need to ensure there's some human judgment applied human judgment applied human judgment applied >> um before final advice etc. So these >> um before final advice etc. So these >> um before final advice etc. So these things will change but for now yeah things will change but for now yeah things will change but for now yeah let's move to talk a little bit about let's move to talk a little bit about let's move to talk a little bit about governance. So data has two sides to it. governance. So data has two sides to it. governance. So data has two sides to it. There's the foundation question, which There's the foundation question, which There's the foundation question, which we just talked about, and then there's we just talked about, and then there's we just talked about, and then there's the trust question and how it's being the trust question and how it's being the trust question and how it's being used, who controls it, how it's used, who controls it, how it's used, who controls it, how it's protected. We're not going to touch on protected. We're not going to touch on protected. We're not going to touch on that right here. Um, Erica Fischer and that right here. Um, Erica Fischer and that right here. Um, Erica Fischer and Matt Fam from Mortgage Choice had a Matt Fam from Mortgage Choice had a Matt Fam from Mortgage Choice had a great conversation on exactly that here great conversation on exactly that here great conversation on exactly that here on this stage earlier today. We have on this stage earlier today. We have on this stage earlier today. We have recorded it for you if you missed it. recorded it for you if you missed it. recorded it for you if you missed it. Um, but for us here in this Um, but for us here in this Um, but for us here in this conversation, we're going to talk about conversation, we're going to talk about conversation, we're going to talk about uh getting the data foundations right as uh getting the data foundations right as uh getting the data foundations right as being one side of the equation. And then being one side of the equation. And then being one side of the equation. And then also um how do you build the guard rails also um how do you build the guard rails also um how do you build the guard rails that protect the organization without that protect the organization without that protect the organization without becoming the reason that you put the becoming the reason that you put the becoming the reason that you put the handbrake on and stop everything good handbrake on and stop everything good handbrake on and stop everything good moving forward with AI? So Helen,

moving forward with AI? So Helen, moving forward with AI? So Helen, there's a lot of board level there's a lot of board level there's a lot of board level conversation about AI um as a conversation about AI um as a conversation about AI um as a riskmanagement question and it's riskmanagement question and it's riskmanagement question and it's legitimate, but your view seems to be legitimate, but your view seems to be legitimate, but your view seems to be that boards are not asking all the that boards are not asking all the that boards are not asking all the questions that they should. Um what do questions that they should. Um what do questions that they should. Um what do you think they should be asking? Can you you think they should be asking? Can you you think they should be asking? Can you give me some more context to that give me some more context to that give me some more context to that conversation? Sure. Yeah. Look, I was I conversation? Sure. Yeah. Look, I was I conversation? Sure. Yeah. Look, I was I was I stay up with, you know, Institute was I stay up with, you know, Institute was I stay up with, you know, Institute of Directors or whatever um governance of Directors or whatever um governance of Directors or whatever um governance latest views and I literally haven't latest views and I literally haven't latest views and I literally haven't seen AI used once in the context of an seen AI used once in the context of an seen AI used once in the context of an opportunity. It's all about risk opportunity. It's all about risk opportunity. It's all about risk management um in all of their management um in all of their management um in all of their educational materials and and that is educational materials and and that is educational materials and and that is incredibly important. I mean certainly incredibly important. I mean certainly incredibly important. I mean certainly the companies I work with has scanned the companies I work with has scanned the companies I work with has scanned the t terms and conditions of every the t terms and conditions of every the t terms and conditions of every every um every um every um artificial intelligence supplier we have artificial intelligence supplier we have artificial intelligence supplier we have because we really want to understand in because we really want to understand in because we really want to understand in detail what data is being used and where detail what data is being used and where detail what data is being used and where and and protect our our our competitive and and protect our our our competitive and and protect our our our competitive modes. But um modes. But um modes. But um the it's a governance it's a broader the it's a governance it's a broader the it's a governance it's a broader governance issue I think in Australia governance issue I think in Australia governance issue I think in Australia that it's so overindexed on risk rather that it's so overindexed on risk rather that it's so overindexed on risk rather than growth and AI has enormous than growth and AI has enormous than growth and AI has enormous opportunity and growth as well. Um every opportunity and growth as well. Um every opportunity and growth as well. Um every company I work with is launching company I work with is launching company I work with is launching products leveraging some of these new products leveraging some of these new products leveraging some of these new technologies gaining new revenue because technologies gaining new revenue because technologies gaining new revenue because of some of these technologies. of some of these technologies. of some of these technologies. Absolutely. efficiency, potentially cost Absolutely. efficiency, potentially cost Absolutely. efficiency, potentially cost savings, absolutely, but also savings, absolutely, but also savings, absolutely, but also opportunity to serve your customers opportunity to serve your customers opportunity to serve your customers better to to you know the holy grail of better to to you know the holy grail of better to to you know the holy grail of marketing forever come from marketing um marketing forever come from marketing um marketing forever come from marketing um to personalize journeys to personalize journeys to personalize journeys um to the segment of one. um to the segment of one. um to the segment of one. Welcome to AI. you know, you have that Welcome to AI. you know, you have that Welcome to AI. you know, you have that that ability now in a marketing context, that ability now in a marketing context, that ability now in a marketing context, in every life cycle for every customer in every life cycle for every customer in every life cycle for every customer to personalize to one. Um, be careful to personalize to one. Um, be careful to personalize to one. Um, be careful when you do and how you do all of those when you do and how you do all of those when you do and how you do all of those usual judgment questions. Um, but I usual judgment questions. Um, but I usual judgment questions. Um, but I think opportunity it needs to be much think opportunity it needs to be much think opportunity it needs to be much more where boards are directing the more where boards are directing the more where boards are directing the questions. um once some risk guardrails questions. um once some risk guardrails questions. um once some risk guardrails of course are in place, but our teams of course are in place, but our teams of course are in place, but our teams aren't silly. We also need to encourage aren't silly. We also need to encourage aren't silly. We also need to encourage some risk appetite around new technology some risk appetite around new technology some risk appetite around new technology because you just don't know where it because you just don't know where it because you just don't know where it will end and you do not want to not be will end and you do not want to not be will end and you do not want to not be part of it. part of it. part of it. >> Yeah, absolutely. But I like what you >> Yeah, absolutely. But I like what you >> Yeah, absolutely. But I like what you said that the ultimate goal is growth. said that the ultimate goal is growth. said that the ultimate goal is growth. You know, everything else that we do is You know, everything else that we do is You know, everything else that we do is to get us to growth. [snorts] Um and so to get us to growth. [snorts] Um and so to get us to growth. [snorts] Um and so the governance while you need to be the governance while you need to be the governance while you need to be mindful we need to work out a way to to mindful we need to work out a way to to mindful we need to work out a way to to navigate I know you have a strong navigate I know you have a strong navigate I know you have a strong perspective here how should leaders be perspective here how should leaders be perspective here how should leaders be thinking about governance as an enabler thinking about governance as an enabler thinking about governance as an enabler rather than a constraint. rather than a constraint. rather than a constraint. >> Yeah I mean I would echo a lot of what >> Yeah I mean I would echo a lot of what >> Yeah I mean I would echo a lot of what Helen said that we're fortunate again Helen said that we're fortunate again Helen said that we're fortunate again probably because of the industry we're probably because of the industry we're probably because of the industry we're in. Our board is very much about what in. Our board is very much about what in. Our board is very much about what can we do with this? what are all the can we do with this? what are all the can we do with this? what are all the you know I think if you're in a uh you know I think if you're in a uh you know I think if you're in a uh engineering product technology company engineering product technology company engineering product technology company but frankly probably most companies you but frankly probably most companies you but frankly probably most companies you always have this um paradox of choice always have this um paradox of choice always have this um paradox of choice there's usually more you want to do than there's usually more you want to do than there's usually more you want to do than you can do today you can do today you can do today >> and so I think if we see AI or any >> and so I think if we see AI or any >> and so I think if we see AI or any technological change as freeing up technological change as freeing up technological change as freeing up capacity freeing up time allowing you to capacity freeing up time allowing you to capacity freeing up time allowing you to go after new opportunities that maybe go after new opportunities that maybe go after new opportunities that maybe were too cost prohibitive before too were too cost prohibitive before too were too cost prohibitive before too complicated whatever it might be then I complicated whatever it might be then I complicated whatever it might be then I think it changes the conversation think it changes the conversation think it changes the conversation completely completely completely Um and but but you know we are a large Um and but but you know we are a large Um and but but you know we are a large company and everyone has to make sure company and everyone has to make sure company and everyone has to make sure you are secure but we did a similar you are secure but we did a similar you are secure but we did a similar thing where we got a tiger team together thing where we got a tiger team together thing where we got a tiger team together legal risk small group uh you know legal risk small group uh you know legal risk small group uh you know internal IT internal IT internal IT your goal with our risk appetite being your goal with our risk appetite being your goal with our risk appetite being slightly higher is to say how do we help slightly higher is to say how do we help slightly higher is to say how do we help us move faster so you don't have to us move faster so you don't have to us move faster so you don't have to change every process you just get the change every process you just get the change every process you just get the right few people together they know right few people together they know right few people together they know their job is to make sure that the right their job is to make sure that the right their job is to make sure that the right safe AI tools can come into the business safe AI tools can come into the business safe AI tools can come into the business as quickly as possible with some cost as quickly as possible with some cost as quickly as possible with some cost guard rails but then unleash our team guard rails but then unleash our team guard rails but then unleash our team members to do as much experimentation members to do as much experimentation members to do as much experimentation and get the benefit of it. and get the benefit of it. and get the benefit of it. >> I like what you said about bringing that >> I like what you said about bringing that >> I like what you said about bringing that team together. Who did you have on that team together. Who did you have on that team together. Who did you have on that in that group? You said legal in that group? You said legal in that group? You said legal >> legal risk and it >> legal risk and it >> legal risk and it >> legal risk and IT. So you're getting >> legal risk and IT. So you're getting >> legal risk and IT. So you're getting everybody on board. You're making it everybody on board. You're making it everybody on board. You're making it their responsibility to drive that drive their responsibility to drive that drive their responsibility to drive that drive that innovation. that innovation. that innovation. >> Yeah. Rather than trying to be like well >> Yeah. Rather than trying to be like well >> Yeah. Rather than trying to be like well you know why are you it's just like the you know why are you it's just like the you know why are you it's just like the goal is keep us safe and secure. That is goal is keep us safe and secure. That is goal is keep us safe and secure. That is your job. Uh but here is the goal for your job. Uh but here is the goal for your job. Uh but here is the goal for the company. We need as many of these the company. We need as many of these the company. We need as many of these tools to be able to come in, get them in tools to be able to come in, get them in tools to be able to come in, get them in securely and help our employees get securely and help our employees get securely and help our employees get access so they can go after the next access so they can go after the next access so they can go after the next opportunity and then they feel empowered opportunity and then they feel empowered opportunity and then they feel empowered to go enable that for the company as to go enable that for the company as to go enable that for the company as opposed to being seen as the handbrake opposed to being seen as the handbrake opposed to being seen as the handbrake which I think is quite liberating for which I think is quite liberating for which I think is quite liberating for them. them. them. >> Yeah. So you put them in the driver's >> Yeah. So you put them in the driver's >> Yeah. So you put them in the driver's seat of making it happen and unleashing seat of making it happen and unleashing seat of making it happen and unleashing the the freedom to do what we need to do the the freedom to do what we need to do the the freedom to do what we need to do with AI. I think that's really powerful. with AI. I think that's really powerful. with AI. I think that's really powerful. We need to think about the way we apply We need to think about the way we apply We need to think about the way we apply AI in terms of it being institutional AI in terms of it being institutional AI in terms of it being institutional and not individual. And I talked a bit and not individual. And I talked a bit and not individual. And I talked a bit about this before when you do what about this before when you do what about this before when you do what Angad's just describing where you put Angad's just describing where you put Angad's just describing where you put it, you know, you talk about what's the it, you know, you talk about what's the it, you know, you talk about what's the outcome that we're trying to drive and outcome that we're trying to drive and outcome that we're trying to drive and then we put the team together that's not then we put the team together that's not then we put the team together that's not only going to help like release the only going to help like release the only going to help like release the governance that that's going to make governance that that's going to make governance that that's going to make that happen, but then you probably also that happen, but then you probably also that happen, but then you probably also got a technology team that's actually got a technology team that's actually got a technology team that's actually building what you need. Then we're building what you need. Then we're building what you need. Then we're creating something inside a business creating something inside a business creating something inside a business that is creating growth and that's that is creating growth and that's that is creating growth and that's really meaningful rather than making really meaningful rather than making really meaningful rather than making tools available and saying, you know, tools available and saying, you know, tools available and saying, you know, everybody have a go at creating some everybody have a go at creating some everybody have a go at creating some efficiency with AI. So, I think that's efficiency with AI. So, I think that's efficiency with AI. So, I think that's really meaningful. I want to ask you to really meaningful. I want to ask you to really meaningful. I want to ask you to share something with us that's going to share something with us that's going to share something with us that's going to allow us to close on something really allow us to close on something really allow us to close on something really concrete. Um, so I'm going to come to concrete. Um, so I'm going to come to concrete. Um, so I'm going to come to all of you. I'm going to start with you,

all of you. I'm going to start with you, all of you. I'm going to start with you, Will. Of everything that you've heard Will. Of everything that you've heard Will. Of everything that you've heard today, what is the one thing that today, what is the one thing that today, what is the one thing that leaders should consider doubling down leaders should consider doubling down leaders should consider doubling down on? What would your advice be for people on? What would your advice be for people on? What would your advice be for people in the room? in the room? in the room? >> Uh, I would say experimenting. Um, I I I >> Uh, I would say experimenting. Um, I I I >> Uh, I would say experimenting. Um, I I I said at the PC purgatory comment before, said at the PC purgatory comment before, said at the PC purgatory comment before, but it's still really important to make but it's still really important to make but it's still really important to make sure that there's broad adoption. And so sure that there's broad adoption. And so sure that there's broad adoption. And so I think making big bets is really I think making big bets is really I think making big bets is really important. So we don't want to go away important. So we don't want to go away important. So we don't want to go away from that. But there's still so many new from that. But there's still so many new from that. But there's still so many new technologies. There's new models. technologies. There's new models. technologies. There's new models. There's new frameworks. There's new There's new frameworks. There's new There's new frameworks. There's new agents. Like um it's not a technology agents. Like um it's not a technology agents. Like um it's not a technology where you can make a decision in January where you can make a decision in January where you can make a decision in January and come back and see the results in and come back and see the results in and come back and see the results in December. So I think having this sort of December. So I think having this sort of December. So I think having this sort of appetite for playing uh for appetite for playing uh for appetite for playing uh for understanding what's coming for making understanding what's coming for making understanding what's coming for making sure that you're always like having it sure that you're always like having it sure that you're always like having it in your hands. I think that would be the in your hands. I think that would be the in your hands. I think that would be the thing that all leaders should likely be thing that all leaders should likely be thing that all leaders should likely be doing at the moment. Um I do my personal doing at the moment. Um I do my personal doing at the moment. Um I do my personal life, but I think also it permeates the life, but I think also it permeates the life, but I think also it permeates the the work life as well. the work life as well. the work life as well. >> And can I come to you? >> And can I come to you? >> And can I come to you? >> Uh yeah, if I can cheat, I'll give you >> Uh yeah, if I can cheat, I'll give you >> Uh yeah, if I can cheat, I'll give you two. I think um [snorts] two. I think um [snorts] two. I think um [snorts] >> one I would say use it, but use it >> one I would say use it, but use it >> one I would say use it, but use it yourself as a leader. Like build build yourself as a leader. Like build build yourself as a leader. Like build build something, try it out. I think you something, try it out. I think you something, try it out. I think you cannot lead your teams or your cannot lead your teams or your cannot lead your teams or your organization through change if you truly organization through change if you truly organization through change if you truly don't understand how these tools work. don't understand how these tools work. don't understand how these tools work. it. Some things might fail, some things it. Some things might fail, some things it. Some things might fail, some things might surprise you, but I think you have might surprise you, but I think you have might surprise you, but I think you have to have a deep understanding of what is to have a deep understanding of what is to have a deep understanding of what is possible rather than just the hype reel possible rather than just the hype reel possible rather than just the hype reel of, you know, what can be in the media. of, you know, what can be in the media. of, you know, what can be in the media. And then secondly, I would say um and And then secondly, I would say um and And then secondly, I would say um and we'll touch on it earlier, be very clear we'll touch on it earlier, be very clear we'll touch on it earlier, be very clear about where you want human about where you want human about where you want human accountability. You will want it. It's accountability. You will want it. It's accountability. You will want it. It's critically important. critically important. critically important. >> And instead of just thinking about how >> And instead of just thinking about how >> And instead of just thinking about how we're going to redesign the process of we're going to redesign the process of we're going to redesign the process of where there are less humans, how are we where there are less humans, how are we where there are less humans, how are we going to redesign the process? Where do going to redesign the process? Where do going to redesign the process? Where do we want the humans? Where do we want the we want the humans? Where do we want the we want the humans? Where do we want the agents? And how can the agents agents? And how can the agents agents? And how can the agents accelerate what the humans are are accelerate what the humans are are accelerate what the humans are are already doing? already doing? already doing? >> Yeah. >> Yeah. >> Yeah. >> Yeah. Awesome. Thank you, Helen. Totally >> Yeah. Awesome. Thank you, Helen. Totally >> Yeah. Awesome. Thank you, Helen. Totally agree. Um, but I think we're living in agree. Um, but I think we're living in agree. Um, but I think we're living in such volatile times just geopolitically such volatile times just geopolitically such volatile times just geopolitically alone. alone. alone. >> Yeah. Cringe ever every day. And, uh, AI >> Yeah. Cringe ever every day. And, uh, AI >> Yeah. Cringe ever every day. And, uh, AI and this transformational technology and this transformational technology and this transformational technology that is just moving at a pace I've never that is just moving at a pace I've never that is just moving at a pace I've never seen in a 30-year career in digital. Um, seen in a 30-year career in digital. Um, seen in a 30-year career in digital. Um, there is, I think, a bit of a temptation there is, I think, a bit of a temptation there is, I think, a bit of a temptation for people to put their head in the for people to put their head in the for people to put their head in the sand. You know, geopolitics at the sand. You know, geopolitics at the sand. You know, geopolitics at the moment. There's more people than ever moment. There's more people than ever moment. There's more people than ever not watching the news. I realize this not watching the news. I realize this not watching the news. I realize this sounds like a red hearing, but I think sounds like a red hearing, but I think sounds like a red hearing, but I think what we mustn't do is put our heads in what we mustn't do is put our heads in what we mustn't do is put our heads in the sand. Australia mustn't put its head the sand. Australia mustn't put its head the sand. Australia mustn't put its head in the sand in this very volatile, very in the sand in this very volatile, very in the sand in this very volatile, very fastchanging time. We need to lean in fastchanging time. We need to lean in fastchanging time. We need to lean in and see opportunity. So my my leaders and see opportunity. So my my leaders and see opportunity. So my my leaders opportunity. We've covered a lot today opportunity. We've covered a lot today opportunity. We've covered a lot today from why the gap between AI ambition and from why the gap between AI ambition and from why the gap between AI ambition and commercial reality still exists for so commercial reality still exists for so commercial reality still exists for so many organizations to what it actually many organizations to what it actually many organizations to what it actually takes to build uh internal conviction takes to build uh internal conviction takes to build uh internal conviction around AI. Get the data foundations around AI. Get the data foundations around AI. Get the data foundations right and then put governance in place right and then put governance in place right and then put governance in place that enables speed but doesn't kill it. that enables speed but doesn't kill it. that enables speed but doesn't kill it. Um, and I think what sits underneath it Um, and I think what sits underneath it Um, and I think what sits underneath it all is a simple truth that the all is a simple truth that the all is a simple truth that the organizations that are winning at the organizations that are winning at the organizations that are winning at the moment, they're not waiting for perfect moment, they're not waiting for perfect moment, they're not waiting for perfect conditions. They are they're making conditions. They are they're making conditions. They are they're making deliberate choices about outcomes, about deliberate choices about outcomes, about deliberate choices about outcomes, about access, and about where humans stay access, and about where humans stay access, and about where humans stay involved to your point. Um, and they've involved to your point. Um, and they've involved to your point. Um, and they've started to your point and the context started to your point and the context started to your point and the context underlying uh is what makes AI actually underlying uh is what makes AI actually underlying uh is what makes AI actually work. your customer data, your team's work. your customer data, your team's work. your customer data, your team's knowledge, your business history. Um, knowledge, your business history. Um, knowledge, your business history. Um, and that's not going to sort itself out. and that's not going to sort itself out. and that's not going to sort itself out. The organizations pulling ahead are the The organizations pulling ahead are the The organizations pulling ahead are the ones that are investing in that ones that are investing in that ones that are investing in that foundation now and then letting their foundation now and then letting their foundation now and then letting their teams and their agents do work together. teams and their agents do work together. teams and their agents do work together. So, I hope today's conversation gives So, I hope today's conversation gives So, I hope today's conversation gives you something concrete to take away. you something concrete to take away. you something concrete to take away. Please join me in thanking Will Angard Please join me in thanking Will Angard Please join me in thanking Will Angard and Helen [applause]