Latest / The Adults In The AI Room / Earley AI Podcast - Episode 83: AI, Governance, and the Execution Gap with Brian Stafford

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Earley AI Podcast - Episode 83: AI, Governance, and the Execution Gap with Brian Stafford · The Adults In The AI Room

• 0:01
  SPEAKER_00: This is the Early AI Podcast hosted by Seth to a detailed detail to the actions, expertise, and experiences of artificialists to talk about what's possible for artificial intelligence.
• 0:14
  SPEAKER_00: The Early AI Podcast is sponsored by Early Information Science for a digital transformation journey with design and deployment of innovative technology solutions as well as Better.
• 0:26
  SPEAKER_00: Now enjoy the show.
• 0:28
  SPEAKER_02: Welcome to the Early AI Podcast.
• 0:31
  SPEAKER_02: I'm your host, Seth Early, and each episode we jump into different challenges and issues around AI adoption and how organizations need to be prepared, how they need to execute, and how they need to operationalize AI.
• 0:44
  SPEAKER_02: Today we're going to be looking at how AI is influencing governance, risk, and compliance and what it takes to lead in this rapidly changing environment, right?
• 0:52
  SPEAKER_02: The technology is changing so quickly it's it's very, very difficult, even for the experts, to keep up with that.
• 0:59
  SPEAKER_02: So joining to me today is Brian Stafford, a CEO of Diligent, a$700 million global software and AI company focused on governance, risk, and compliance.
• 1:08
  SPEAKER_02: Brian has served as CEO for the past 10 years, guiding the organization through growth and innovation.
• 1:13
  SPEAKER_02: Before joining Diligent, he was a partner at McKinsey and Company and an entrepreneur based in New York City with his wife and four kids.
• 1:20
  SPEAKER_02: He is uh uh draws on a diverse background in consulting, entrepreneurship, and executive leadership to help organizations navigate very complex challenges.
• 1:28
  SPEAKER_02: Brian, welcome to the show.
• 1:30
  SPEAKER_01: Thanks for me having thanks for having me here, Seth, and I'm looking forward to the discussion.
• 1:33
  SPEAKER_02: Great.
• 1:33
  SPEAKER_02: So I like to start with um a challenge, uh, issues around misconceptions around AI.
• 1:39
  SPEAKER_02: What are organizations not getting?
• 1:41
  SPEAKER_02: Go into an enterprise, and that's changing over time, but what are they not getting?
• 1:45
  SPEAKER_02: What are the things that uh that are great misconceptions on the part of leadership, on the part of boards and organizations?
• 1:51
  SPEAKER_01: I think I think for most organizations where we stand now, at least from a CEO perspective, I think that there is a widely held belief that AI is going to be transformative to organizations.
• 2:05
  SPEAKER_01: And so I think we've crossed the, for most organizations, crossed beyond the what.
• 2:10
  SPEAKER_01: And now many organizations are into the mode of how.
• 2:13
  SPEAKER_01: How do you actually get there?
• 2:14
  SPEAKER_01: How do you actually get either the productivity, the insights, the growth, or whatever it might end up being?
• 2:19
  SPEAKER_01: And I think a lot of organizations are still struggling with the how.
• 2:23
  SPEAKER_02: So so what are they not getting?
• 2:25
  SPEAKER_02: Like what are the things that are getting in their ways?
• 2:27
  SPEAKER_02: Or when you talk to a board, what are the parts that they either misunderstand or don't understand?
• 2:33
  SPEAKER_01: I think it's a lack of capabilities within the organization.
• 2:35
  SPEAKER_01: And so there is awareness, there is knowledge, but how do I actually drive that transformation in my support organization?
• 2:43
  SPEAKER_01: How do I actually use AI to transform the way that we interact with our clients?
• 2:48
  SPEAKER_01: And I think that's where the gap breaks down.
• 2:50
  SPEAKER_01: And there's a lot of organizations out there and kind of joke about it and call it like website AI.
• 2:54
  SPEAKER_01: You go to a company's website and it talks about all the different AI capabilities that exist, but then you know, but then when in practice, what does that mean beyond, you know, a button that does really, really basic stuff?
• 3:06
  SPEAKER_01: Because the button that does basic stuff, um, candidly, we can all do that on our own.
• 3:10
  SPEAKER_01: Uh we can all do that through Chat GPT, anthropic law, whatever else it ends up being.
• 3:14
  SPEAKER_01: But how do you actually really fundamentally drive that change?
• 3:16
  SPEAKER_02: Yeah, so it's not necessarily a misconception, it's just a lack of knowledge.
• 3:20
  SPEAKER_02: So they're not laboring under uh you know false ideas.
• 3:24
  SPEAKER_02: They're just saying, okay, I get it, it's gonna be transformational, but really how do I do it?
• 3:28
  SPEAKER_01: Yeah, I I I read, I see McKinsey publish, but any other any other uh um consulting organization that you know function X is going to be transformed by 20% or made you know 50% more efficient.
• 3:41
  SPEAKER_01: And so a CEO then goes and looks at that function and says, okay, now how do we actually get there and how do we effectively do it?
• 3:48
  SPEAKER_01: And you see some organizations, and it is part of the knowledge capabilities, kind of some maturity matrix that actually talks about why some clients are further along on that journey than others.
• 3:57
  SPEAKER_01: But I think many organizations are still in the early stages of driving that.
• 4:00
  SPEAKER_01: Because I mean you'll you'll read, you'll see the CEO needs to be the champion of AI transformation, okay?
• 4:05
  SPEAKER_01: But the CEO needs to make sure that there are people capable within the organization who can actually actually take it on and actually drive it.
• 4:11
  SPEAKER_02: So, and and a lot of organizations are kind of doing these point solutions.
• 4:15
  SPEAKER_02: They're doing pilots, and the pilots don't get out of pilot mode, right?
• 4:18
  SPEAKER_02: They get stuck in pilots and it's hard to operationalize.
• 4:21
  SPEAKER_02: What do you see?
• 4:22
  SPEAKER_02: And I I showed you a little bit of the framework that we look at when we kind of consider this.
• 4:26
  SPEAKER_02: What are your thoughts about readiness and maturity?
• 4:29
  SPEAKER_02: Do you look at this and do you help your organizations, your client organizations, understand their readiness?
• 4:34
  SPEAKER_02: And if so, what what are the elements of that from your perspective?
• 4:38
  SPEAKER_01: Sure.
• 4:38
  SPEAKER_01: Well, first off, I'd have to say I hate the term pilot.
• 4:41
  SPEAKER_01: Like I really, really hate the term pilot.
• 4:43
  SPEAKER_01: I think pilot gives organizations the license to actually call something unsuccessful.
• 4:48
  SPEAKER_01: So now it's just the pilot.
• 4:50
  SPEAKER_01: Yeah, exactly.
• 4:51
  SPEAKER_01: Exactly.
• 4:51
  SPEAKER_01: And so if you call it a pilot, it's why I don't know, like a stat was raised like I don't know, six months ago that said, you know, seven 70% of AI initiatives fail.
• 5:00
  SPEAKER_01: Well, that's because you call them pilots and you give people excuses to, you know, to um uh call it the pilot didn't work well, we didn't see the value and move on.
• 5:07
  SPEAKER_01: Because I think it's ultimately it's a transformation across an organization, which will include trying many things, but like as part of that transformation, you'll have things that work better than you thought and things that didn't work as well as you thought.
• 5:19
  SPEAKER_01: But that transformation, you don't set you're not piloting a transformation.
• 5:23
  SPEAKER_01: You're either driving it and you start with a few different initiatives.
• 5:26
  SPEAKER_01: And I think the most successful organizations are, you know, aware of what the problem is, skill and make sure that the team has the right knowledge, have some sort of operational capabilities that they can actually make it happen, and then have a little bit of leadership and vision to actually drive it through with, like as as as you have a framework, with the right governance around those projects actually being successful long term.
• 5:44
  SPEAKER_02: Yeah.
• 5:44
  SPEAKER_02: And so, you know, when when organ uh we call them proof of value, by the way, when we do them, because what we want to do is we want to use production data, we want to make sure it can be scaled and and and operationalized, right?
• 5:56
  SPEAKER_02: So so I'm with you on the proof of concept idea that it is kind of an excuse to not fail, not succeed in and oh, it's just a pilot, right?
• 6:05
  SPEAKER_02: Proof of concept.
• 6:06
  SPEAKER_02: So we're a pilot.
• 6:07
  SPEAKER_02: So anyway, so when you think about where you see organizations, what what are you uh are they understanding that this is kind of multidimensional, that they do need to have a many, many pieces in place, that they do need to embed this in the operations of the organization?
• 6:22
  SPEAKER_02: Because I see a lot of uh enterprises doing lots of individual point solutions and lots of experimentation, not necessarily integrating this uh you know holistically throughout the organization.
• 6:34
  SPEAKER_02: What is your experience uh with with uh Yeah, and I can give you the experience in two sides.
• 6:39
  SPEAKER_01: One of it is uh the transformation that we're driving a diligent, and second, the transformation that our clients are driving.
• 6:45
  SPEAKER_01: And I, you know, I've shared with our team many, many times that um, and I'm really, really passionate about that.
• 6:51
  SPEAKER_01: You know, we're a company that that sells, you know, so software and AI to our clients that that ultimately they're looking for outcomes.
• 6:59
  SPEAKER_01: And I fundamentally believe that making sure that we're driving an effective AI transformation internally will make our products better because we're in we see what works in our own transformation of different departments.
• 7:10
  SPEAKER_01: And you see then you put on your product hat and says, Well, I don't think we're going far enough.
• 7:15
  SPEAKER_01: How do we go farther to make sure we're having real impact for our clients?
• 7:17
  SPEAKER_01: Because when I look internally at Diligent and we have our own transformation goals and transformation targets around how AI is going to transform how we do business and how we operate.
• 7:25
  SPEAKER_01: And the reality is I'm not looking for people buying products, I'm looking for people transforming and getting more leverage out of their business.
• 7:33
  SPEAKER_01: And so it makes you very, very aware to say, well, how are we talking about our products?
• 7:37
  SPEAKER_01: How are we talking about that transformation that we're ultimately driving with our products for our clients?
• 7:41
  SPEAKER_01: Because again, I'm I'm not looking for people buying a bunch of software.
• 7:44
  SPEAKER_01: I'm looking for people, I'm looking for our own teams to actually drive real transformation.
• 7:48
  SPEAKER_01: And so when we go into our clients, if you actually have that right mindset, we sell software into legal departments, compliance departments, audit department, risk departments.
• 7:57
  SPEAKER_01: And it's helpful to know and have that framing that each of those departments likely has some sort of AI-driven goal that's been handed down by the CEO.
• 8:05
  SPEAKER_01: So whether that is compliance has to be able to do way more with less resources.
• 8:09
  SPEAKER_01: Okay, great.
• 8:10
  SPEAKER_01: So when you go in and talk to a client, you don't talk about your features.
• 8:13
  SPEAKER_01: You talk about how you can help them transform their compliance organization so they can um keep up with and make good on all the compliance challenges and complexities, but they can do so with the same, if not fewer, people.
• 8:24
  SPEAKER_01: I think that's ultimately the framing.
• 8:26
  SPEAKER_01: Doing that through people, for the most part, don't care how they're doing it.
• 8:28
  SPEAKER_01: I think people want to put a check mark next to we're doing it through AI.
• 8:31
  SPEAKER_01: But ultimately, they're looking to say, how do I get much more efficient in my business?
• 8:34
  SPEAKER_01: And you can do that with AI-powered software.
• 8:37
  SPEAKER_02: Right.
• 8:38
  SPEAKER_02: And and AI technology is one element of that, but there's lots of other pieces that need to be in place and need to be a part of the system.
• 8:46
  SPEAKER_01: A large, a large client of ours, um, and I won't uh share the name of it, came and said, Hey, you know, for one of the areas of their business that we sell software in, they would like to completely automate that function.
• 8:55
  SPEAKER_01: And they currently have a large team of place, a large team in place actually doing that.
• 9:00
  SPEAKER_01: And they want to use AI and agents to actually make sure that's automated in the future.
• 9:04
  SPEAKER_01: The client said, That's our goal.
• 9:05
  SPEAKER_01: We're gonna do it.
• 9:06
  SPEAKER_01: It's a five-year plan.
• 9:07
  SPEAKER_01: This is what we're working on.
• 9:08
  SPEAKER_01: This has been pushed down.
• 9:09
  SPEAKER_01: It's not just for our function, but it's for every function.
• 9:11
  SPEAKER_01: And the conversation with them was we can help you do that.
• 9:14
  SPEAKER_01: Here's how we do that with our product and help you do that and drive it.
• 9:17
  SPEAKER_01: And they're on the hook to meet a target from their organization, and ultimately they need partners to help them do it.
• 9:23
  SPEAKER_01: And I think the most successful SaaS companies, AI companies, are the ones that just say, look, what are the outcomes and how does AI help to deliver that for you, as opposed to just um, you know, pilots?
• 9:34
  SPEAKER_02: Sure.
• 9:34
  SPEAKER_02: Yeah, it might that makes a lot of sense.
• 9:35
  SPEAKER_02: And and tell me, you know, without necessarily getting into a commercial for diligent, but tell me how diligent helps.
• 9:41
  SPEAKER_02: Like what do they what do you guys do for that?
• 9:43
  SPEAKER_02: Yeah, so so it's how do you how do you help uh catalyze those changes?
• 9:46
  SPEAKER_01: It's pretty, it's pretty um, pretty straightforward.
• 9:48
  SPEAKER_01: So a little bit of the history of diligent.
• 9:50
  SPEAKER_01: So diligent started out as a as a governance company.
• 9:53
  SPEAKER_01: And so we are fortunate enough to work with 70% of the Fortune 1000, 70% of the FTSE 100, two-thirds of the DAX 30, same thing in Australia.
• 10:01
  SPEAKER_01: So it's a big global footprint um across leading organizations.
• 10:04
  SPEAKER_01: Um and we work with thousands of mid-market companies too.
• 10:07
  SPEAKER_01: And we help you improve how you do governance.
• 10:09
  SPEAKER_01: So, how management connects with the board, how you make sure that you have the right information, right conversations, connectivity, and all the workflows around that.
• 10:16
  SPEAKER_01: Um, over time, we found that boards and CEOs were spending way more time on areas like risk and compliance because the risks coming at us have just increased dramatically over the last 10 years.
• 10:25
  SPEAKER_01: I mean, areas of compliance, if if you mess up and get it wrong, you're gonna be embarrassed by whatever jurisdiction you operate in and their government.
• 10:31
  SPEAKER_01: And so we um we moved into solutions that help um our clients in those ways.
• 10:35
  SPEAKER_01: The reality is, for good or for bad, um areas like risk, areas like compliance, areas like audit, those are areas that are not outside of like highly regulated organizations, they're not areas that are getting massive amounts of incremental budget.
• 10:49
  SPEAKER_01: And so, but they're areas where the complexity continues to increase for our clients over time.
• 10:54
  SPEAKER_01: So it's very, very simple and straightforward.
• 10:56
  SPEAKER_01: The way those clients look at software and the way those clients look at AI is saying, how do I keep up with an increasing set of needs in a department where you know flat um flat is the new up for budget?
• 11:09
  SPEAKER_01: But the reality is if you talk to any CEO out there and you say, look, do you expect your compliance department, do you expect your compliance spend to grow at the same rate at revenue?
• 11:19
  SPEAKER_01: No, no, you don't.
• 11:21
  SPEAKER_01: And what do you expect with your compliance spend over the next five years with AI?
• 11:25
  SPEAKER_01: Everybody expects it to be radically transformed.
• 11:28
  SPEAKER_01: And so you have clients who come to us and say, Diligent, here's the future.
• 11:32
  SPEAKER_01: I need to be compliant with more things.
• 11:34
  SPEAKER_01: And my boss or my boss's boss tells me, and we gotta do it at half or a third the cost.
• 11:40
  SPEAKER_01: And so we ultimately say, and what we do, what we've done with our platform is wire everything we did with AI.
• 11:45
  SPEAKER_01: So rather than just taking and improving workflows for you, we now improve workflows and use agents.
• 11:51
  SPEAKER_01: So you said, look, in order to meet, grow, and exceed whatever your compliance requirements are, you can now do it with um a team that charged with agents doesn't need to be as large.
• 12:00
  SPEAKER_01: And that's ultimately we fell in a very spot where it's really easy for us to deliver for our clients because it's very, very clear to us what they need.
• 12:08
  SPEAKER_01: Increasing compliance obligations is an expectation for decreasing budget, and you're not going to do that in any other way than for a with and with agents.
• 12:15
  SPEAKER_01: And the I mean, you know this very well, but the um, you know, what is really transformative about AI is it's not just the software TAM, but it's the labor TAM as well.
• 12:23
  SPEAKER_01: Because people expect to say, how do I make that more efficient?
• 12:26
  SPEAKER_01: And that's what we do for our clients.
• 12:28
  SPEAKER_02: So so when you think about governance and you think about what a board needs to do and what the CEO needs to do, they need to understand how the investments in AI are working, right?
• 12:39
  SPEAKER_02: How well they're getting uh the return, how uh things are progressing.
• 12:43
  SPEAKER_02: And that kind of can get into pretty deep in the weeds.
• 12:46
  SPEAKER_02: How do you help facilitate that?
• 12:48
  SPEAKER_02: How deep do you go with your governance processes to help, say, monitor investments and monitoring?
• 12:56
  SPEAKER_01: So, how do we help our clients effectively um run governance or manage governance of their AI projects?
• 13:02
  SPEAKER_01: Let me talk about the three different main areas governance, risk, and compliance and how we help our clients and what that looks like.
• 13:07
  SPEAKER_01: On the governance side is exactly what you mentioned.
• 13:09
  SPEAKER_01: On the governance side, where it is we have goals to achieve that we have committed to our board.
• 13:14
  SPEAKER_01: How do we make sure that we're driving the right process to track and make sure that those goals tie to actually, and those activities tied to the goals that we've communicated, either um with our board or even in some cases to our shareholders?
• 13:26
  SPEAKER_01: So we help make it really easy to track that, look longitudinally, and we use AI to do that.
• 13:30
  SPEAKER_01: What did I say?
• 13:31
  SPEAKER_01: What did I commit?
• 13:32
  SPEAKER_01: How am I tracking on it?
• 13:33
  SPEAKER_01: How does it tie to different initiatives going internally and making it really easy to actually do that and track that longitudinally over time as management, as the CEO, and the board?
• 13:41
  SPEAKER_01: On the compliance side, we talked about on the compliance side, it's it's a cost optimization efficiency job, making sure that you don't lower the bar from a um uh from a compliance obligation side.
• 13:52
  SPEAKER_01: Um, that's also true of audit, where people have the same goals but want to be able to do it in an efficient way with agents and less people.
• 13:57
  SPEAKER_01: On the risk side, it's interesting and it ties back to the governance side, risk being more strategic, where the promise of AI, the challenge with risk is signal and noise.
• 14:06
  SPEAKER_01: How do I understand with all the things coming out of me?
• 14:08
  SPEAKER_01: How do I help to understand?
• 14:09
  SPEAKER_01: How do I help to separate the signal from the noise?
• 14:12
  SPEAKER_01: And AI actually gives you the ability to do that.
• 14:15
  SPEAKER_01: And it's a in a really, really powerful way.
• 14:18
  SPEAKER_01: We try to make it very, very accessible for any organization to actually manage risk.
• 14:23
  SPEAKER_01: And we help to make it really, really easy for that organization to keep it always on, continuously monitoring and make sure you're aware of those things because the risk is what will keep you from achieving those obligations and those goals that you said actually to your board, and ultimately you're being successful in that AI transformation.
• 14:39
  SPEAKER_02: Interesting.
• 14:39
  SPEAKER_02: So when you look across your your your customers and your the industries that they're in in the sectors, I'm sure that the preparedness and the readiness and the maturity is lumpy, right?
• 14:50
  SPEAKER_02: There's some sectors that are more ready than others.
• 14:54
  SPEAKER_02: How would you kind of classify them?
• 14:56
  SPEAKER_02: What kind of buckets would you put them in?
• 14:58
  SPEAKER_02: I know you mentioned that there's some that don't want anything to do with AI, right?
• 15:01
  SPEAKER_01: And there's some embracement.
• 15:03
  SPEAKER_01: It's interesting.
• 15:03
  SPEAKER_01: Um I I think most CEOs would tell you.
• 15:07
  SPEAKER_01: I I I think there are few and fewer and fewer organizations, I think over time, that are not at least AI aware and know that AI applied to certain businesses or functions ultimately is going to be required.
• 15:22
  SPEAKER_01: And you know, however you define is going to be required.
• 15:24
  SPEAKER_01: It's either going to be required from the board, gonna be required by their shareholders, gonna be required to keep up with the competition, et cetera.
• 15:30
  SPEAKER_01: So I think that the number of organizations that are, you know, I'm not touching AI with a 10-foot pole, you know, gets fewer and fewer, you know, every six months or every year.
• 15:40
  SPEAKER_01: So we did have clients who would say that initially, and I can remember one very distinct one who said, you know, I'm not touching AI.
• 15:46
  SPEAKER_01: But a year later, saying, Well, how do we pick the right places to go and experiment?
• 15:51
  SPEAKER_01: I think you have a lot of clients who are in the launching pilots, go back to your thing, fashion, and you know, and who are gonna have to manage through the fact that it can't just be pilots, it has to be transformation.
• 16:03
  SPEAKER_01: Then I think you see the next tranche of clients that's actually really starting to tackle functions and drive real change.
• 16:09
  SPEAKER_01: And then I think you see the last liver, which is a truly unique and special set of companies who are actually really transforming their organizations with AI.
• 16:17
  SPEAKER_01: More of those organizations tend to sit in Silicon Valley or other innovation hubs.
• 16:22
  SPEAKER_01: Um uh, but you'll see you're seeing that they're 10x more productive um than the average organization.
• 16:27
  SPEAKER_01: And then how does it long take for the people in the middle of the pack or even the people who are leading the way to get up to that 10x way?
• 16:32
  SPEAKER_01: And I think that is still just a handful of organizations.
• 16:35
  SPEAKER_02: So, and and would you say it is it is it kind of heterogeneous across uh sectors and and industries, or do you see some patterns emerge?
• 16:44
  SPEAKER_02: Or are there certain size organizations that are in in each of these buckets?
• 16:49
  SPEAKER_01: How do you kind of it's it's a great question?
• 16:51
  SPEAKER_01: I I I don't um I have not seen as much of a variance by sector per se.
• 16:57
  SPEAKER_01: Let me sorry, remove remove technology, remove tech companies who you know, AI is much their product as it is like their business, and it like it it's everybody everybody is an AI company.
• 17:08
  SPEAKER_02: Exactly.
• 17:09
  SPEAKER_01: It has to be at some at some level there.
• 17:11
  SPEAKER_01: I think with other organizations, it's really interesting.
• 17:13
  SPEAKER_01: It's um, I think it is much, it is not sector or size of company specific.
• 17:17
  SPEAKER_01: You can put a little asterisk next to companies like in healthcare or other places that have HIPAA and other requirements that you know require a ton of additional club flexible.
• 17:24
  SPEAKER_01: I think it's almost leadership driven.
• 17:26
  SPEAKER_01: Like I was blown away by a large insurer um who's one of our clients, where the CEO has mandated that every single role or function, every single role has a digital twin, an AI capability that they'll build up every single role, up and including the board, where every single role actually has that and they're driving that.
• 17:43
  SPEAKER_01: And they expect that digital twin to be able to do the role of those individuals, and then eventually, I don't know, maybe it automates that role over time or you know makes those people 10x the um productive or whatever might end up being.
• 17:56
  SPEAKER_01: And I would assume that there are other insurers who are maybe not as aggressive in their journey and picking a few departments or spots to try it.
• 18:03
  SPEAKER_01: And so I do think it is as much leadership driven.
• 18:06
  SPEAKER_01: Um I also our business is quite global, and so I go around the globe as well.
• 18:10
  SPEAKER_01: And you know, I think uh I've been more impressed than I thought I would be, even around some European companies and they're leaning in and transformation.
• 18:19
  SPEAKER_01: And I think part of it is specific to the type of work and functions we do.
• 18:24
  SPEAKER_01: Given the excessive regulation that exists in some places in Europe, I think some of those organizations are having to lean in more because that's just kind of the only way you can deal with it.
• 18:32
  SPEAKER_01: And so I think it is really a mixed bag.
• 18:34
  SPEAKER_01: I don't think uh, like I said, I think the prevailing wisdom in the US is that Europe is further behind on AI, but I haven't necessarily seen that, at least within the functions that we work on.
• 18:44
  SPEAKER_01: So I think you've seen enough companies leaning in.
• 18:47
  SPEAKER_02: It's so interesting.
• 18:48
  SPEAKER_02: Um, and I and again, you're always going to have the outliers right on either end of the spectrum.
• 18:52
  SPEAKER_02: Uh so it's interesting to hear that whole idea of every role having a digital twin.
• 18:57
  SPEAKER_02: That's that's fascinating.
• 18:58
  SPEAKER_02: And I could see how that could lead to a lot of interesting opportunities and challenges and so on.
• 19:03
  SPEAKER_02: Tell me where you feel or where you observe that organizations are have the greatest gaps in terms of their preparedness, their ability to execute.
• 19:13
  SPEAKER_02: What what what is missing?
• 19:14
  SPEAKER_02: I mean, data is a big piece of this.
• 19:16
  SPEAKER_01: I think I think there is a massive gap in ability to execute.
• 19:19
  SPEAKER_01: Like I just think it's a massive gap.
• 19:21
  SPEAKER_01: I think it is it is a chasm.
• 19:22
  SPEAKER_01: I think it is between the conversations that happen at the CEO and board level, even for the most committed CEOs who say, we're gonna transform what we do.
• 19:31
  SPEAKER_01: Okay, then that's the what.
• 19:33
  SPEAKER_01: And then the how.
• 19:34
  SPEAKER_01: How do we do it?
• 19:36
  SPEAKER_01: And I think the gap between understanding and reading um, you know, a case study around how an organization had their, like I said, and like I mentioned earlier, their support organization become, you know, 2x as productive or whatever it might end up being, um, or required half as many people to meet that target.
• 19:52
  SPEAKER_01: Well, how do you actually do that?
• 19:54
  SPEAKER_01: And that's where that's where the gap is.
• 19:56
  SPEAKER_01: Um, some companies, some partners, some organizations are helping to fill that gap.
• 20:01
  SPEAKER_01: And if CEOs know, diligence is actually going to help me drive that transformation and compliance that I'm asking for, I can put a check next to, okay, make this function 50% more productive.
• 20:13
  SPEAKER_01: Like as you go through those, as you separate from the the noise and like the website AI from the actual impact, I think that's where the gap still exists.
• 20:20
  SPEAKER_01: You see the impact in functions, of course, that you know, um, I'm sure you've talked about before, but areas like, you know, in developer tools and engineering productivity or things like, as I mentioned, things like support or or customer success.
• 20:33
  SPEAKER_01: But I think some of those other functions, if a partner can help you accelerate it, you lean with the partners and you see those companies grow really fast.
• 20:40
  SPEAKER_01: If um, if you can't find the right partner, you find a bit of the, you know, that chasm around how do I build the capabilities, how do I bring in the right people to do it.
• 20:48
  SPEAKER_02: Yeah.
• 20:48
  SPEAKER_02: So yeah, one area we're seeing a lot of interest in that where we're helping organizations is software development lifecycle.
• 20:54
  SPEAKER_02: Where can they insert coding assistance and where can they uh bring in AI to help everything from requirements and and uh user stories to everything through documentation, coding assistance, and so on?
• 21:07
  SPEAKER_02: So that seems to be a pretty big area of opportunity, but also the customer facing call deflection, uh self-service, support bots, those types of things.
• 21:16
  SPEAKER_02: We find that the biggest gap there is data and content.
• 21:20
  SPEAKER_02: Are you is that something that's surfacing uh for your companies that you're dealing with, or is that kind of subsumed into other operational uh yeah, it's um uh, you know, it it's one of the things that we go through, like our own internal transformation, you're completely right.
• 21:35
  SPEAKER_01: Like it all starts with having the right data in the right places to manage.
• 21:39
  SPEAKER_01: For most of our clients on the diligent side, they already have their data in diligent systems.
• 21:44
  SPEAKER_03: Okay.
• 21:45
  SPEAKER_01: And so the ability to take that and then transform it and make it more accessible, more productive, continuously monitor it, add agents on top of it is just is massive.
• 21:54
  SPEAKER_01: And so for our clients, they're already part of the way down the journey because they have that information in the right system.
• 22:00
  SPEAKER_01: Now do you do do you require manual little checks, people confirm, you know, people uh managing a workflow, or do you have agents managing that workflow?
• 22:07
  SPEAKER_02: So are you managing uh knowledge bases and those types of things or support?
• 22:11
  SPEAKER_02: Yes, interesting.
• 22:12
  SPEAKER_02: Oh, so that's a big part of that whole process is ingesting uh those assets.
• 22:17
  SPEAKER_01: And the data, once you have the data, you have it structured and you have the workflows around it.
• 22:20
  SPEAKER_01: One of the things that for governance, risk, and compliance, especially areas of risk, compliance, audit, there are workflows that are relatively standard that just need to be added agents to automate.
• 22:30
  SPEAKER_01: Data's in the right place.
• 22:31
  SPEAKER_01: In some cases, data is always messy at some level with different clients.
• 22:34
  SPEAKER_01: But when most clients have their data already in diligent, then it's really easy for us to help to add agents and automate.
• 22:40
  SPEAKER_02: That's great.
• 22:41
  SPEAKER_02: That's really it sounds like a really you know complete holistic solution.
• 22:45
  SPEAKER_01: And and for for our clients, that's why it has been a huge unlock in value for them.
• 22:50
  SPEAKER_01: Because you say if the data is sitting in there, how do I drive the right automation?
• 22:54
  SPEAKER_01: How do I not just manage it from point A to point B, but how do I take it through as full, useful life?
• 22:59
  SPEAKER_01: And now you can do that as it starts within our systems, but may need to leave our systems and go to other places to solve problems for a client.
• 23:06
  SPEAKER_01: Right.
• 23:06
  SPEAKER_02: Do you what do you do you have an opinion about companies like Glean?
• 23:10
  SPEAKER_02: We've seen some organizations deploy them, get some good results, but there's a little bit of opaqueness to some of their uh things like ontologies and knowledge graphs, and plus their their kind of walled garden.
• 23:23
  SPEAKER_02: You know, you have to really be in their environment.
• 23:25
  SPEAKER_02: Do you have an opinion about those kinds of companies?
• 23:27
  SPEAKER_01: We uh uh we are a client.
• 23:28
  SPEAKER_01: Um we use Glean to help depower um our internal um diligent GPT and our tools.
• 23:35
  SPEAKER_01: And we have found that it's very helpful for kind of some of the initial work we've done.
• 23:40
  SPEAKER_01: But then our team internally has built agents on top of it to take much further along than some of current capabilities.
• 23:48
  SPEAKER_01: You know, it's interesting because we um the same conversation we have with our clients, we also have with our partners and suppliers.
• 23:53
  SPEAKER_01: And in many cases, the conversations that we will have with, you know, with folks at Glean is here's what we're looking to do.
• 23:59
  SPEAKER_01: If you can deliver that capability, you know, that's great.
• 24:03
  SPEAKER_01: If you can't, then we'll help to take and add our own capabilities on top.
• 24:06
  SPEAKER_01: And for some of our more forward-thinking clients, we'll have that discussion with them as well around diligence capabilities as well.
• 24:13
  SPEAKER_01: And I always love to spend the direct time with clients and understand what is your roadmap.
• 24:17
  SPEAKER_01: And if you have a capability that you want to build on top of it, we'd we'd be glad to do it for you because if it works for you, it likely works for other clients.
• 24:24
  SPEAKER_01: And most of our clients are very much in the mode of saying, yeah, if you can do this for us in a way where you can manage it at scale, so we don't have to do it on our own.
• 24:32
  SPEAKER_01: We're happy to have diligent do it as long as the price-to-value equation works for me doing it ourselves.
• 24:37
  SPEAKER_01: And I think just from a glean perspective, I think our team has built a ton on top of and waiting for kind of capabilities.
• 24:44
  SPEAKER_01: And like I said, kind of us being adopters makes me also realize what you know I want in a partner if I'm one of Diligent's customers using our product help to drive.
• 24:53
  SPEAKER_01: And I think that there is a lot of innovation given how easy it is to add capabilities today, kind of with tools, et cetera, vibe coding, et cetera, on top of vendor stacks.
• 25:02
  SPEAKER_01: The question is how quickly will vendors actually deliver and actually deliver on those agents for you so you won't have to build them on top of the stacks.
• 25:08
  SPEAKER_01: Right.
• 25:09
  SPEAKER_01: And wherever we can learn from our early adopters, we we do so.
• 25:13
  SPEAKER_02: And so interesting.
• 25:14
  SPEAKER_02: There's uh, you know, there's aspirational functionality, I like to call it.
• 25:18
  SPEAKER_02: Right.
• 25:19
  SPEAKER_02: It's something that you you're planning, it's in your roadmap, but then the question is what you know, what's the gap between you know where you are today and what that aspiration is.
• 25:25
  SPEAKER_01: And part of our role too, and we've done this for a lot of our clients, um, like, you know, there will be an AI board member in the future.
• 25:32
  SPEAKER_01: Sure.
• 25:33
  SPEAKER_01: So what does that look like?
• 25:34
  SPEAKER_01: How does that function?
• 25:35
  SPEAKER_01: And how do we have that dialogue with our clients around how do we power some of those capabilities?
• 25:40
  SPEAKER_01: And I think I think staying ahead and with you know your most innovative clients helps challenge you to make sure you say, you know, where where do the early adopters want to push us and how do we deliver those capabilities for them?
• 25:53
  SPEAKER_01: If we can be fortunate enough to work with the people who are truly pushing the edges of innovation, it just makes us better and helps us up our game.
• 26:00
  SPEAKER_02: Absolutely.
• 26:00
  SPEAKER_02: Absolutely.
• 26:01
  SPEAKER_02: Shift gears a little bit.
• 26:02
  SPEAKER_02: You and I talked about how AI is kind of transforming the labor market, the job market.
• 26:08
  SPEAKER_02: I was uh talking about how you know entry-level jobs are disappearing because they're being handled by AI.
• 26:14
  SPEAKER_02: And then you had a very interesting perspective on this where you talked about AI native employees, new hires, interns, people coming out of university or even not even going to university, but coming in with a new set of skills.
• 26:26
  SPEAKER_02: Talk a little bit about how you see that evolving because a lot of organizations are kind of thinking, well, you know, we can automate these jobs, but then where do the future senior uh leaders come from, right?
• 26:38
  SPEAKER_02: Uh, how do they come up through the ranks?
• 26:39
  SPEAKER_02: But you had a very interesting perspective on that.
• 26:41
  SPEAKER_01: You want to Yeah, I would um I would disagree with the narrative that says there are not going to be roles for recent college grads.
• 26:50
  SPEAKER_01: Um, in a very, I mean, when you think about it, um, I need team members who are willing to be all in on AI, adopt all the latest tools, and make sure that they are 10x employees, 10x team members.
• 27:03
  SPEAKER_01: And the reality is I'm gonna create every opportunity I can for my current team to become 10x team members.
• 27:09
  SPEAKER_01: But if someone isn't intellectually curious, if someone doesn't want to learn that X set of tools or capabilities, I will, and I think most other organizations will give them a period of time, but at some period of time, you know, you don't wait.
• 27:20
  SPEAKER_01: And when I look at new employees coming in, and there are you know new, you can characterize new as there are many kinds of new, but people come in with knowledge of and using all the most modern tools and already function and role that is five to 10x, um what um what another team member will do.
• 27:38
  SPEAKER_01: I think there are tons and tons of opportunities for those individuals to come in.
• 27:42
  SPEAKER_01: And so my advice to a early stage um, you know, um potential team member employee, same thing I would give to a late tenured um team member, which is you gotta be functioning with all the newest set of tools.
• 27:55
  SPEAKER_01: You need to be intellectually curious, you need to build your capabilities because that's how you're gonna scale your career.
• 28:00
  SPEAKER_01: And I think there are some people who are hungry and eager and already using those tools who can deliver that value and maybe faster than the people who don't want to change.
• 28:07
  SPEAKER_02: Yeah, and then there's a group of people who are overusing the tools, right?
• 28:12
  SPEAKER_02: I don't know if you've experienced that, but we've had, you know, we use contractors sometimes, and sometimes a contractor will come in and they'll they'll produce outputs without synthesis or without their true creativity and so on.
• 28:24
  SPEAKER_02: Are you seeing that happening in organizations?
• 28:27
  SPEAKER_01: Less so across our clients.
• 28:28
  SPEAKER_01: I would say most of those individuals are well, I would say less so across our clients in general.
• 28:34
  SPEAKER_01: There are people at the margin who are trying to create everything themselves.
• 28:38
  SPEAKER_01: And while I think the new tools and capabilities give you the ability to do that, I think just defining and aligning on what's the strategy and how you should more is just more by definition.
• 28:50
  SPEAKER_01: And so I think more of the right is what matters the most.
• 28:53
  SPEAKER_01: And I think, and I think we try to help our clients and filter to where we can create the right stuff that has the right impact.
• 28:59
  SPEAKER_02: Right, right, right.
• 29:00
  SPEAKER_02: So um let's see, we talked about the changing workforce.
• 29:04
  SPEAKER_02: What else do you see as kind of the so you talked a lot about you know the the fact that organizations there's a gulf between having a vision and being able to execute?
• 29:14
  SPEAKER_02: Where are the gaps in terms of what you're able to do for an organization where they need to kind of go out?
• 29:20
  SPEAKER_02: So, where does the the the enablement that you provide leave off and where the customer really has to either find a partner or or or build the capability or how far can you take them versus how far they have to go?
• 29:32
  SPEAKER_02: I guess is the question.
• 29:33
  SPEAKER_01: Yeah, it's a great question.
• 29:34
  SPEAKER_01: Uh um uh so we offer, like I said, uh AI-infused, AI-wired software and agents to our clients.
• 29:42
  SPEAKER_01: And it's it's a really interesting evolution that's going on just across the software industry in general, where you know, in the past it required, you know, a partner to do a bunch of arms and legs work to piece things together to make it easier for your software to work.
• 29:59
  SPEAKER_01: With AI, that is um uh decreasing materially for a lot of use cases.
• 30:06
  SPEAKER_01: And by that I mean you can just get up and running much faster.
• 30:09
  SPEAKER_01: We can use agents to go and collect and pull and tag your data and go access different systems to pull that directly.
• 30:14
  SPEAKER_01: There will always be some of that, and we lean on partners to help to do that, but way, way, way less of that um today than there was in the past, and there'll be way less, way less of that in the future.
• 30:24
  SPEAKER_01: And I think that's just the way software is heading.
• 30:27
  SPEAKER_01: People expect things to just work, and agents will help to enable that for clients sooner.
• 30:31
  SPEAKER_01: And so there will always be a need to help to partner and help organizations cross the chasm.
• 30:36
  SPEAKER_01: I think for what we do, which are specific, you know, departmental or functional tools, we already have the context and know what your organization is likely trying to do.
• 30:46
  SPEAKER_01: You will educate us a bit, but then you can turn us loose and we'll help to drive the change and the outcomes and the impact you expect.
• 30:52
  SPEAKER_02: Interesting.
• 30:52
  SPEAKER_02: Yeah.
• 30:53
  SPEAKER_02: So one of the things that we're seeing, and you mentioned agents a number of times, organizations are trying to take that next level of building agentic capabilities.
• 31:01
  SPEAKER_02: And we're certainly helping organizations do that as well.
• 31:04
  SPEAKER_02: But how do how do you see that impacting compliance and risk management?
• 31:08
  SPEAKER_02: Because now you're introducing things that can kind of operate somewhat autonomously.
• 31:13
  SPEAKER_02: We still have to have the right guardrails, we still have to understand the process.
• 31:17
  SPEAKER_02: I like to say you can't automate what you don't understand.
• 31:19
  SPEAKER_02: So, how does it tell me how that agenc landscape or emerging agentic landscape is impacting?
• 31:25
  SPEAKER_01: Yeah, it's it's a great question.
• 31:26
  SPEAKER_01: Um, uh a couple things.
• 31:28
  SPEAKER_01: So you've you've highlighted this before, but yeah, you need the right data.
• 31:31
  SPEAKER_01: Yeah, you don't have the data, right data, and you don't right know where the right data is, like you can't drive the progress you expect.
• 31:37
  SPEAKER_01: For many of our clients, it's already in our system, so it makes it easy to do that.
• 31:41
  SPEAKER_01: And you have to have the right process.
• 31:42
  SPEAKER_01: You can't automate something if you don't know what the process ultimately ends up in.
• 31:45
  SPEAKER_01: So you need both those things.
• 31:47
  SPEAKER_01: Those are just foundational, found, foundational components to get started.
• 31:50
  SPEAKER_01: Now, beyond that, it's interesting.
• 31:51
  SPEAKER_01: Uh, most of our clients, and we're having this debate um uh last week across Steam, most of our clients um are not asking for agents.
• 31:58
  SPEAKER_01: No, most of our clients are not saying they're asking for capabilities and they're asking for outcomes.
• 32:02
  SPEAKER_01: And so I think that there is a whole view of you know what technology helps you deliver those outcomes.
• 32:08
  SPEAKER_01: But for most of our clients, they don't they don't care if I ever said the word agent or not.
• 32:12
  SPEAKER_01: They just care about an outcome.
• 32:14
  SPEAKER_01: I spend, as you mentioned, you know, about 10 years of my career at McKinsey and Company.
• 32:19
  SPEAKER_01: And I like to, I like to liken agents to like that really smart associate.
• 32:24
  SPEAKER_01: And you can you have the analogy in any in any team or any work environment, but it is the person who does the job you ask them for, but also knows what the next step likely is and asks you if you would like to do that as well.
• 32:38
  SPEAKER_01: What is that next step?
• 32:40
  SPEAKER_01: And that and over time, you trust that you don't need them to check in with you multiple times a day.
• 32:47
  SPEAKER_01: Maybe they check in with you at the end of every day or each morning.
• 32:51
  SPEAKER_01: And then maybe you say that that person is so good on their own, they know what the next step is.
• 32:56
  SPEAKER_01: They do the in a contextually aware environment, they know what decisions we've made historically as an organization, and so they know what to replicate.
• 33:03
  SPEAKER_01: Now I'm doing it weekly, or now they're sending me reports, etc.
• 33:07
  SPEAKER_01: So I think that's the right way to think about it.
• 33:08
  SPEAKER_01: Now, there is the notion of how do I make sure, like it's not things running around doing everything through the initial checking, you're ultimately training that agent.
• 33:18
  SPEAKER_01: So one of the um uh something I read on online that really resonated, which says you actually have to think about training an agent for the same level of training a team member or employee.
• 33:28
  SPEAKER_01: Yeah, exactly.
• 33:29
  SPEAKER_01: And so if the time frame getting someone up and running for their job was going to be a month, you should expect some level of of that before your agents as well.
• 33:38
  SPEAKER_01: We can help because most of the activities are pretty standard workflow.
• 33:41
  SPEAKER_01: So once you kind of do that, you have the right hard rails for it.
• 33:44
  SPEAKER_01: But to the extent that there is variance in what you might want that individual to do or that agent to do, it's gonna come from teaching.
• 33:51
  SPEAKER_01: And so back to your thing around, I think people will and are making sure that they check in with the agent.
• 33:56
  SPEAKER_01: The agent prompts them more frequently as it gets up and running.
• 33:59
  SPEAKER_01: But once you're comfortable with it, you can just let it go and update you later.
• 34:03
  SPEAKER_01: Now, what we make sure that we can do is have the right governance and have the right audit trails around it.
• 34:07
  unknown: Right.
• 34:07
  SPEAKER_01: Because on anything that is risk compliance audit or governance related, you may be okay with that agent making 10 decisions once you get comfortable with it.
• 34:16
  SPEAKER_01: But you're gonna want to go back and someone's gonna say, wait, wait, wait, how did we get to this endpoint?
• 34:21
  SPEAKER_01: Show me that we checked all these things along the way, and you're gonna need to pull string and show out here's all the decision that went on along the way.
• 34:28
  SPEAKER_01: And I and that is just that's just the nature of the way enterprise systems powered by agents are gonna be done.
• 34:34
  SPEAKER_01: And it is incredibly true in areas like risk, compliance, governance, and all it's like.
• 34:38
  SPEAKER_02: Those audit trails and that traceability is going to be paramount to this.
• 34:42
  SPEAKER_02: And I really like the way you're thinking about this is you know, it's a it's a trusted colleague.
• 34:47
  SPEAKER_02: I treat my clawed uh projects that way, right?
• 34:50
  SPEAKER_02: I upload lots of content to my past articles, and my thought leadership, and webinars, and podcasts, and client meetings and all of that.
• 34:58
  SPEAKER_02: And I ask it questions, and it does astound me every day.
• 35:01
  SPEAKER_02: You know, I give it really hard problems to solve, and I'm and I'm always blown away, and and the value is just astounding.
• 35:08
  SPEAKER_02: But I but I do think of it that way.
• 35:09
  SPEAKER_02: I think of it as you know, here's an entity that I'm asking questions of that understands the context, understands this world, and has the ability to make some of those decisions.
• 35:20
  SPEAKER_02: It's I'm mostly doing it to produce deliverables and things like that, but or to derive new IP or to do evaluations such as our you know, our 74 question uh uh uh survey.
• 35:31
  SPEAKER_02: That's a lot of that is automated, right?
• 35:32
  SPEAKER_02: A lot of that is, you know, you can gather the the uh the the information, the inputs, and then the agent basically goes off and and uh fills that in and produces the scores and and the and the outcomes and the expectations.
• 35:45
  SPEAKER_02: I I like also the fact that you are are emphasizing the fact that you need to understand the process, right?
• 35:50
  SPEAKER_02: I used to say you can't automate a mess, but you can automate a mess, you can have an automated mess, but you can't automate what you don't understand.
• 35:56
  SPEAKER_02: So I think that's really critical.
• 35:57
  SPEAKER_01: And then someone mentioned something that really, really resonated with me as well.
• 36:01
  SPEAKER_01: They're talking about, you know, how does this world unfold?
• 36:04
  SPEAKER_01: Like with what will what will Claude do?
• 36:06
  SPEAKER_01: What will OpenAI do?
• 36:07
  SPEAKER_01: And all those different dynamics.
• 36:09
  SPEAKER_01: And they're talking within the context of of domain specific or vertical vertical specific or niche specific um uh current technology providers.
• 36:19
  SPEAKER_01: Like what ends up getting commoditized versus what ends up being its own separate um function.
• 36:25
  SPEAKER_01: And and um uh and the notion of context is incredibly important.
• 36:30
  SPEAKER_01: I think that's what differentiates the way you think about operating.
• 36:34
  SPEAKER_01: If you can work with a partner who already knows your context and they're up and running much faster, like that's huge.
• 36:41
  SPEAKER_01: If for work that doesn't require a ton of context, and then you can offer more generic solutions.
• 36:47
  SPEAKER_01: But context is ultimately how your agents will make the decisions within knowing either a business function, process, environment, regulatory framework that matters.
• 36:57
  SPEAKER_01: And if that context is more nuanced, then you know you'll see your current partners, if they can up their game, thrive for you.
• 37:04
  SPEAKER_01: But if it doesn't and that it matters less, then I think that you'll have general purpose LLMs that will serve those incredibly quickly.
• 37:11
  SPEAKER_01: And you'll always offer more context to those, they'll get better, but you can offer the most relevant solution to you that gets you to your outcome fastest.
• 37:18
  SPEAKER_02: Yeah, yeah, that's great.
• 37:19
  SPEAKER_02: And I think that makes a lot of sense.
• 37:21
  SPEAKER_02: And again, it it's it's astounding how powerful these things are.
• 37:24
  SPEAKER_02: You give I give it several different spreadsheets and and uh interview findings and and uh statements of work and meeting transcripts and all these things.
• 37:34
  SPEAKER_01: I mean, I I I worry like, you know, um, you know, we have healthy debates internally.
• 37:38
  SPEAKER_01: One of the departments we sell into is legal, you know, we talk all these different departments, and it's really, really interesting to see just how good the LLMs have gotten at like take legal use cases in specific.
• 37:50
  SPEAKER_01: And so if you're going to be a software company that delivers or offers things into legal as an apartment, what level of functionality are you going to put on top of that?
• 38:02
  SPEAKER_01: And I think that's an area that is big and generic enough where like that's a really good question because every seven months, elephants have another big breakthrough.
• 38:11
  SPEAKER_03: Exactly.
• 38:11
  SPEAKER_01: When does that continue or whatever?
• 38:13
  SPEAKER_01: Like, you know, I just I how you offer that value to your clients, how can you can offer more context to their unique needs to offer that unique value?
• 38:20
  SPEAKER_01: I think in some categories it's it's easy.
• 38:22
  SPEAKER_01: I think some categories it's gonna be much tougher.
• 38:25
  SPEAKER_02: So with that, let's let's kind of wrap up with your thoughts about um where you see the industry going, where you see diligent going.
• 38:32
  SPEAKER_02: What are your what's on the horizon?
• 38:33
  SPEAKER_02: How do you see things kind of evolving in the next couple of years?
• 38:36
  SPEAKER_02: I mean, obviously uh a year's a long time in in a in our world.
• 38:39
  SPEAKER_01: Yeah, it's um uh I mean there's so much change going on in the world that these are like conversations that we have all the time, kind of with our clients, with our team, with our you know, investors and board.
• 38:49
  SPEAKER_01: Um, you know, I will start with saying there's never been a more exciting time in my career to be building product.
• 38:56
  SPEAKER_01: Yeah.
• 38:56
  SPEAKER_01: Like AI offers just so many incredible opportunities.
• 38:59
  SPEAKER_01: So I think it's gonna be transformative.
• 39:00
  SPEAKER_01: And I think the organizations who transform their organizations around AI and deliver those capabilities to clients are gonna do unbelievably well.
• 39:08
  SPEAKER_01: But it'll be massive transformation or shift.
• 39:11
  SPEAKER_01: You're gonna say some companies who don't who don't make it and don't transform and don't make it to the next level.
• 39:16
  SPEAKER_01: And I think we are in both an exciting time and a scary time for this.
• 39:20
  SPEAKER_01: And I think it's really uh I think it's awesome.
• 39:22
  SPEAKER_01: We're growing faster um um uh than we than we have in the last many years.
• 39:28
  SPEAKER_01: We're seeing massively accelerating growth.
• 39:31
  SPEAKER_01: Clients are looking for, you know, um partners who can help deliver outcomes for them.
• 39:35
  SPEAKER_01: And I think you'll see that for a lot of organizations.
• 39:38
  SPEAKER_01: You can see volatility in the stock market as they look to see who the next winners are.
• 39:42
  SPEAKER_01: Um I think the winners are emerging.
• 39:44
  SPEAKER_01: You just have to look hard to find them.
• 39:46
  SPEAKER_01: And I think we find ourselves in a really, really exciting time and place to uh to win in a really big way.
• 39:51
  SPEAKER_02: Agree, agree.
• 39:52
  SPEAKER_02: That's wonderful.
• 39:53
  SPEAKER_02: Well, thank you for your time and and your insights.
• 39:56
  SPEAKER_02: This has been a fantastic conversation.
• 39:58
  SPEAKER_02: I've really enjoyed it and uh look forward to maybe happening having you on uh in the future.
• 40:02
  SPEAKER_01: Great.
• 40:03
  SPEAKER_01: Thanks that thanks, Tess.
• 40:04
  SPEAKER_01: Uh, really appreciate the time.
• 40:05
  SPEAKER_01: A fun, fun discussion.
• 40:06
  SPEAKER_02: Absolutely.
• 40:07
  SPEAKER_02: And where can people find you?
• 40:08
  SPEAKER_01: People can find me at uh uh at diligent.com in New York City on LinkedIn or on X.
• 40:15
  SPEAKER_02: Okay, wonderful.
• 40:16
  SPEAKER_02: So those will be in the show notes as well.
• 40:18
  SPEAKER_02: And I want to thank our audience uh for uh their time, and we'll see you next time at the next uh Early AI podcast.
• 40:24
  SPEAKER_02: Thanks, Beth.
• 40:27
  SPEAKER_00: Thank you for joining us on another deep dive into AI innovation.
• 40:31
  SPEAKER_00: Tune in next time when we introduce another industry expert and discuss how to maximize AI in your world.
• 40:37
  SPEAKER_00: The Early AI Podcast is sponsored by Early Information Science and Vector.
• 40:42
  SPEAKER_00: To learn more, visit early.com at earl e y dot com.
• 40:48
  SPEAKER_00: Thank you for tuning in.