Pod Insights Eye On A.I. The Single Biggest Barrier to AI Adoption Isn't the Technology — It's This | Errol Gardner of EY About this episode Errol Gardner has spent 35 years advising the world's largest organizations through major technology transitions, and his assessment of where enterprise agentic AI actually stands is one of the most grounded you'll hear anywhere. His number: less than 1 out of 10 on a maturity scale. Not because the technology isn't ready, but because deploying agentic AI across an organization doesn't tweak how it works, it requires rebuilding how it works. And that is a fundamentally different kind of challenge than anything the AI hype cycle is currently acknowledging.
In this conversation with Craig Smith, Gardner walks through why cloud adoption still hasn't reached 7 out of 10, what that means for agentic AI timelines, why the single biggest barrier to adoption is human resistance rather than technical limitation, and why governments will ultimately have to step in to manage workforce displacement at scale. He also raises a question that almost nobody is asking: is the value exchange between the technology sector and traditional industries sustainable in the long run? It's a conversation that doesn't just describe where AI is, it explains why the gap between the narrative and the reality has never been wider.
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Transcript Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.
0:00 Craig S. Smith? Most organizations have embraced the cloud and have moved most of what's movable to the cloud. It seems like it's sort of morphing into a new industry.
0:11 Speaker 01 The single biggest impediment for any organization changing is usually something related to the human beings. It could be the leaders, it could be the sponsors, it could be middle managers, it could be the workers, it could be a whole, it could be a combination of. There's huge anxiety in the workforce about whether AI effectively is going to displace their job.
0:33 Craig S. Smith? Okay, well, I'm interested in talking because I speak quite a bit to one of the other big consulting firms. I actually do some writing for them. And so I have a good sense of what, how they view this world, the new AI and particularly agentic world. And I thought this would be an opportunity to hear from you guys, how you see the corporate landscape, the penetration of AI in production in large corporations and in particular
1:18 Craig S. Smith? agentic systems. Because the, you know, I, I end up having a lot of startups on the podcast and they're all selling systems and they all say, oh, it's, you know, everyone's using our system. But, uh, you know, when you get beyond an agent, you know, watching your email inbox, it gets more complicated and I'm, I just, that's what I'm interested in. So, uh, usually I have the guests start by introducing themselves, giving a little
1:56 Craig S. Smith? bit of their background insofar as it's relevant, uh, for either consulting or AI. And then maybe you can start by talking about EY's.
2:13 Craig S. Smith? View or thesis on what's happening with AI in the workforce or in the enterprise, I should say.
2:23 Speaker 01 Well, thank you for having me. It's great to be speaking to you about this, arguably the hottest topic in most corporate environments, government environments and many other organizations. So my name is Errol Gardner. I lead our consulting business here at EY globally. I've been doing that for about six years. I've been in this industry for over 35 years. So I've seen a number of different technology trends during that time. And probably can look at AI in the context of many things that have been historically spoken about as changing the world very rapidly and then maybe give some context on that.
3:06 Speaker 01 But look forward to talking to you about all these different topics. And maybe to start in terms of how I see AI currently within the corporate environment and what businesses are doing and how they're responding to that.
3:24 Speaker 01 I think the first thing, maybe just to highlight, is actually the reality that change within large organizations is very difficult to execute. So anybody who references or pretends that to be otherwise, I think is either has never done it before or potentially maybe being slightly economical with what is achievable. And there are lots of very good and positive reasons for that. Organizations exist and those that are big and at scale generally have been around for quite some time.
4:05 Speaker 01 And they've got, you know, various mechanisms, barriers, arguably enablers that have made them successful, but also sometimes can act as barriers to them achieving change quickly.
4:21 Speaker 01 That can be lots of structures organizationally that get put in place, management structures, management systems. It can be people that work in the organizations. It can be leaders of a certain generation mindset, work style, which doesn't necessarily align itself to new technologies and driving innovation and creativity. It could be a regulatory environment. There's a whole button and a number of other factors that that can very much come in the way of that. So I think fundamentally what we're seeing in the market at the moment, I think is a lot of
5:02 Speaker 01 talking up about the benefits that AI will bring to the corporate sector, what that looks like, and what that could be, both productivity wise, efficiency wise, customer experience, driving value in different paradigms. The route to achieve that, though, has to go through all of those other elements that I've just spoken spoken to and about. So I think you'll find the progress that's happening currently, as we're seeing with our clients, is is very good in terms of people adopting employees embracing AI, lots of development programs in terms of those with their technology skills, as well as those that don't have
5:47 Speaker 01 technology skills, understanding the art of the possible. How you then translate that into building capabilities that genuinely scale, be it across a whole value chain, even across a full business process, let alone then across GOs, across different services and functions. We're still quite a way away from that. And when I say quite a while, I don't mean years and years. I just mean it's not happening like yesterday in the way that a lot of people are talking about in my humble opinion.
6:25 Craig S. Smith? Yeah. And you're talking about AI broadly or about agentic AI?
6:31 Speaker 01 Oh, of course, I I mean more in relation now to agentic AI. So that's a very good, good qualification, actually. So, I mean, obviously, AI actually has been around for quite some time. So and different variants, and I know from from your own experience and talking with many others, you you you know about those different elements. So I think, but the if you kind of talk about the slightly more modern versions of it, I think machine learning is used at scale in a number of different organizations across their processes and and is driving efficiency and is well embedded in many different industries and and processes across the board.
7:15 Speaker 01 If you think about gen AI, if you like, the the kind of, I guess, we were probably starting three years ago with the deployment of models, L L Ms and things of that nature. So effectively just capturing information and and processing it as fast as possible and converting it into texts, responses that effectively a human would would would put into place. I think that is being used quite extensively in a number of organizations for that purpose. So as a way of be it using information that sits outside the organization
7:57 Speaker 01 and doing analytics around that, depending on the nature of the process, if you're doing research that's clearly widely available on the internet and using all the tools that can enable that. But then similarly, creating private L L Ms that would stay within the firewall of the organization, leveraging the data, knowledge and insight within the organization itself to deliver a secure and protected way of protecting the corporate information within the four walls of the organization and using that as well. So I think that is used, again, increasingly across business.
8:38 Speaker 01 But that's probably, again, not as pervasive as some may may think that to be.
8:45 Speaker 01 And then the the element I was speaking to obviously is everybody is now talking about Agentic and probably have been for the last 12 months or so. I think that's the piece that arguably is genuinely transformational and impactful, were it to be able to deliver.
9:06 Speaker 01 But I think when you start looking then at agents replacing activity and activities that join up into a workflow, that join up into a process that are part of a value chain, that's the piece I think that is, there's a lot of work because that is genuinely transforming an organization, that is genuinely not even just tweaking how they do things. You're essentially saying you have to rebuild how an organization works and operates. The the challenge of doing that at scale is is is one that's ahead of us, not one that's behind us.
9:46 Craig S. Smith? Yeah, and I have a few questions, both on the Gen AI and Agentic side. Is that being, is the adoption being driven or the or the experimentation with regards to Agentic being driven from the bottom up of, you know, employees who are using AI, commercial AI agents to to track their emails or or, you know, fill out forms or something like that? Or is it being because of security concerns and that sort of thing? Is it really being driven from the top
10:28 Craig S. Smith? down, which I imagine would be a much slower process?
10:34 Speaker 01 Well, I think you could argue that that both of those and other models are out there, and I think everybody's learning on this journey. So. I mean, obviously, as I mentioned earlier, with large corporates, they have checks and balances in place that take things like data privacy, obviously their own corporate data, but also their customer data, their employee data and various other things. So they, they would have put mechanisms in place to make sure that information doesn't get out into L L M's in the broader world. So the challenge with that, of course, then, is how do you control the employees that
11:15 Speaker 01 sit within an organisation from leveraging tools that they may be more comfortable using in their private lives and moving corporate data into those tools in order to, oh, if only I could use it to, to do this bit of analysis or understand what the quick answer to is to this particular problem.
11:38 Speaker 01 So that is a real and genuine issue. I think that a number of organisations have to grapple with in terms of where the top down, bottom up meets. So if you have a workforce that is well versed in the usage of, of gen AI tools, if you like, how do you control them not misusing data within an organisation and putting it a little bit out there or in the public domain? Because as you know, all these L L M's that sit more broadly on the internet are training models and using that data then and propagating that in a way that is not controllable from outside of the organisation.
12:22 Speaker 01 So I think, I think increasingly you will now find most major, or I would argue all major organisations now will put guardrails to prevent that from happening and will monitor usage by employees of any movement of data from their work laptops to platforms, environments that, that are not controlled in that respect. And some therefore may see if you're more of the innovative, creative side as an employee, you would may see that as constraining your ability to innovate. So if you're using then the house tools and the house L L M to all the and and the curated
13:05 Speaker 01 private corporate L L M that is used by the organization, that you may not be, it may not be your favorite tool of choice. It might not be the one that you're used to using and you might not like the constraints. And and so that can become an issue. So I I think you have no doubt both that adoption at, if you like, bottom up at the employee level, driving innovation, testing their own creativity and the boundaries of what they'd like to do, but probably with guardrails they're not so comfortable with. And then, as I say, from a top down perspective, I think most organizations are encouraging
13:46 Speaker 01 their employees to embrace A I and become A I literate and do more L and D around this and understand how to use it. Because I think people understand the benefits of employees being comfortable with it and enhancing their own personal productivity. But as I say, they'll do it with guardrails, which creates that that at some at some levels, some of that disconnect in the eyes of the employees in terms of, well, what you're asking me to do one thing and then you you're putting constraints on my ability to do it.
14:23 Craig S. Smith? Yeah. Is this changing consulting? I mean, do you do you guys build, for example, as well as advise?
14:35 Speaker 01 Yes, absolutely. So.
14:39 Speaker 01 But to answer your, I mean, your first question, it is changing consulting and I'm sure it will continue to change consulting. And I mean, the, the whole essence of the consulting industry, as you know, is essentially change. That is our, you know, primary function and objective is to help organizations change. So by definition, we're a business, we're an industry that also has had to evolve and change with every, you know, macro as well as in some cases, micro change that happens in the working world. And so us changing is
15:24 Speaker 01 not particularly unusual in that respect. We've been through cycles with, you know, a lot of workloads move significantly offshore. So you, you know, you have huge practices now that sit in, in India and very other, various other parts of the world, which 30 years ago didn't happen. You've got the rise of in-house consulting operations within corporates that we've had to change and react to. So there's a number of things that, that over time, we've had to react to. And this is just the latest, which, which says, probably I'd crystallize it in two or three different ways. One is, we can't show up to clients
16:06 Speaker 01 and tell them about the benefits of how they could, if they deployed AI, change their business unless we're doing it ourselves. So in the first instance, we have to show in our own business that we're at the front edge of, of deploying AI into what we do, how we operate. And, and, you know, so that's one. Secondly, the way we deliver services to clients, which obviously, interestingly, has also been through quite a significant transformation in the last five, six years. So pre 2020, generally, this was an industry that if the client didn't see you sitting in their offices or their building or premises
16:51 Speaker 01 in some way, shape or form, they didn't believe you were working for them. They thought you were doing something else. And obviously with COVID, we've kind of completely changed that paradigm in terms of people physically being present with a, with a client.
17:07 Speaker 01 But now with AI, you get to a position of, okay, we're moving from a model where we measure consulting primarily by inputs as opposed to outputs. So how many hours have you worked? How many days have you worked? What have you done in order to produce this, deliver all this outcome? You can now say, well, surely used AI for that. So it can't possibly have taken you as long. So what does that look like? So that presents both a challenge and opportunity for us in terms of how we operate, because we can do things faster than we would have done historically. But we can also do more than we would have done historically as well, and therefore
17:52 Speaker 01 achieve more as consequence. So it's completely changing us in terms of how we do service delivery. And then the other critical piece of what I think are, and probably our most fundamental role then is, how do we help other organizations move across that change as fast as possible? And what I'd say is the, the single biggest impediment for any organization changing is usually something related to the human beings. So it could be the leaders, it could be the sponsors, it could be middle managers, it could be the workers, it could be a combination of. So how do we help organizations deploy and embrace the technology?
18:39 Speaker 01 How do you think about and reimagine what the new world could be leveraging the AI, gen AI and/or an agentic workforce? But then how do you get the parts of the organization that need to make that happen bought in and aligned to making it happen?
19:01 Speaker 01 And it may be one for us to talk more broadly about later, but the, as you can imagine, we talk a little bit about the workforce reimagine study that we did. There's huge anxiety in the workforce about whether AI effectively is going to displace their, their role, their job, which is going to lead to resistance in the workplace to the deployment of enterprise-wide and enterprise-grade solutions.
19:32 Craig S. Smith? Yeah, and that's interesting when you say that you in order to to be a credible consultant, you have to, you know, go through the process yourself. Can you talk about that? How EY has adopted both Gen AI and Agentic AI? And well, let's do that first because I have another question about how consulting has changed.
20:04 Speaker 01 Well, we we obviously are an organization that employ a lot of people. So at the broadest sense for EY globally, we're about 400,000 people overall. That's the whole organization. And we very early made the decision to give as many of our employees as possible access to the tools in order to be able to leverage and use Gen AI within our environment. We again, very early built a private L L M and moved a lot of our knowledge and information into that and gave people access to that with the controls that I described so that
20:46 Speaker 01 they could experiment and do things with the information and data that we have within our organization. We also embarked on a huge learning and development exercise around, especially though because we have a lot of people who've got technology skills natively, of course, but we have a number of people that don't have those skill sets. And just encouraging as many people as possible to see AI and especially if you think about it in the Gen AI context, it makes technology as easily accessible as you could possibly think.
21:26 Speaker 01 So to get it to stop thinking about the fact that this is a barrier or I'm not a technologist, I can't do this to actually this is straightforward. It's as easy as using a search engine or something else in that in that context to get some of the information that you need. So we've, we've done a lot of activity around.
21:47 Speaker 01 Giving people the tools and the platform, giving them the learning and development, and then asking them to do experimentation. And then also, I guess, top down is to say which parts of our business can we move fastest in terms of driving, you know, be it the way we do research, the way how we think about engaging with clients from a proposal perspective, for instance, or how we contract and think about consolidating that and making that a much faster process.
22:21 Speaker 01 To then, as I say, building solutions that are how we access knowledge that sits obviously anywhere globally, that we can now bring that into a much more accessible system to any consultant who's sitting anywhere and can bring that to the client as fast as possible. So a number of different elements of what we've done. And then, of course, there's big campaigns in terms of pushing that and encouraging the workforce to embrace that change. And as I say, to to make it clear to our people that we need to show up differently in order to be credible in the marketplace. And that's not just in consulting, it's true of our tax business, it's true of our audit
23:05 Speaker 01 business as well in terms of what we're driving from that market perspective. So those are some of the things that we focused on. As I say, we've probably got about ninety thousand technologists within our business who are part of helping to build and engineer that the more sophisticated solutions around that. And also, we work with the parties, some of our ecosystem partners to drive and enable that as well. But that's the essence of how we've approached moving this forward within the organization.
23:42 Craig S. Smith? Yeah. And what about agentic? Are you experimenting or have you adopted any agentic workflows?
23:51 Speaker 01 Yeah, so I mean, again, that's probably for the last twelve months or so, we've had a lot more focus on that. And so.
24:01 Speaker 01 We've we've got ever increasing number of agents, if you like, that sit within the business. It it initially became a bit of a sport to try and count them, but now it's, you know, we're a big organization across many countries. It becomes a state you can't really count them in that sense anymore. And we look more qualitatively about what we're seeing. So be it, I think you mentioned earlier about in terms of looking at emails about how you think about analyzing information, about updating yourself and on new and information as it comes in on an hourly basis, could be a daily basis, but also deploying agents
24:43 Speaker 01 into tasks from a service delivery perspective, which are quite consistent. So we've seen that a lot in our tax business, that we've been able to do that in terms of producing returns and increasingly in the way that we deliver audits. That's that's a key element. And similarly, in the software development lifecycle, there are a number of efficiencies that were driving from an agentic perspective in that as well. So that's maturing. That's, as I say, we're we're our own corporate organization in that respect in terms of getting that and operating it at scale. But but those are some of the areas that we're we're we're using agents across the business.
25:27 Craig S. Smith? Yeah, I can see this convergence, and maybe it's been going on for a long time. I don't know. But between, I mean, the the consultants are now building systems. There are companies that build systems that in effect are consultants because they'll go to a prospective client, do an audit of their business and say, well, this is where we can automate. You know, this aspect or this workflow. And then you've you've got
26:05 Craig S. Smith? the L L M's themselves, which increasingly have ingested all of the E Y reports, all of the McKinsey reports. And, you know, there's a lot of public facing information about the consulting industry's practices and outcomes.
26:27 Craig S. Smith? And and you can turn to an L L M. Well, I mean, I I spoke to one company about they're calling it decision intelligence and they they're building in effect a C E O co pilot where the C E O would work alongside with this agentic system
26:54 Craig S. Smith? to explore the organization, you know, brainstorm, come up with ideas and and get information so that that they could go prepared to to their management or their board to propose changes. I mean, so do you see that kind of convergence? The that there's, you know, systems that are acting as consultants there. There are startups that are have products, but then have a consulting side to get their products into the enterprise. And then consulting companies that now build products. It just it seems like it's sort of
27:39 Craig S. Smith? morphing into a new industry.
27:43 Speaker 01 Yeah, I think I think there's a lot of
27:48 Speaker 01 what you say, and there's a lot of both discussion about this. There's maybe some. Extrapolation that takes place around this topic. But I think that's part of, to your earlier point about the consulting industry changing. Arguably, the whole ecosystem is changing, both what an organisation, you know, what a corporation does and what the boundaries of that organisation are. What the technology companies are doing, what the boundaries of their organisations are, and what startups are doing, as you say, and what what established service providers or consulting organisations are doing and what they're doing. So I think at the margins, those things may be becoming a little bit more blurred.
28:32 Speaker 01 I'd also say that it's driving us to a point that the solution, if you like, the sweet spot is probably a collaboration model between various actors that I've outlined and others in order to make the most compelling proposition. But I do think, and my kind of personal view around this is there's a lot of talk around product companies becoming service companies and service companies being embedded in software and and all of these types of things. And I think in reality, the the process of change
29:15 Speaker 01 is fundamentally one that is embedded in a service organisation. And how you how you implement technology and apply technology into a business in order to generate a business outcome and business value is something that consulting organisations have many, many years of experience of doing. I don't think we're yet at the stage that you can codify that into a product, unless the product is something that's been arguably bought by an agent and or a non-human.
29:55 Speaker 01 So I think, and as long as we're an organisation and industry that is fundamentally helping and supporting human beings, people in corporations to deliver outcomes for their wider business, they will want to interact with people to do that. And similarly, if they're Workforce is made up of a blend of agents and people. You still have to make sure that the people are not acting as a limiter on the achievement of that overall business. So having and making sure that's the case is critically important. And then if you get to the dystopian world that says, yes, but maybe we'll operate touchless
30:40 Speaker 01 without any people, no humans in the loop. I think people need to deal with, that's a very interesting theoretical model.
30:49 Speaker 01 But tell me how that's going to work in practice. Because I think the reason technology exists is to make, hopefully, the human condition and human life better and corporate life better and enriching us, not in a monetary sense, but in terms of what we can achieve as opposed to in a redundant sense.
31:12 Craig S. Smith? Yeah, yeah. A good point. Of the, on agentic, where do you think we are in the enterprise writ large? Say, on a scale of zero to 10, zero is no agentic AI in the workforce. 10 is sort of maximal agentic use. I don't know what that looks like, but presumably we'll get there. I mean, do you, do you, do you think we're just, you know, at one or two on that scale? Are we closer to five?
31:58 Craig S. Smith? And how quickly do you see that moving?
32:02 Speaker 01 It's a great question that I, I can realize that the way I answer this could, could lead me as a hostage to fortune in many different ways. But I mean, what I would say, if I look at how technology, as I say, has been deployed historically in the, and maybe I'll ask you a question, actually, if I'm allowed to do that. Where would you say cloud is today in the enterprise world on a one to 10 scale?
32:30 Craig S. Smith? Well, not being in the business from, but from what I I hear, I would say it's at seventy and seven on a scale of one to ten, that most organizations insofar as they can, because their regulations and prevent some stuff from moving to the cloud. But most organizations have embraced the cloud and have moved most of what's movable to the cloud. I don't know, is that, is that close from what you see?
33:06 Speaker 01 Well, I don't, I don't, I think it's a very difficult question to answer, but I would say it's less than seventy. So less than seven out of ten. And the reason I say that is not that it maybe seven out of ten organizations have embraced it. But how wide is their usage of it in reality? So you said that most that could be moved to the cloud, whereas what's determining what could be moved? Uh, because I think you'll probably that find that varies by the same, the same industry. Different companies will deter, make a different determination of what could and shouldn't be moved. And the reason I use that as an example is that cloud's been around for fifteen years. And it's taken that long to get to, let's even use your number of seven out of ten.
33:51 Speaker 01 So I mean, what I was going to say, which I think is validated by what you say is we're at less than one. Um, and, and the reality is that we
34:03 Speaker 01 there is so far for us to go to get even to seven out of ten. I'm not saying it'll take fifteen years, but it's going to certainly take longer than fifteen days or even fifteen months. And I think that, um, for all the constraint points that I made earlier, it's, it's much more difficult to do this. You could argue actually that cloud is almost a prerequisite to being able to do it as well. So there's, there's a, a codependency there in terms of making sure that you can do that. I mean, some would argue that's not necessarily the case. But, but I think that we are very, very early in terms of its adoption curve.
34:48 Speaker 01 Again, maybe you have.
34:52 Speaker 01 A relatively large number of organizations, although I'd say that's still probably only 20%, who use it a little bit. I mean, in production, not playing with it. I mean, it's genuinely being used in a production scenario. But it will be at a very, very small element of their overall business.
35:14 Craig S. Smith? Yeah.
35:14 Speaker 01 So I think we, now, that will be my view. And as I say, I'm a hostage to fortune, no doubt, in terms of committing to something so mathematical in, in describing it. But what I'd say to you is that that reflects the huge opportunity that's still ahead for organizations to get the real benefits of deploying this technology and doing it in a safe way, doing it in a responsible way, given the impact it could have potentially on employees, doing it in a way that will generate and create new opportunities for employees in the future to work in a very different way as opposed to purely looking at it from a
35:58 Speaker 01 an efficiency perspective that may end up ultimately be a proxy for saying that we want to reduce our headcount. So I, I think, I think we're early. I genuinely think we're at less than one in that scenario. And I appreciate some of the hyperbole in the market would suggest that we're much further down. But in the enterprise space, I'm speaking to now.
36:20 Craig S. Smith? Yeah.
36:21 Speaker 01 I think we're still very much close to the starting gate.
36:26 Craig S. Smith? Yeah. And are you, from what you've seen of agents, either in experimentation or production at EY, do you think that the hype is going to be borne out? Or do you think, I mean, it could be that they can never, the researchers can never resolve the trust issue, can never resolve the reliability issue? And agents just fall to these, you know, watch in your inbox rather than, you know, critical business processes?
37:05 Speaker 01 Well, I think the, if you think about the barrier of getting from experimentation, innovation to adoption at scale and effectively deploying across workflows, not just single tasks or activity, that is quite a difficult hurdle to overcome. But I think it will, you know, you'll start to see many more organizations achieve that in terms of certain elements of their business and parts of their value chain, for sure. I think, you know, I go back to there are macro factors that are going to challenge,
37:45 Speaker 01 if you like, the train, the AI train that we all speak to and speak about. And so I, we just talked about cloud a little bit, if you like, and just going back to that, maybe just to zoom out a little bit from AI as a topic in its own right. As you know, there are a number of dynamics happening in the world today that are probably acting more as impediments to the fast adoption of AI globally. In compared to, if you think about in 2011, 2012, the globalization train that was assumed
38:30 Speaker 01 to be acting in perpetuity. So if you think about how the world's changed in the last five years and how we are very much more in a space where there's sensitivity around data and information from a nation-state perspective and how much you can rely on critical infrastructure and industries being deployed and delivered from countries outside of the nation that you're sitting in. So sovereignty and directions around that being driven by governments, that's especially
39:13 Speaker 01 the case in Europe increasingly, but I think you're seeing it, well, it's arguably the case, it always has been the case in the US, but you're seeing it in many other countries around the world now who are worried about. We cannot end up being dependent on such a transformative technology without having some level of control in case something goes wrong. So that that would be one. You then have the challenge of the narrative around the displacement of work. That ultimately you say, well, who's going to act as custodian to protect employees from mass redundancy? Is a company going to do that?
39:57 Speaker 01 Are the technology firms going to do that? Or a government's going to have to do that? And I think you'll find ultimately that governments are going to have to lean in to make sure that doesn't happen. Which is going to inevitably be through regulation or peer pressure or taxes or whatever it may be that will disincentivize organizations from displacing people um and replacing them with robots or agents or any other at at scale um in that respect. I think then you've got um the other dimension of this ultimately is is the in many ways, the balance the other way that says
40:42 Speaker 01 the world's moving to a state where our productive workforce and capability is declining. Um. So especially in the Western world, we've got a declining working age population in most major countries. And increasingly, um a burden falling on that working age population to manage the two ends of the spectrum, the babies and the old people um who are nonproductive, if you like, in the in a way that you you understand what I'm saying.
41:13 Craig S. Smith? Yeah.
41:14 Speaker 01 So how quickly can AI deliver the solution to solve for that productive capacity gap without displacing people on mass that you have the problem the other way? I think that is such a macro issue that in many ways you there is no model. There's no platform, there's no empirical evidence of how you can solve for that. But I think a number of governments, um be they transnational or national governments are going to have to.
41:49 Speaker 01 Think about in terms of how do you manage this, which inevitably is going to put the brakes on some of the things and some of the technologies that are out there and the ability of organizations to adopt them quickly. The other one I'd just say to you as well is what's also interesting, of course, is that the the value exchange that's happening at the moment between the technology industry, which is getting a huge amount of value uplift from the AI, if you like, and the AI lift that is is the perception of that. And I don't mean just in
42:30 Speaker 01 stock market terms, but but and I don't it's not about talking about a bubble or in things in that nature, but the transition in many ways of workload and effort moving from traditional industries to technology firms doing things on their behalf. How sustainable is that in the longer term when essentially those companies, those traditional consumer companies, oil and gas companies, financial services and the like, how sustainable is that for those business models going forward? And that's another interesting dynamic that I think we'll need
43:10 Speaker 01 to watch going forward into the future as to how that where's the equity in that relationship going forward? And how do how do you kind of make sure that the technology sector doesn't become so powerful that it's it's controlling so many other sectors and or even replacing them in terms of the services that you see currently offered by other major organizations?
43:38 Craig S. Smith? Yeah, and and I mean, as much as agentic, maybe.
43:45 Craig S. Smith? Within, you know, speaking relatively, in relative terms, maybe far in the future. I mean, that that could simply be years, suppose the decades. But I think that this whole workforce transition is going to have to be addressed by governments. I don't think through regulation of of of hiring and firing practices itself, but maybe through taxation to provide universal basic income to to people who've been laid off.
44:26 Craig S. Smith? But, you know, that that gets very speculative. Today, when you're, two questions. When when customers coming to you, can you break it down just very roughly? How many are coming for traditional consulting?
44:53 Craig S. Smith? Help, I mean, you know, we're moving into this product line. We're transitioning away from that product line. How do we do that? How much of it is AI related generally? And how much of it is, you know, what is a Gentec AI? How can we use it?
45:17 Speaker 01 Well, I think, again, without getting mathematical, I think the vast majority is still
45:24 Speaker 01 solving traditional business problems. So we want to launch a new product. We want to buy an organization to lift our value. We want to get a better penetration to our customers, better customer experience. We want to drive productivity. We want, you know, more efficiency in our supply chain, whatever. All of those things are still driving our business. Probably what's different is the challenges coming increasingly as to, and we need to leverage AI to do that in a much more effective, efficient way. That the sure is the case and and we're seeing increasingly as organizations commit to be it longer term technology projects that are non AI related. So it could be putting
46:09 Speaker 01 in, you know, what are you call the systems of record, changing their ERP platforms. They're increasingly saying, okay, that might be a three year project. Can you do it A faster, but also then deploy AI to do it in a very different way than you would have done it in the past. And they'll kind of build in
46:30 Speaker 01 almost savings expected from future developments in where AI is going in order to achieve that. So I think there's, there's more
46:42 Speaker 01 more of a push to achieve through the traditional things that companies want to drive in terms of delivering business value in the traditional sense of the way you describe it, but to use that as a mechanism to, to lift, to drive, to get the benefits of AI and its usage as quickly as possible. So that, that's probably more the way it's happening as opposed to people coming, clients coming saying, can you give us an AI thing? Or can you agenty fi our business without a context of, well, what are you agenty fiing it for?
47:24 Craig S. Smith? Yeah. Yeah. Do you think that there are in, in most industries now, agentic first startups that, that are hoping to build businesses that, that compete with the majors and whatever industry they're in? Do you think that there will be the growth of new companies in many industries that are not only gen AI native, but agent native and therefore will be faster, cheaper,
48:05 Craig S. Smith? more productive than, than the traditional leaders?
48:11 Speaker 01 I think you, well, the very simple answer to that is yes, no doubt. The however bit that I would say is you kind of need to break that down beyond the generic into, let's say, particular sectors where that's more likely to happen.
48:32 Speaker 01 And, and, you know, maybe even parts of a business that are likely to, parts of the value chain of the business that you could actually, you know, a yesterday's traditional model, maybe you'd outsource that, but tomorrow's is actually somebody comes along and takes it away from you, one of the startups that you're describing. So I think that's it. And obviously Agentic lends itself more to industries which are more focused around processing information and, and where the product
49:11 Speaker 01 is not necessarily a physical product. It's, it's actually, it could be data, it could be digital, it could be a service.
49:22 Speaker 01 So for instance, financial services would be an obvious one in that regard. But then you've obviously got other challenges in industries like that because they're heavily regulated and you can't just kind of jump in and, and start taking over bits of that without
49:39 Speaker 01 a kind of making sure you can adhere to a regulatory framework. So I think you for sure will see it. But the ability to do that at scale, again, both multi, across multiple geographies, but also across multiple companies within a sector is going to be hard for a lot of the startups to, to execute on. Because as I say, again, if you're a startup, you're startup, startups generally in the technology space that are in a B to C world. So if they're operating in the consumer end of the spectrum, you can find a way to get to consumer adoption relatively quickly.
50:22 Speaker 01 Getting through to an enterprise buyer is not straightforward.
50:28 Craig S. Smith? Yeah, yeah, that's right. And I didn't mean to ignore the work reimagined report. What were your general findings? I mean, I know we're running out of time, but with with regard to AI's impact on the workforce.
50:53 Speaker 01 Well, as you can imagine, I touched on it earlier, that the I mentioned earlier that the, you know, the people dimension of of the
51:04 Speaker 01 proliferation and success of AI will be significant. And so themes around anxiety of the existing workforce. So because a lot of it is just the hype that they read, you know, online in social media and and how things get amplified in a particular way. There's a concern as to what that will mean for their roles. There's the another was around the gap of the learning and development that the employees are getting to embrace some of the tools and be able to use that in their work environment and how they're being encouraged around those things.
51:44 Speaker 01 But I think there was also a little bit, which I think is for leaders to be very mindful of is to is the vision for an organization as to how
51:57 Speaker 01 how they want to embrace AI and what that means for the people within the organization. So not even necessarily than at a micro level saying, you know, an individual that works in a call center, but actually just more broadly, what's the philosophy? What's the vision? How? How important is it? And by by getting people to
52:19 Speaker 01 You know, adopt and use and leverage AI in their day to day lives. They're the staff, the employees are getting a little bit worried that they're being moved into a scenario that, you know, a vision, a philosophy, an end game that they're not clear on in terms of what that looks like. So I think just increasing the communication from a leadership and sponsorship level and the C suite and executives into the workforce to be clear about how they feel about that. What what is what are some of the guardrails they would think to in terms of the use and deployment of this will be really important.
52:58 Craig S. Smith? Yeah, and and it seems you're you're very focused on
53:05 Craig S. Smith? the impact on on the worker, not so much on management.
53:12 Speaker 01 Well, I well, in that in that study as well, you it. Well, I I think the worker includes the management in that sense.
53:19 Craig S. Smith? Yeah.
53:20 Speaker 01 But I but but I I think the, if you think about it in terms of senior management, I think you also have a generational issue in terms of what you typically find, of course, is that younger workers are quite happy to embrace using the tooling and and experiment and innovate. But oftentimes they're working for people who are of a different generation who do not necessarily embrace that innovation themselves personally and will not necessarily reward those that and encourage those that are driving that activity. So there's certainly a kind of workforce intergenerational issue at play there.
54:03 Speaker 01 But I think it affects all levels in terms of potentially the impact on on their, you know, longevity within an organization.
54:14 Craig S. Smith? Yeah, okay, we're we're up to an hour. I mean, do you have a hard stop or or should we? Did we end it here?
54:23 Speaker 01 I don't have a hard stop, but I.
54:26 Craig S. Smith? But you're busy.
54:30 Craig S. Smith? Yeah, no, that's okay. It's just, it's the sort of thing I can talk forever.
54:36 Craig S. Smith? Okay, let's.
54:37 Speaker 01 Or anything you wanted to ask, you didn't get the chance to ask.
54:40 Craig S. Smith? Well, no, it's my, my mind works a little more slowly. Um, so, you know, things occur to me as we go along, but I think we covered everything.
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