WEBVTT 00:00:04.269 --> 00:00:06.769 How do you lead a workforce through a moment 00:00:06.769 --> 00:00:09.869 when the speed of change outpaces the average 00:00:09.869 --> 00:00:12.529 worker's ability to keep up? This is one of the 00:00:12.529 --> 00:00:15.289 questions I hear everywhere I go, from board 00:00:15.289 --> 00:00:18.410 rooms to front lines to conference halls and 00:00:18.410 --> 00:00:21.089 today's guest, he's someone that sits right at 00:00:21.089 --> 00:00:23.929 the heart of this conversation. His name's David 00:00:23.929 --> 00:00:28.089 Martin, he's a senior partner at BCG and the 00:00:28.089 --> 00:00:30.969 leader of their people and organisation practice. 00:00:31.370 --> 00:00:34.210 where he spends his days helping companies rethink 00:00:34.210 --> 00:00:37.869 skills, roles, culture and working patterns all 00:00:37.869 --> 00:00:41.189 as AI is reshaping every corner of the workplace. 00:00:42.009 --> 00:00:46.229 And he also serves on BCG's global AI leadership 00:00:46.229 --> 00:00:49.130 team which gives him a rare vantage point over 00:00:49.130 --> 00:00:52.009 the adoption divide that he's widening between 00:00:52.009 --> 00:00:55.630 those who instinctively fold AI into their daily 00:00:55.630 --> 00:00:58.390 rhythm and those that just keep hitting friction 00:00:58.390 --> 00:01:01.329 at every step along the way. Sound familiar? 00:01:02.469 --> 00:01:04.489 Well, our conversation today will move through 00:01:04.489 --> 00:01:07.750 the patterns BCG is seeing across more than 10 00:01:07.750 --> 00:01:10.989 ,000 survey respondents. He'll explain why AI 00:01:10.989 --> 00:01:13.969 fluency is increasing in some pockets while new 00:01:13.969 --> 00:01:17.250 joiners are stalling at the starting line, why 00:01:17.250 --> 00:01:19.250 middle managers are quietly becoming the heavy 00:01:19.250 --> 00:01:22.609 users and why frontline workers still lack that 00:01:22.609 --> 00:01:24.609 hands -on learning that they need to thrive. 00:01:25.709 --> 00:01:28.829 but we'll also explore together the reality behind 00:01:28.829 --> 00:01:31.670 those big headline claims about productivity 00:01:31.670 --> 00:01:34.730 jumps in engineering and customer service and 00:01:34.730 --> 00:01:37.310 look at how the biggest gains only arrive when 00:01:37.310 --> 00:01:40.349 companies rewire the whole workflow rather than 00:01:40.349 --> 00:01:42.989 just drop a tool on top of an existing process 00:01:42.989 --> 00:01:45.049 so yeah, that means we're going to be talking 00:01:45.049 --> 00:01:47.230 about leadership behaviours the psychology of 00:01:47.230 --> 00:01:50.790 learning under constant disruption under honest 00:01:50.790 --> 00:01:54.109 fears around shadow AI that many leaders are 00:01:54.109 --> 00:01:57.069 quietly trying to contain right now. So the theme 00:01:57.069 --> 00:01:59.129 that we'll run through everything David will 00:01:59.129 --> 00:02:02.750 share today is this phase of AI change has very 00:02:02.750 --> 00:02:06.310 little to do with shiny new models and everything 00:02:06.310 --> 00:02:10.210 to do with people, trust, skills and confidence. 00:02:10.949 --> 00:02:14.430 So how do you lead through all of that with clarity 00:02:14.430 --> 00:02:18.449 and care? But now. It's time for today's interview. 00:02:18.789 --> 00:02:23.530 Let me introduce you to today's guest. So a massive 00:02:23.530 --> 00:02:25.889 warm welcome to the show. Can you tell everyone 00:02:25.889 --> 00:02:28.509 listening a little about who you are and what 00:02:28.509 --> 00:02:31.110 you do? Yeah, sure. So my name is David Martin. 00:02:31.229 --> 00:02:34.050 I'm a senior partner at BCG. I lead our people 00:02:34.050 --> 00:02:36.569 and organization business unit. So everything 00:02:36.569 --> 00:02:39.949 around talent and skills, organizational and 00:02:39.949 --> 00:02:42.229 operating model design and culture and change 00:02:42.229 --> 00:02:45.629 management. And then I serve with a cross -functional 00:02:45.629 --> 00:02:48.210 group of folks on our AI leadership team globally. 00:02:49.519 --> 00:02:53.039 Awesome. And of course AI continues to be a huge 00:02:53.039 --> 00:02:55.419 topic. It's been what three years since chat 00:02:55.419 --> 00:02:58.780 GPT first arrived. We have the early adopters, 00:02:58.919 --> 00:03:01.180 those that are caught in pilot phase, not getting 00:03:01.180 --> 00:03:03.780 out. I've got to ask, what do you see as the 00:03:03.780 --> 00:03:06.039 main reason behind this growing divide between 00:03:06.039 --> 00:03:09.080 those AI fluent teams and those that are just 00:03:09.080 --> 00:03:10.840 struggling to keep up and struggling to get out 00:03:10.840 --> 00:03:13.939 of those pilot phases and into life? Yeah, you 00:03:13.939 --> 00:03:16.729 know, it's funny because i was really impressed 00:03:16.729 --> 00:03:20.009 with how quickly and broadly companies started 00:03:20.009 --> 00:03:23.789 to attack this i think what we see with folks 00:03:23.789 --> 00:03:25.990 who are getting value out of it is they're actually 00:03:25.990 --> 00:03:29.610 doing fewer things and attacking it bigger and 00:03:29.610 --> 00:03:32.849 more holistically which was surprising to us 00:03:32.849 --> 00:03:35.030 um companies that are still struggling are the 00:03:35.030 --> 00:03:38.849 ones who you know we're approaching it by what 00:03:38.849 --> 00:03:41.150 we call a thousand flowers blooming and they 00:03:41.150 --> 00:03:44.319 took on You know hundreds of use cases across 00:03:44.319 --> 00:03:47.639 the organization but thinking about it very narrowly. 00:03:48.120 --> 00:03:49.840 And because of that it's really hard to capture 00:03:49.840 --> 00:03:52.599 value if you save you know five minutes of someone's 00:03:52.599 --> 00:03:55.219 time of week i'm translating that into dollar 00:03:55.219 --> 00:03:57.620 impact is really difficult so they're doing fewer 00:03:57.620 --> 00:04:01.590 things bigger. And I appreciate this is a question 00:04:01.590 --> 00:04:03.610 that everybody wants the answer to right now, 00:04:03.629 --> 00:04:06.669 but how can an organization move beyond simply 00:04:06.669 --> 00:04:10.169 providing AI access to actually enabling their 00:04:10.169 --> 00:04:13.030 employees to use it confidently and effectively? 00:04:13.289 --> 00:04:15.370 Cause we're three years down the line now. So 00:04:15.370 --> 00:04:19.730 you think we'd start to see more happening. Yeah, 00:04:19.769 --> 00:04:22.649 for sure. It's funny because, and we especially 00:04:22.649 --> 00:04:26.939 see adoption lagging on the front lines and Part 00:04:26.939 --> 00:04:29.160 of it is because people have so much day -to 00:04:29.160 --> 00:04:31.959 -day work to do. You ask employees and they say, 00:04:31.980 --> 00:04:34.000 I just don't have time to learn the tools. And 00:04:34.000 --> 00:04:36.399 so one thing that organizations are starting 00:04:36.399 --> 00:04:40.000 to do well is full immersive training. I think 00:04:40.000 --> 00:04:43.399 what we've also seen is in our workshop is just 00:04:43.399 --> 00:04:45.980 not sufficient to help someone understand how 00:04:45.980 --> 00:04:48.379 to use it effectively in their day -to -day life. 00:04:48.420 --> 00:04:51.459 So they're doing more immersive training. They're 00:04:51.459 --> 00:04:53.319 building awareness. They're providing access 00:04:53.319 --> 00:04:55.779 to good quality tools. And we're also seeing 00:04:55.779 --> 00:04:58.180 leadership behavior being a big contributor. 00:04:59.240 --> 00:05:03.360 And so I think our recent data showed that supportive 00:05:03.360 --> 00:05:07.300 leaders have employees who are four times more 00:05:07.300 --> 00:05:10.060 likely to use the tools effectively. And so leadership 00:05:10.060 --> 00:05:13.180 behavior obviously another big piece there. Wow, 00:05:13.180 --> 00:05:15.180 I never saw that one coming I must admit because 00:05:15.180 --> 00:05:17.720 I've heard so many stories of some bosses some 00:05:17.720 --> 00:05:20.139 teams outright banning issues because of the 00:05:20.139 --> 00:05:22.620 fear of the data etc Which is a valid point, 00:05:22.620 --> 00:05:25.399 but there's workarounds around that now, but 00:05:25.399 --> 00:05:28.420 training is it's a great point I mean, why is 00:05:28.420 --> 00:05:31.439 AI training still such a gap for frontline workers? 00:05:31.480 --> 00:05:34.579 And what kind of hands -on learning make is making 00:05:34.579 --> 00:05:36.279 the biggest difference? So one of the other reasons 00:05:36.279 --> 00:05:38.360 I asked that I was speaking somebody recently 00:05:38.360 --> 00:05:40.259 and I was said inside the average organization 00:05:40.259 --> 00:05:43.639 It's the people at mid -tier at that organization. 00:05:44.019 --> 00:05:45.939 They're the heavy users, not the junior users, 00:05:46.019 --> 00:05:48.980 not the C -suites. What's going wrong with training 00:05:48.980 --> 00:05:51.860 here? Well, OK, so maybe a couple of things. 00:05:52.399 --> 00:05:55.139 And your stat, I think, is spot on. We saw 90 00:05:55.139 --> 00:05:58.720 % of middle managers using it at least once a 00:05:58.720 --> 00:06:02.040 week, I think it was, where frontline lags significantly. 00:06:02.560 --> 00:06:05.759 I would say that for the frontline folks using 00:06:05.759 --> 00:06:10.439 it, they are much more frequent users and probably 00:06:10.439 --> 00:06:12.500 more effective users in the middle managers. 00:06:13.079 --> 00:06:15.220 And so we do look at volume and effectiveness 00:06:15.220 --> 00:06:18.480 of usage and adoption, not just, you know, weekly 00:06:18.480 --> 00:06:21.560 usage. Yeah, at the front line, I think one big, 00:06:22.259 --> 00:06:24.819 one big piece is what they have, you know, their 00:06:24.819 --> 00:06:27.259 everyday work to do. And so the tools need to 00:06:27.259 --> 00:06:31.120 be relevant for the work they're doing. It's 00:06:31.120 --> 00:06:33.779 not just using chat GPT to summarize emails or 00:06:33.779 --> 00:06:37.279 to write emails. It's actually If you're a software 00:06:37.279 --> 00:06:40.120 engineer, it's using Claude code or cursor to 00:06:40.120 --> 00:06:44.019 write your code more effectively. And marketing, 00:06:44.160 --> 00:06:46.120 same thing on content creation. If you're an 00:06:46.120 --> 00:06:48.540 HR professional, you're using some of the embedded 00:06:48.540 --> 00:06:53.759 tools inside of your HR IS. And it's really difficult 00:06:53.759 --> 00:06:56.779 for employees to keep up with just how fast the 00:06:56.779 --> 00:07:00.560 ecosystem is changing. And we saw this in software 00:07:00.560 --> 00:07:02.319 engineering. We were working with a large tech 00:07:02.319 --> 00:07:04.959 company. and their engineers were using it about 00:07:04.959 --> 00:07:09.060 once a day, but they had no idea the capability 00:07:09.060 --> 00:07:12.500 of the tools that had recently rolled out. And 00:07:12.500 --> 00:07:14.759 so their ability to use things like the model 00:07:14.759 --> 00:07:18.959 context protocol and some of those tools that 00:07:18.959 --> 00:07:22.819 Claude has rolled out is just far lacking relative 00:07:22.819 --> 00:07:24.860 to what the capabilities are. So that immersive 00:07:24.860 --> 00:07:27.540 training helps, I think, really educate people 00:07:27.540 --> 00:07:30.490 on what the... the quality of the capabilities 00:07:30.490 --> 00:07:32.670 are and how impactful it could be for your day 00:07:32.670 --> 00:07:35.170 -to -day life. And middle managers, I would say 00:07:35.170 --> 00:07:38.410 it's slightly less so. It's more in that chat 00:07:38.410 --> 00:07:42.329 GPT world, which is great. And we do know that 00:07:42.329 --> 00:07:44.569 leaders and managers who are using tools have 00:07:44.569 --> 00:07:47.230 their frontline employees using them more effectively, 00:07:47.930 --> 00:07:50.629 but they're seeing a little bit less value at 00:07:50.629 --> 00:07:52.750 that layer of the organization than the frontline 00:07:52.750 --> 00:07:56.360 employees who are using it well. And you mentioned 00:07:56.360 --> 00:07:58.620 everyone from tech teams, software engineering 00:07:58.620 --> 00:08:01.279 to marketing teams who are largely unaware of 00:08:01.279 --> 00:08:03.839 some of the capabilities of this technology. 00:08:04.000 --> 00:08:06.660 So on that side of things, what role does leadership 00:08:06.660 --> 00:08:09.860 play in helping accelerate AI adoption across 00:08:09.860 --> 00:08:12.699 a company? And I'm curious as well, what behaviors 00:08:12.699 --> 00:08:15.519 separate those successful leaders from the more 00:08:15.519 --> 00:08:19.500 cautious and hesitant ones? Yeah, so I think 00:08:19.500 --> 00:08:22.980 leaders Generally embrace the notion that they 00:08:22.980 --> 00:08:25.939 need to communicate to their employees that the 00:08:25.939 --> 00:08:28.660 employees need to be using the tools. But a good 00:08:28.660 --> 00:08:30.639 leader is actually using the tools themselves 00:08:30.639 --> 00:08:33.519 so they can understand the capabilities and the 00:08:33.519 --> 00:08:36.480 disruptive change. But I think above that is 00:08:36.480 --> 00:08:39.419 curiosity. I think there's a lot of apprehension 00:08:39.419 --> 00:08:43.059 for leaders to actually reinvent themselves. 00:08:43.759 --> 00:08:46.480 And what you'll see, I think, going forward at 00:08:46.480 --> 00:08:50.179 all layers of an organization is that curiosity 00:08:50.179 --> 00:08:54.039 and the always on learning mindset is critical 00:08:54.039 --> 00:08:58.019 and leaders who exhibit that we do see are much 00:08:58.019 --> 00:09:00.539 more effective at helping their frontline drive 00:09:00.539 --> 00:09:03.120 it. I would say the other thing is communicating 00:09:03.120 --> 00:09:06.500 a vision for how they view work to be in the 00:09:06.500 --> 00:09:10.039 future. We've seen a lot of leaders get overwhelmed 00:09:10.039 --> 00:09:12.720 by just how fast the world is changing and the 00:09:12.720 --> 00:09:15.779 uncertainty. And employees can pick up on that. 00:09:16.320 --> 00:09:18.639 And leaders who are able to actually craft a 00:09:18.639 --> 00:09:21.299 vision of where they think their function's going, 00:09:21.480 --> 00:09:23.919 or if you're a CEO, where you think the organization's 00:09:23.919 --> 00:09:26.600 going, and communicating to employees on how 00:09:26.600 --> 00:09:30.259 they fit into that vision, you see much larger 00:09:30.259 --> 00:09:33.460 uptake of the tools. Whereas if you don't do 00:09:33.460 --> 00:09:36.440 that, you see increased amount of fear of job 00:09:36.440 --> 00:09:39.259 loss. And obviously, there's just a lot of uncertainty 00:09:39.259 --> 00:09:42.480 that employees you know aren't very comfortable 00:09:42.480 --> 00:09:44.659 with if you don't have a good leader communicating 00:09:44.659 --> 00:09:49.799 that vision. And we started 2025 talking about 00:09:49.799 --> 00:09:53.220 the ROI, the big questions that organizations 00:09:53.220 --> 00:09:56.720 were asking as they were struggling with scattered 00:09:56.720 --> 00:09:59.299 AI experiments caught in pilot phase. Then it 00:09:59.299 --> 00:10:02.419 evolved, all the conversation evolved into agentic 00:10:02.419 --> 00:10:04.460 AI and the work that agents were doing. We're 00:10:04.460 --> 00:10:07.919 recording this at the end of the year now and 00:10:07.919 --> 00:10:09.820 begin to look back and look ahead at what could 00:10:09.820 --> 00:10:13.440 be happening next year. How have you seen organization 00:10:13.440 --> 00:10:16.100 shift from those AI experiments at the beginning 00:10:16.100 --> 00:10:19.379 of the year to true workflow transformation that's 00:10:19.379 --> 00:10:21.679 driving that real measurable business impact? 00:10:21.799 --> 00:10:24.419 Are you seeing that this year? Yeah, you are. 00:10:24.559 --> 00:10:28.159 And I do think that customer service, marketing, 00:10:28.580 --> 00:10:30.519 software engineering, some in the back office 00:10:30.519 --> 00:10:34.100 functions like FP &A and some HR functions, you 00:10:34.100 --> 00:10:37.440 are actually starting to see not just experimentation 00:10:37.440 --> 00:10:40.529 and pilots, but but really strong value coming 00:10:40.529 --> 00:10:43.169 from the investment there. And it is to your 00:10:43.169 --> 00:10:45.590 point, you have to start with thinking about 00:10:45.590 --> 00:10:49.889 the workflow end to end and identify not just 00:10:49.889 --> 00:10:53.509 places where you can use AI, but identify what 00:10:53.509 --> 00:10:56.409 that new workflow looks like and what the role 00:10:56.409 --> 00:11:00.009 of agents are in that workflow. And then consequently, 00:11:00.370 --> 00:11:03.980 what the role of the humans are. Sometimes that 00:11:03.980 --> 00:11:06.460 includes redefining roles. And that's why companies 00:11:06.460 --> 00:11:08.879 who you see have done it really well in 2025 00:11:08.879 --> 00:11:15.200 have also redefined roles and they have redefined 00:11:15.200 --> 00:11:17.559 competencies in that as well. But the biggest 00:11:17.559 --> 00:11:19.039 thing they've done is think about the workflow 00:11:19.039 --> 00:11:21.399 end to end. If you go back to software engineering 00:11:21.399 --> 00:11:24.759 as a good example, the tech company I mentioned 00:11:24.759 --> 00:11:26.720 earlier, when you started just by looking at 00:11:26.720 --> 00:11:28.659 the workflow, you saw the engineers were only 00:11:28.659 --> 00:11:31.259 spending 35 % of their time with their hands 00:11:31.259 --> 00:11:35.389 on the keyboard. And the other 65 % was going 00:11:35.389 --> 00:11:37.809 back and forth with the product manager on getting 00:11:37.809 --> 00:11:40.690 clarity on the requirements and working downstream 00:11:40.690 --> 00:11:45.190 with quality assurance and deployment. And so 00:11:45.190 --> 00:11:47.929 if you don't address some of those upstream and 00:11:47.929 --> 00:11:50.610 downstream parts of the workflow, then even if 00:11:50.610 --> 00:11:53.809 you're driving huge productivity increases on 00:11:53.809 --> 00:11:56.450 their time spent coding, you're still only at 00:11:56.450 --> 00:11:58.710 a fraction of what the opportunity is. So start 00:11:58.710 --> 00:12:01.149 with the workflow and then think about how GNI 00:12:01.149 --> 00:12:04.419 fits into that. not the other way around. I love 00:12:04.419 --> 00:12:06.799 that. And as I said this year, AI agents has 00:12:06.799 --> 00:12:09.720 been talked about everywhere. Adoption has remained 00:12:09.720 --> 00:12:12.220 relatively low as I think companies try and get 00:12:12.220 --> 00:12:14.879 to grips with the capabilities there. But anything 00:12:14.879 --> 00:12:17.200 you're seeing that's holding companies back and 00:12:17.200 --> 00:12:19.759 how do you see their role evolving next year? 00:12:21.679 --> 00:12:24.139 Yeah, a couple of things. You mentioned it earlier. 00:12:24.159 --> 00:12:27.460 I do think data quality to some degree is holding 00:12:27.460 --> 00:12:29.639 some companies back. And so they're having to 00:12:29.639 --> 00:12:31.379 address just some of their core infrastructure. 00:12:31.679 --> 00:12:36.179 Maybe more importantly is apprehension or risk. 00:12:36.620 --> 00:12:39.399 I do think there's like, and maybe well justified 00:12:39.399 --> 00:12:42.419 reservation from companies about turning over 00:12:42.419 --> 00:12:45.720 too much of the workflow to be run by agents 00:12:45.720 --> 00:12:48.720 because there's this fear of either hallucinations 00:12:48.720 --> 00:12:51.399 or alignment risk or a variety of risks that 00:12:51.399 --> 00:12:53.679 they want to figure out before they embrace that 00:12:53.679 --> 00:12:56.120 too much. And the last one would just be, I don't. 00:12:56.200 --> 00:12:58.139 I think a lot of companies just aren't familiar 00:12:58.139 --> 00:13:02.019 with the possibilities or the capabilities of 00:13:02.019 --> 00:13:05.139 some of those tools. I think what we saw, 70 00:13:05.139 --> 00:13:07.940 % of employees said they had heard about agents 00:13:07.940 --> 00:13:11.740 and only 15 % could describe what they actually 00:13:11.740 --> 00:13:15.039 are. And I think that mirrors a lot of companies 00:13:15.039 --> 00:13:18.240 too, which certainly has inhibited adoption. 00:13:19.699 --> 00:13:23.980 Another topic this year is how IT has added Shadow 00:13:23.980 --> 00:13:27.259 AI to the list of losing battles. Others on the 00:13:27.259 --> 00:13:31.379 list of course would be Shadow IT. before it 00:13:31.379 --> 00:13:35.120 was BYOD, but I mean, with more than half of 00:13:35.120 --> 00:13:37.779 employees more than willing to use unauthorized 00:13:37.779 --> 00:13:41.519 AI tools on their machines and devices, how can 00:13:41.519 --> 00:13:43.840 businesses strike that right balance between 00:13:43.840 --> 00:13:46.179 the innovation and the increased capabilities 00:13:46.179 --> 00:13:50.159 and productivity? And as an XIT guy, that governance, 00:13:50.360 --> 00:13:52.720 you know, the boring stuff. Yeah, it's incredible, 00:13:52.899 --> 00:13:55.509 right? Like one of... company's biggest concerns 00:13:55.509 --> 00:13:57.830 is not being able to get employees to adopt it. 00:13:57.830 --> 00:14:00.970 And then we see the data that says 50 % are using 00:14:00.970 --> 00:14:05.309 it for work outside of their IT infrastructure, 00:14:05.309 --> 00:14:09.850 to your point, which is kind of ironic. One is 00:14:09.850 --> 00:14:12.850 access to quality tools. I think we see if companies 00:14:12.850 --> 00:14:15.190 aren't providing quality tools to their employees, 00:14:15.250 --> 00:14:18.330 then they are finding ways to go outside of the 00:14:18.330 --> 00:14:21.669 enterprise ecosystem and use tools. And then 00:14:21.669 --> 00:14:25.169 the other thing I would say is Just really, really 00:14:25.169 --> 00:14:28.110 good quality training. And I think specifically 00:14:28.110 --> 00:14:31.889 on that one, there's huge risk for an enterprise 00:14:31.889 --> 00:14:34.850 that needs to be managed. I think by both IT 00:14:34.850 --> 00:14:39.730 and HR, um, about using tools outside of the 00:14:39.730 --> 00:14:42.169 enterprise, um, IT infrastructure, obviously 00:14:42.169 --> 00:14:44.649 there's, you know, huge risk with that. It's 00:14:44.649 --> 00:14:47.149 not just an IT job though, to help navigate that 00:14:47.149 --> 00:14:51.299 risk. It is an operating model. and a culture 00:14:51.299 --> 00:14:53.419 change that some companies have to have to make 00:14:53.419 --> 00:14:56.159 sure that their employees understand the risks 00:14:56.159 --> 00:15:00.519 and that they practice the right behaviors. The 00:15:00.519 --> 00:15:03.759 other piece on that shadow IT, which is maybe 00:15:03.759 --> 00:15:07.659 not surprising, is you see while 50 % of employees 00:15:07.659 --> 00:15:10.960 are using tools outside of the ecosystem for 00:15:10.960 --> 00:15:14.879 Gen Z, it is far higher. And so you would expect 00:15:14.879 --> 00:15:17.159 that trend to only increase if companies don't 00:15:17.159 --> 00:15:20.309 get on top of it quickly. Yeah, such a great 00:15:20.309 --> 00:15:22.590 point. And when I was doing a little research 00:15:22.590 --> 00:15:25.090 on you before you came on the podcast, one of 00:15:25.090 --> 00:15:26.590 the things that I found was that you said that 00:15:26.590 --> 00:15:30.649 the secret to AI success is 10 % algorithms, 00:15:30.990 --> 00:15:34.830 20 % technology, and 70 % people and processes. 00:15:34.889 --> 00:15:38.889 And it is so true. So for people that may disagree 00:15:38.889 --> 00:15:41.690 with you, why does that human factor matter so 00:15:41.690 --> 00:15:43.450 much in this equation? Because I think it often 00:15:43.450 --> 00:15:46.590 gets lost in large organizations, but it's more 00:15:46.590 --> 00:15:49.250 important than ever, isn't it? Yeah, well, and 00:15:49.250 --> 00:15:52.330 this is based on empirical data. We were on consistent 00:15:52.330 --> 00:15:55.029 tracking surveys and this data that you mentioned, 00:15:55.149 --> 00:15:59.929 the 10, 20, 70, as we call internally, is been 00:15:59.929 --> 00:16:02.129 consistent really since companies started investing 00:16:02.129 --> 00:16:05.169 in digital transformations even prior to AI. 00:16:05.590 --> 00:16:08.730 And the people process is so important. I mentioned 00:16:08.730 --> 00:16:13.009 earlier just reimagining the workflows and how 00:16:13.009 --> 00:16:16.059 critical that is, but clearly talent. And culture 00:16:16.059 --> 00:16:20.759 also just really important drivers of a company's 00:16:20.759 --> 00:16:23.840 ability to get a return on investment. And so 00:16:23.840 --> 00:16:28.039 if 10 % is data, then 20 % is the tech infrastructure, 00:16:28.100 --> 00:16:30.639 as you mentioned. You still have to have really 00:16:30.639 --> 00:16:33.539 good, high -quality talent managing that other 00:16:33.539 --> 00:16:36.919 30%. And we do see companies who have been early 00:16:36.919 --> 00:16:40.500 adopters and companies who are what we define 00:16:40.500 --> 00:16:43.220 as leaders. They're actually extending their 00:16:43.220 --> 00:16:45.139 lead and a lot of it is because of the people 00:16:45.139 --> 00:16:48.340 in process You see those companies attracting 00:16:48.340 --> 00:16:50.779 better talent and so consequently they're able 00:16:50.779 --> 00:16:53.799 to realize value more effectively and more quickly 00:16:53.799 --> 00:16:57.539 in their investments But yeah that the 70 % on 00:16:57.539 --> 00:17:02.440 people in process is huge And you are in a fantastic 00:17:02.440 --> 00:17:05.099 position here. You get to not only speak to customers 00:17:05.099 --> 00:17:07.099 and clients all around the world, but you also 00:17:07.099 --> 00:17:09.819 get access to a lot of information, a lot of 00:17:09.819 --> 00:17:12.460 data, a lot of reports. So when you put all this 00:17:12.460 --> 00:17:16.200 into your own little AI in your brain, what excites 00:17:16.200 --> 00:17:18.119 you about the road ahead from everything that 00:17:18.119 --> 00:17:21.619 you're seeing and hearing? I think a lot of us 00:17:21.619 --> 00:17:23.779 are in the consulting business because there's 00:17:23.779 --> 00:17:26.460 a little bit of ADD in us and we love change 00:17:26.460 --> 00:17:29.579 and we love to, you know, just to be a part of 00:17:30.759 --> 00:17:33.500 What's at the bleeding edge? And I think what 00:17:33.500 --> 00:17:35.960 excites me is just the amount of change we have 00:17:35.960 --> 00:17:38.460 in front of us and and really the quality of 00:17:38.460 --> 00:17:40.160 life improvements that will come out of this 00:17:40.160 --> 00:17:43.279 as well. I think there's really exciting opportunities 00:17:43.279 --> 00:17:45.380 and in the field of health care like back to 00:17:45.380 --> 00:17:47.559 your point on us having, you know, pretty good 00:17:47.559 --> 00:17:49.420 data and pretty good visibility across a lot 00:17:49.420 --> 00:17:51.920 of industries. I'm I'm really excited about the 00:17:51.920 --> 00:17:54.640 impact AI can have on humanity and solving some 00:17:54.640 --> 00:17:56.519 of our most complex challenges, whether it be 00:17:56.519 --> 00:17:59.779 health care or food scarcity or things like that. 00:18:00.029 --> 00:18:02.470 And then I'm just fascinated to see where the 00:18:02.470 --> 00:18:06.269 technology takes us. I think I've seen some of 00:18:06.269 --> 00:18:08.470 the tech leaders over the past couple of weeks 00:18:08.470 --> 00:18:13.910 or even year just talking about how quickly some 00:18:13.910 --> 00:18:17.049 of the breakthrough technologies are changing 00:18:17.049 --> 00:18:20.900 and are gonna be in front of us. and as I said 00:18:20.900 --> 00:18:22.859 you've got access to so much information now 00:18:22.859 --> 00:18:24.980 you might find it easy it might even be more 00:18:24.980 --> 00:18:27.500 challenging for you someone leading the road 00:18:27.500 --> 00:18:29.980 ahead but for many people listening that pace 00:18:29.980 --> 00:18:32.920 of technological change and how do they continuously 00:18:32.920 --> 00:18:34.839 learn and keep up to speed with everything I 00:18:34.839 --> 00:18:36.440 think that's something many people are going 00:18:36.440 --> 00:18:39.640 to be thinking about as they hit 2026 and this 00:18:39.640 --> 00:18:41.240 is what I'm going to do differently this is what 00:18:41.240 --> 00:18:43.559 I'm going to learn and all those kind of resolutions 00:18:43.559 --> 00:18:46.299 before we resort back to our usual self -buy 00:18:46.299 --> 00:18:49.099 end of January but for anyone that is thinking 00:18:49.099 --> 00:18:50.990 that How do you self -educate? How do you keep 00:18:50.990 --> 00:18:52.710 up to speed? Any tips or anything you'd be doing 00:18:52.710 --> 00:18:55.190 there? Well, I do listen to a lot of podcasts 00:18:55.190 --> 00:18:59.009 and I guess I'll start by saying another piece 00:18:59.009 --> 00:19:02.210 of data from the survey was asking people if 00:19:02.210 --> 00:19:04.809 they're saving time by using generative AI, what 00:19:04.809 --> 00:19:06.809 are they doing with that time? And you could 00:19:06.809 --> 00:19:10.269 say how much of that productivity improvement 00:19:10.269 --> 00:19:13.490 do you get? I'm to invest into your own learning 00:19:13.490 --> 00:19:16.869 and i think right now the data showed well companies 00:19:16.869 --> 00:19:20.410 are really demanding a lot of different things 00:19:20.410 --> 00:19:22.890 and so they're spending it more on leisure activities 00:19:22.890 --> 00:19:25.369 and things like that and i do think that. Spending 00:19:25.369 --> 00:19:28.109 time investing in yourself and learning is gonna 00:19:28.109 --> 00:19:31.769 be critical to the specific question i spend 00:19:31.769 --> 00:19:34.849 a lot of time listening to podcasts i read as 00:19:34.849 --> 00:19:39.849 much as i can. I have children who are. One just 00:19:39.849 --> 00:19:43.049 started college and and I have twins who are 00:19:43.049 --> 00:19:45.670 just about to start high school and I'm convinced 00:19:45.670 --> 00:19:48.329 that they need to also be learning about it. 00:19:48.329 --> 00:19:50.329 And so I'm trying to be a good role model for 00:19:50.329 --> 00:19:53.670 them. But yeah, lots of reading and lots of podcasts 00:19:53.670 --> 00:19:56.869 primarily. Brilliant, and I think that's a brilliant 00:19:56.869 --> 00:19:59.150 moment to end on, but before I do let you go, 00:19:59.369 --> 00:20:01.450 for anyone listening wanting to find out more 00:20:01.450 --> 00:20:04.329 information about you, your work at BCG, et cetera, 00:20:04.710 --> 00:20:06.289 or where they can keep up to speed with anything. 00:20:06.410 --> 00:20:09.029 Anyway, in particular, you'd like to point everyone? 00:20:10.089 --> 00:20:12.950 Yeah, so we've been pretty prolific in publishing. 00:20:13.109 --> 00:20:16.869 We put all of that on our bcg .com website. We, 00:20:17.049 --> 00:20:19.710 as I've alluded to a couple of times, have a... 00:20:19.740 --> 00:20:23.160 A variety of different research reports that 00:20:23.160 --> 00:20:25.619 are out. One is called AI at Work, which I'd 00:20:25.619 --> 00:20:27.599 encourage people to check out. It covers a lot 00:20:27.599 --> 00:20:30.119 of what we talked today about with respect to 00:20:30.119 --> 00:20:33.160 training and adoption. We have research called 00:20:33.160 --> 00:20:35.940 Build for the Future, which is some of what I 00:20:35.940 --> 00:20:39.660 alluded to around value and return on investment. 00:20:39.960 --> 00:20:42.160 And then we actually just this week published 00:20:42.160 --> 00:20:46.759 research in concert with MIT about kind of the 00:20:46.759 --> 00:20:49.319 impact of AI on the workforce. And so those would 00:20:49.319 --> 00:20:51.740 be a couple of specific ones to check out. But 00:20:51.740 --> 00:20:54.359 like I said, we publish significantly. People 00:20:54.359 --> 00:20:57.559 can also, of course, hit me up on LinkedIn and 00:20:57.559 --> 00:21:00.220 we can connect that way as well. And you can 00:21:00.220 --> 00:21:03.000 see some of what I've been posting about this 00:21:03.000 --> 00:21:05.599 topic. Brilliant. Well, I'll have links to everything 00:21:05.599 --> 00:21:07.460 you mentioned there. Make it easy for people 00:21:07.460 --> 00:21:10.559 to find out more information. Love chatting with 00:21:10.559 --> 00:21:12.420 you today. We had a little bit of fun along the 00:21:12.420 --> 00:21:14.140 way, but more than anything, just thank you for 00:21:14.140 --> 00:21:16.140 sharing your insights today. Pure gold. Thanks 00:21:16.140 --> 00:21:18.420 for joining. Thanks, Neil, and thanks for all 00:21:18.420 --> 00:21:21.460 you do. So this is great. I think what stood 00:21:21.460 --> 00:21:23.859 out most in that conversation was just how much 00:21:23.859 --> 00:21:26.740 of the real progress happens far away from those 00:21:26.740 --> 00:21:30.359 headlines in our news feeds. Yes, AI capability 00:21:30.359 --> 00:21:34.660 is accelerating at a wild pace, yet the human 00:21:34.660 --> 00:21:37.720 readiness that unlocks its value is often uneven 00:21:37.720 --> 00:21:41.619 and overlooked. And David's point about immersive 00:21:41.619 --> 00:21:44.740 learning landed strongly for me because one hour 00:21:44.740 --> 00:21:47.809 workshop Scattered pilots might look neat on 00:21:47.809 --> 00:21:50.509 a slide and ticking a few boxes, but they don't 00:21:50.509 --> 00:21:54.410 move the dial It's when people receive focused 00:21:54.410 --> 00:21:56.990 hands -on coaching and see leaders using the 00:21:56.990 --> 00:21:59.970 tools themselves These are the moments the magic 00:21:59.970 --> 00:22:02.769 moments where confidence rises and real change 00:22:02.769 --> 00:22:06.730 takes hold So it's a reminder that adoption is 00:22:06.730 --> 00:22:09.789 built through rhythm and repetition rather than 00:22:09.789 --> 00:22:13.609 announcements and slogans So thank you to him 00:22:13.609 --> 00:22:16.599 for bringing some much needed clarity to the 00:22:16.599 --> 00:22:19.359 debate around AI agents as well because I think 00:22:19.359 --> 00:22:22.059 plenty of companies are curious right now very 00:22:22.059 --> 00:22:25.240 few feel fully prepared and that is okay but 00:22:25.240 --> 00:22:28.000 many still need to strengthen their data foundations 00:22:28.000 --> 00:22:30.819 before they go one of the repeated phrases I'm 00:22:30.819 --> 00:22:33.559 hearing at conferences all over the world is 00:22:33.559 --> 00:22:38.619 no data no AI and despite all this though optimism 00:22:38.619 --> 00:22:41.480 from workers who understand the tools is quite 00:22:41.480 --> 00:22:44.359 striking When people see how these agents fit 00:22:44.359 --> 00:22:46.640 into the wider workflow and understand where 00:22:46.640 --> 00:22:49.519 human judgment remains essential the fear fades 00:22:49.519 --> 00:22:52.960 and that tension between excitement and caution 00:22:52.960 --> 00:22:56.160 I think is something that could shape 2026 in 00:22:56.160 --> 00:22:59.720 a very real way and leaders who guide their teams 00:22:59.720 --> 00:23:02.700 with transparent communications rather than just 00:23:02.700 --> 00:23:04.779 trying to replace people with technology these 00:23:04.779 --> 00:23:07.940 are the ones that will benefit the most. So As 00:23:07.940 --> 00:23:10.660 we wrap up, I'm keen to hear your thoughts. Where 00:23:10.660 --> 00:23:13.519 do you see yourself in this adoption story? Are 00:23:13.519 --> 00:23:17.140 you feeling energised by the pace of change or 00:23:17.140 --> 00:23:20.319 overwhelmed by it? And if you had to choose one 00:23:20.319 --> 00:23:25.470 area to upskill in 2026, what would it be? Share 00:23:25.470 --> 00:23:28.410 those reflections with me because your experiences 00:23:28.410 --> 00:23:31.970 matter just as much as the expert insights on 00:23:31.970 --> 00:23:35.170 the show. So please head over to techtalksnetwork 00:23:35.170 --> 00:23:37.430 .com. You can leave me an audio message there 00:23:37.430 --> 00:23:41.230 or go to LinkedIn X Instagram, just at Neil C 00:23:41.230 --> 00:23:43.950 Hughes. But that's it for today so huge thank 00:23:43.950 --> 00:23:47.230 you to everyone at BCG, my guests and indeed 00:23:47.230 --> 00:23:50.230 you for tuning in every single day. I'm conscious 00:23:50.230 --> 00:23:53.369 I do throw a lot of interviews your way so thank 00:23:53.369 --> 00:23:55.829 you for coming back and hopefully you'll join 00:23:55.829 --> 00:23:58.789 me again tomorrow. Speak with you then. Bye for 00:23:58.789 --> 00:23:58.930 now.