1 00:00:00,125 --> 00:00:00,792 People that will 2 00:00:00,792 --> 00:00:03,128 join companies next year 3 00:00:03,128 --> 00:00:04,713 will be managers on day one. 4 00:00:05,046 --> 00:00:05,714 They will just be 5 00:00:05,714 --> 00:00:06,923 managing a workforce 6 00:00:06,923 --> 00:00:07,257 that is an 7 00:00:07,257 --> 00:00:09,050 agentic-based workforce, 8 00:00:09,050 --> 00:00:09,718 one that is 9 00:00:09,718 --> 00:00:10,593 extremely powerful 10 00:00:10,593 --> 00:00:11,803 and sometimes clumsy. 11 00:00:16,808 --> 00:00:17,809 Welcome to WorkLab 12 00:00:17,809 --> 00:00:19,102 the podcast for Microsoft. 13 00:00:19,102 --> 00:00:20,228 I’m Molly Wood. 14 00:00:20,228 --> 00:00:21,438 On this show, we explore 15 00:00:21,438 --> 00:00:23,732 the future of work and the power of AI 16 00:00:23,732 --> 00:00:25,358 to amplify human potential 17 00:00:25,358 --> 00:00:27,235 and transform organizations. 18 00:00:27,235 --> 00:00:29,529 And today's guest is at the forefront 19 00:00:29,529 --> 00:00:31,031 of this new world of business. 20 00:00:31,031 --> 00:00:33,074 Dan Diasio is Global Consulting 21 00:00:33,074 --> 00:00:35,160 AI leader at EY. 22 00:00:35,160 --> 00:00:36,536 We'll be talking about moving from 23 00:00:36,536 --> 00:00:38,913 pilot projects to real world impact, 24 00:00:38,913 --> 00:00:40,874 reskilling for the AI era, 25 00:00:40,874 --> 00:00:42,459 and what leadership looks like 26 00:00:42,459 --> 00:00:45,378 when humans and AI agents team up. 27 00:00:45,378 --> 00:00:47,255 EY is in the inaugural class 28 00:00:47,255 --> 00:00:48,798 of the Digital Data Design 29 00:00:48,798 --> 00:00:50,383 Institute at Harvard 30 00:00:50,383 --> 00:00:52,635 Frontier Firm AI Initiative, 31 00:00:52,635 --> 00:00:54,512 hosted by Harvard Business School 32 00:00:54,512 --> 00:00:56,181 in collaboration with Microsoft. 33 00:00:56,556 --> 00:00:57,766 The initiative will research 34 00:00:57,766 --> 00:00:59,392 human-AI collaboration, 35 00:00:59,392 --> 00:01:01,311 upskill global C-suite leadership, 36 00:01:01,311 --> 00:01:03,354 and deliver new insights and tools 37 00:01:03,354 --> 00:01:05,356 to help reinvent organizations 38 00:01:05,356 --> 00:01:07,067 as Frontier Firms. 39 00:01:07,275 --> 00:01:08,860 Dan, welcome to WorkLab. 40 00:01:08,860 --> 00:01:10,111 I'm excited to join you, Molly. 41 00:01:10,111 --> 00:01:11,571 You've been in this business a long time. 42 00:01:11,571 --> 00:01:13,364 Tell me what you have seen 43 00:01:13,364 --> 00:01:14,324 and how you've ended up 44 00:01:14,324 --> 00:01:15,408 in the moment we're in right now. 45 00:01:15,950 --> 00:01:17,327 EY is a large, 46 00:01:17,327 --> 00:01:18,578 complex organization. 47 00:01:18,578 --> 00:01:20,205 We have 400,000 people. 48 00:01:20,205 --> 00:01:21,831 There is 100 years’ 49 00:01:21,831 --> 00:01:22,665 worth of history 50 00:01:22,665 --> 00:01:25,001 and had a heritage in the businesses 51 00:01:25,001 --> 00:01:26,336 we operate in. 52 00:01:26,336 --> 00:01:27,796 It was only a couple of months into 53 00:01:27,796 --> 00:01:29,214 after ChatGPT had 54 00:01:29,214 --> 00:01:30,465 kind of arrived on the scene, 55 00:01:30,465 --> 00:01:32,300 and we realized this was very different 56 00:01:32,300 --> 00:01:33,676 from the AI of the past. 57 00:01:33,968 --> 00:01:35,345 I would say AI of the past 58 00:01:35,345 --> 00:01:36,971 was really focused as a discipline, 59 00:01:36,971 --> 00:01:38,932 like there was a team of data scientists 60 00:01:38,932 --> 00:01:40,141 and machine learning engineers 61 00:01:40,391 --> 00:01:41,768 that were really responsible 62 00:01:41,768 --> 00:01:43,478 for taking data and turning that 63 00:01:43,478 --> 00:01:44,646 into insights and 64 00:01:44,646 --> 00:01:46,481 translating that into actions. 65 00:01:46,731 --> 00:01:48,525 It was a part of our organization. 66 00:01:48,525 --> 00:01:49,901 What we realized pretty quickly 67 00:01:49,901 --> 00:01:51,611 is that AI was going to impact 68 00:01:51,611 --> 00:01:52,946 every single corner 69 00:01:52,946 --> 00:01:55,281 across every part of our business, 70 00:01:55,281 --> 00:01:56,699 and we needed to really rethink 71 00:01:56,699 --> 00:01:58,576 what our organization was going to be. 72 00:01:58,910 --> 00:02:01,079 So we created a part of our business. 73 00:02:01,079 --> 00:02:02,831 We called it EY.ai, 74 00:02:02,831 --> 00:02:04,874 which was the symbol for us internally 75 00:02:04,874 --> 00:02:06,167 that we need to move from the old 76 00:02:06,167 --> 00:02:09,170 business EY.com to EY.ai, 77 00:02:09,170 --> 00:02:11,047 and that meant a real rescale 78 00:02:11,047 --> 00:02:12,257 and rethink of everything 79 00:02:12,257 --> 00:02:13,758 that we do across the organization 80 00:02:13,758 --> 00:02:15,343 and how we enable our people. 81 00:02:15,552 --> 00:02:17,595 I'd say it's been very fundamental, 82 00:02:17,595 --> 00:02:19,430 but we really started with a purpose 83 00:02:19,430 --> 00:02:21,307 and an intent to be able to drive 84 00:02:21,307 --> 00:02:22,976 AI systemically across the business, 85 00:02:22,976 --> 00:02:25,061 as opposed to just turn it on in a way. 86 00:02:25,061 --> 00:02:26,646 It feels like you saw something 87 00:02:26,646 --> 00:02:27,480 really important coming 88 00:02:27,480 --> 00:02:29,023 because to be candid about the 89 00:02:29,023 --> 00:02:31,109 elephant in the room, I would say that 90 00:02:31,526 --> 00:02:34,195 people feel that the advent of LLMs 91 00:02:34,195 --> 00:02:36,614 and the way that people are using AI now 92 00:02:36,614 --> 00:02:38,700 could pose a threat to the consulting 93 00:02:38,700 --> 00:02:40,910 business that we have always known. 94 00:02:40,910 --> 00:02:41,870 I'm putting this gently, 95 00:02:41,870 --> 00:02:43,163 but it sounds like EY 96 00:02:43,163 --> 00:02:45,123 saw that almost immediately 97 00:02:45,123 --> 00:02:46,499 and moved to adapt. 98 00:02:46,499 --> 00:02:48,585 Yeah, I mean, I think there's been a lot 99 00:02:48,585 --> 00:02:49,836 written about the 100 00:02:49,836 --> 00:02:51,379 demise of the knowledge worker 101 00:02:51,379 --> 00:02:52,547 in the space of AI. 102 00:02:52,547 --> 00:02:53,798 That as cost of knowledge 103 00:02:53,798 --> 00:02:55,425 goes to zero, what happens 104 00:02:55,425 --> 00:02:57,260 to all of these knowledge workers? 105 00:02:57,260 --> 00:02:58,678 And, you know, over time, 106 00:02:58,678 --> 00:03:00,430 I didn't have this impression immediately. 107 00:03:00,430 --> 00:03:01,639 Like there was a bit of shock 108 00:03:01,639 --> 00:03:03,224 and awe that happened in the beginning. 109 00:03:03,224 --> 00:03:04,100 But over time, 110 00:03:04,100 --> 00:03:06,060 I've come to appreciate and believe 111 00:03:06,060 --> 00:03:07,187 that the knowledge worker 112 00:03:07,187 --> 00:03:09,772 is just totally underrated in this moment. 113 00:03:10,064 --> 00:03:11,399 Let's talk about your career at EY 114 00:03:11,399 --> 00:03:12,483 because you’ve been there 115 00:03:12,483 --> 00:03:12,984 a long time, 116 00:03:12,984 --> 00:03:13,943 you’ve been in this business 117 00:03:13,943 --> 00:03:14,569 a long time. 118 00:03:15,028 --> 00:03:16,112 So, Molly, this is a 119 00:03:16,112 --> 00:03:17,197 really fascinating time. 120 00:03:17,197 --> 00:03:18,781 I would say, right now 121 00:03:18,781 --> 00:03:19,991 I spend most of my time 122 00:03:19,991 --> 00:03:21,826 working on trying to help 123 00:03:21,826 --> 00:03:24,037 EY become a Frontier Firm. 124 00:03:24,037 --> 00:03:25,371 And that really means that I focus on 125 00:03:25,371 --> 00:03:26,706 four things every day. 126 00:03:26,706 --> 00:03:28,041 You know, so first 127 00:03:28,041 --> 00:03:29,500 I'm really working with our teams 128 00:03:29,500 --> 00:03:30,835 that are supporting our clients 129 00:03:30,835 --> 00:03:32,921 and trying to move from this idea 130 00:03:32,921 --> 00:03:34,714 of ideation and experimentation 131 00:03:34,714 --> 00:03:37,550 into enterprise scale with our AI agendas. 132 00:03:37,800 --> 00:03:39,761 The second is, if you make a list 133 00:03:39,761 --> 00:03:41,429 of all the industries that are going 134 00:03:41,429 --> 00:03:43,014 to be impacted by AI 135 00:03:43,014 --> 00:03:45,141 professional services near the top of that list. 136 00:03:45,141 --> 00:03:46,643 So we are actively working to 137 00:03:46,643 --> 00:03:48,144 look at everything we do 138 00:03:48,144 --> 00:03:49,771 to deliver value for our clients 139 00:03:49,771 --> 00:03:51,397 and start to infuse AI to become 140 00:03:51,397 --> 00:03:52,482 much more AI powered. 141 00:03:52,649 --> 00:03:53,858 The third is 142 00:03:53,858 --> 00:03:56,319 we have a historical dedication 143 00:03:56,319 --> 00:03:57,278 to a business model 144 00:03:57,278 --> 00:03:58,821 that is focused on effort, and 145 00:03:58,821 --> 00:04:00,406 we are looking to break that with AI. 146 00:04:00,406 --> 00:04:01,574 So there's a lot around 147 00:04:01,574 --> 00:04:02,742 commercial model innovation. 148 00:04:02,742 --> 00:04:04,244 And then fourth, the very essence of 149 00:04:04,244 --> 00:04:05,954 EY is all about our people. 150 00:04:06,246 --> 00:04:07,622 So we are working on building 151 00:04:07,622 --> 00:04:09,499 training programs, tooling and enablement 152 00:04:09,499 --> 00:04:10,917 to really empower the workforce. 153 00:04:10,917 --> 00:04:12,794 I spend most of my time these days 154 00:04:12,794 --> 00:04:15,171 really trying to figure out how we kind of 155 00:04:15,171 --> 00:04:16,714 create a new professional services firm 156 00:04:16,714 --> 00:04:18,299 that is based much more on AI 157 00:04:18,299 --> 00:04:19,717 and disrupting the old one. 158 00:04:19,926 --> 00:04:22,178 There are so many things to unpack there. 159 00:04:22,178 --> 00:04:24,347 Let's start with just the EY part of it, 160 00:04:24,347 --> 00:04:25,807 just the internal transformation. 161 00:04:25,807 --> 00:04:27,600 Because, of course, that's incredibly 162 00:04:27,600 --> 00:04:29,727 valuable when it comes to helping clients. 163 00:04:29,936 --> 00:04:31,479 But I would imagine presents 164 00:04:31,479 --> 00:04:33,940 its own set of challenges 165 00:04:33,940 --> 00:04:35,400 given the size and 166 00:04:35,400 --> 00:04:37,360 history of a firm like EY. 167 00:04:37,360 --> 00:04:39,195 So, Molly, if I can tell you a story? 168 00:04:39,195 --> 00:04:40,613 Say more, absolutely. 169 00:04:40,613 --> 00:04:42,907 So shortly after ChatGPT 170 00:04:42,907 --> 00:04:44,617 came onto the scene, we realized 171 00:04:44,617 --> 00:04:46,661 that our clients were being bombarded 172 00:04:46,661 --> 00:04:48,871 by PowerPoints explaining what AI was. 173 00:04:48,871 --> 00:04:51,374 And you can't learn that much about 174 00:04:51,374 --> 00:04:53,376 how these things work from a PowerPoint. 175 00:04:53,751 --> 00:04:55,753 So we created something inside our 176 00:04:55,753 --> 00:04:58,423 organization that we called a master class. 177 00:04:58,423 --> 00:04:59,966 We would show up with laptops 178 00:04:59,966 --> 00:05:01,676 in our clients, 179 00:05:01,676 --> 00:05:02,927 often in their boardroom 180 00:05:02,927 --> 00:05:04,554 or with their management committee. 181 00:05:04,554 --> 00:05:05,972 And we had some 182 00:05:05,972 --> 00:05:07,682 simple tools and a script. 183 00:05:07,932 --> 00:05:10,310 Often that script was to be able to use 184 00:05:10,310 --> 00:05:13,688 AI to build a new snack product 185 00:05:13,688 --> 00:05:15,023 in a lot of ways, so 186 00:05:15,023 --> 00:05:16,274 it was kind of simple, 187 00:05:16,274 --> 00:05:17,734 It was guided, it was scripted, 188 00:05:17,734 --> 00:05:19,819 but it got their hands on the keyboards. 189 00:05:20,153 --> 00:05:22,030 And it was fascinating, 190 00:05:22,030 --> 00:05:24,032 like just to watch this magic happen 191 00:05:24,032 --> 00:05:26,409 where CEOs were working in teams 192 00:05:26,409 --> 00:05:28,578 with their management committee, 193 00:05:29,078 --> 00:05:30,204 building new products, 194 00:05:30,204 --> 00:05:32,165 creating new marketing plans, 195 00:05:32,165 --> 00:05:33,583 creating jingles 196 00:05:33,583 --> 00:05:34,959 that they could use to advertise it, 197 00:05:34,959 --> 00:05:35,668 and then pitching it 198 00:05:35,668 --> 00:05:36,961 back to their committees. 199 00:05:36,961 --> 00:05:38,463 So it was really, really powerful. 200 00:05:39,047 --> 00:05:40,423 But then we took a step back. 201 00:05:40,423 --> 00:05:42,425 We've done this hundreds of times now, 202 00:05:42,425 --> 00:05:43,885 and I've looked at the results 203 00:05:43,885 --> 00:05:45,762 of all the images of the products 204 00:05:45,762 --> 00:05:47,263 that people have built over time, 205 00:05:47,764 --> 00:05:50,767 and it's all the same looking stuff. 206 00:05:51,351 --> 00:05:53,978 So it's all the same sort of packaging. 207 00:05:53,978 --> 00:05:55,563 It's all the same ingredients, 208 00:05:55,563 --> 00:05:56,647 the same recipes, 209 00:05:56,647 --> 00:05:57,899 the same marketing plans. 210 00:05:57,899 --> 00:05:59,525 Like if this stuff were to come true, 211 00:05:59,525 --> 00:06:00,735 we would have a global shortage 212 00:06:00,735 --> 00:06:01,652 of matcha 213 00:06:01,652 --> 00:06:03,071 and monk fruit everywhere. 214 00:06:03,279 --> 00:06:05,281 But it's a lot of the same. 215 00:06:05,281 --> 00:06:07,992 So what that kind of really translates 216 00:06:07,992 --> 00:06:10,203 to us is AI makes it very easy to produce 217 00:06:10,203 --> 00:06:12,246 something good, but it kind of 218 00:06:12,246 --> 00:06:14,207 commoditizes the output. 219 00:06:14,207 --> 00:06:16,876 And in a lot of ways it raises the floor, 220 00:06:16,876 --> 00:06:18,169 but it doesn't raise the ceiling. 221 00:06:18,544 --> 00:06:19,796 So what does it take 222 00:06:19,796 --> 00:06:21,339 to actually raise the ceiling? 223 00:06:21,339 --> 00:06:23,591 And what we say at EY is that it's 224 00:06:23,591 --> 00:06:25,635 AI and something. 225 00:06:25,635 --> 00:06:28,262 You have to bring context to be able 226 00:06:28,262 --> 00:06:30,139 to really unlock its potential. 227 00:06:30,556 --> 00:06:31,849 We often refer to these things 228 00:06:31,849 --> 00:06:32,975 as the big four. 229 00:06:32,975 --> 00:06:34,852 So you need to have creativity. 230 00:06:34,852 --> 00:06:36,687 You need to have critical thinking, 231 00:06:36,687 --> 00:06:39,357 systems thinking, and deep domain 232 00:06:39,357 --> 00:06:41,734 expertise to be able to really get 233 00:06:41,734 --> 00:06:44,821 what's possible into the system, to work 234 00:06:44,821 --> 00:06:46,114 together with the system, to be able 235 00:06:46,114 --> 00:06:47,824 to create the right and best output. 236 00:06:48,282 --> 00:06:51,536 And in a lot of ways, that's essentially 237 00:06:51,536 --> 00:06:54,330 what consultants are very good at. 238 00:06:54,330 --> 00:06:56,082 So we see that the role of the consultant 239 00:06:56,082 --> 00:06:57,875 is going to shift from one that does 240 00:06:57,875 --> 00:07:00,336 a lot of work and produces content 241 00:07:00,336 --> 00:07:02,547 to one that is much more of a creator, 242 00:07:02,547 --> 00:07:03,548 and using agents 243 00:07:03,548 --> 00:07:04,966 to be able to do a lot of that work. 244 00:07:05,216 --> 00:07:06,551 I mean, as you describe it, 245 00:07:06,551 --> 00:07:07,802 it sounds like what you're saying is 246 00:07:07,802 --> 00:07:08,886 we're going to have our consultants 247 00:07:08,886 --> 00:07:10,847 go back to being great, right? 248 00:07:10,847 --> 00:07:12,140 Like not that they weren't great 249 00:07:12,140 --> 00:07:14,767 to start with, but that there is an 250 00:07:14,767 --> 00:07:17,186 up-leveling that is required 251 00:07:17,186 --> 00:07:19,772 to not only stay ahead but be the best. 252 00:07:19,981 --> 00:07:21,816 And I think they have, you know, often 253 00:07:21,816 --> 00:07:22,859 we find that consultants 254 00:07:22,859 --> 00:07:24,235 have contexts that exists 255 00:07:24,235 --> 00:07:25,862 outside the organization 256 00:07:25,862 --> 00:07:27,780 in which they're supporting’s four walls, 257 00:07:27,780 --> 00:07:29,240 and that is extremely valuable 258 00:07:29,240 --> 00:07:31,033 to be able to get the most out of AI. 259 00:07:31,033 --> 00:07:32,994 So, I do think it is a big change 260 00:07:32,994 --> 00:07:34,745 to move from the old consulting model 261 00:07:34,745 --> 00:07:36,247 to the new consulting model, 262 00:07:36,247 --> 00:07:37,999 but I don't think that work goes away. 263 00:07:37,999 --> 00:07:38,666 It changes, 264 00:07:38,666 --> 00:07:40,418 and I think it becomes more important. 265 00:07:40,418 --> 00:07:41,836 Let's talk about your clients now. 266 00:07:41,836 --> 00:07:43,504 How often are you now 267 00:07:43,504 --> 00:07:45,339 telling this story to them? 268 00:07:45,339 --> 00:07:47,717 I think this is, you know, 269 00:07:47,717 --> 00:07:49,844 we are going through a period right now 270 00:07:49,844 --> 00:07:51,721 where there's too much focus 271 00:07:51,721 --> 00:07:52,847 on productivity 272 00:07:52,847 --> 00:07:54,891 and there's not as much focus 273 00:07:54,891 --> 00:07:56,684 as needed on growth. 274 00:07:56,684 --> 00:07:57,810 And this is very much 275 00:07:57,810 --> 00:07:59,395 part of the growth agenda, 276 00:07:59,395 --> 00:08:01,063 how we start to move 277 00:08:01,063 --> 00:08:02,982 from thinking about what we do today 278 00:08:02,982 --> 00:08:04,192 and how we can use technology 279 00:08:04,192 --> 00:08:05,109 to automate it, 280 00:08:05,109 --> 00:08:06,110 to how we can start 281 00:08:06,110 --> 00:08:07,820 to empower people to start 282 00:08:07,820 --> 00:08:09,614 to create the businesses of the future. 283 00:08:09,614 --> 00:08:11,449 So, it is probably a daily 284 00:08:11,449 --> 00:08:12,408 part of that talk tracks 285 00:08:12,408 --> 00:08:13,451 that I have with clients. 286 00:08:13,451 --> 00:08:15,411 Is it like a matcha granola bar? 287 00:08:15,411 --> 00:08:16,412 Like, what are we talking here? 288 00:08:16,412 --> 00:08:18,206 There's like some monk fruit in it, 289 00:08:18,206 --> 00:08:19,248 some matcha, 290 00:08:19,248 --> 00:08:20,666 You know, often some 291 00:08:20,666 --> 00:08:22,668 some like natural chocolate. 292 00:08:22,668 --> 00:08:24,295 I mean, the same packaging. 293 00:08:24,295 --> 00:08:25,922 It's very crusty looking, 294 00:08:25,922 --> 00:08:27,507 you know, deep greens and browns. 295 00:08:27,507 --> 00:08:28,966 Very environmentally friendly. 296 00:08:28,966 --> 00:08:30,051 Of course, yeah. 297 00:08:30,343 --> 00:08:31,761 I mean, I kind of want to try it. 298 00:08:32,637 --> 00:08:33,638 But we're off topic. 299 00:08:33,638 --> 00:08:36,974 As you start to socialize the adoption 300 00:08:37,600 --> 00:08:38,601 of this technology 301 00:08:38,601 --> 00:08:40,478 with this really important realization, 302 00:08:40,478 --> 00:08:41,854 right, that your human skills matter, 303 00:08:41,854 --> 00:08:42,980 that your context matters, 304 00:08:42,980 --> 00:08:45,107 that your internal data 305 00:08:45,107 --> 00:08:46,275 and the context that brings 306 00:08:46,275 --> 00:08:47,610 you as a business matter, 307 00:08:47,610 --> 00:08:48,903 what kind of specifics 308 00:08:48,903 --> 00:08:50,988 are you starting to talk to people 309 00:08:50,988 --> 00:08:52,156 about when it comes to adoption? 310 00:08:52,156 --> 00:08:54,242 Like, are we building a playbook at last? 311 00:08:54,242 --> 00:08:56,118 Yes, I think we have the beginnings 312 00:08:56,118 --> 00:08:57,787 of a playbook that's been really effective 313 00:08:57,787 --> 00:08:58,663 for many of the clients 314 00:08:58,663 --> 00:08:59,664 that we've been supporting. 315 00:08:59,664 --> 00:09:00,831 The last couple of years 316 00:09:00,831 --> 00:09:02,583 have been an investment in technology. 317 00:09:02,583 --> 00:09:03,709 You're building tools, 318 00:09:03,709 --> 00:09:05,127 and when you use those tools 319 00:09:05,127 --> 00:09:06,170 and you expect to get value 320 00:09:06,170 --> 00:09:07,672 out of those tools, what do you do? 321 00:09:07,672 --> 00:09:08,798 You say, does the tool do 322 00:09:08,798 --> 00:09:10,174 what my person did before? 323 00:09:10,174 --> 00:09:10,967 And then you get into 324 00:09:10,967 --> 00:09:12,134 this productivity loop. 325 00:09:12,134 --> 00:09:14,554 And unfortunately productivity has a limit. 326 00:09:14,554 --> 00:09:15,972 Like there's only so much value 327 00:09:15,972 --> 00:09:17,390 you can create with productivity. 328 00:09:17,390 --> 00:09:20,268 Growth has no limit associated with it. 329 00:09:20,268 --> 00:09:23,563 So, we see that in order to be successful, 330 00:09:23,563 --> 00:09:24,939 you know, you referred to a playbook 331 00:09:24,939 --> 00:09:25,731 earlier, Molly, 332 00:09:25,731 --> 00:09:26,941 in order to be successful, 333 00:09:26,941 --> 00:09:28,526 it takes three things. 334 00:09:28,526 --> 00:09:29,986 It takes the mindset, 335 00:09:29,986 --> 00:09:32,154 the skill set, and the tool set. 336 00:09:32,154 --> 00:09:32,738 And right now, 337 00:09:32,738 --> 00:09:33,739 most of the investments 338 00:09:33,739 --> 00:09:35,741 have gone towards the tool set. 339 00:09:35,741 --> 00:09:38,286 There's not as much in the mindset 340 00:09:38,286 --> 00:09:40,037 and the skill set. 341 00:09:40,037 --> 00:09:41,706 So, what we see is 342 00:09:41,706 --> 00:09:43,624 enterprise transformation 343 00:09:43,624 --> 00:09:45,376 actually begins with the intent 344 00:09:45,376 --> 00:09:47,128 of how we start to frame the problem, 345 00:09:47,128 --> 00:09:49,922 how we start to look after the objectives 346 00:09:49,922 --> 00:09:51,424 of what we're trying to get out of AI. 347 00:09:51,424 --> 00:09:52,717 Are we just using it to do 348 00:09:52,717 --> 00:09:53,676 what we do today? 349 00:09:53,676 --> 00:09:55,344 Or are we going to reinvent 350 00:09:55,344 --> 00:09:57,179 the entire new way of working? 351 00:09:57,179 --> 00:09:58,472 And that shift is something 352 00:09:58,472 --> 00:10:00,099 that I think we're starting to see over 353 00:10:00,099 --> 00:10:01,350 the last couple of months 354 00:10:01,350 --> 00:10:04,353 of moving away from use cases towards 355 00:10:04,353 --> 00:10:05,896 more of a reinvention agenda. 356 00:10:05,896 --> 00:10:08,649 And so how is the concept 357 00:10:08,649 --> 00:10:10,526 and the introduction of agentic tools 358 00:10:10,526 --> 00:10:12,278 and agentic AI 359 00:10:12,278 --> 00:10:13,571 starting to change this conversation 360 00:10:13,571 --> 00:10:15,072 even more, because it feels to me like 361 00:10:15,072 --> 00:10:16,407 that’s a bit of a gateway drug 362 00:10:16,407 --> 00:10:17,617 to really thinking 363 00:10:17,617 --> 00:10:19,744 about transformation in a different way. 364 00:10:19,744 --> 00:10:20,870 Not just productivity, 365 00:10:20,870 --> 00:10:23,122 but new types of employees. 366 00:10:23,122 --> 00:10:23,664 Yeah. 367 00:10:23,664 --> 00:10:25,833 So, new types of employees. 368 00:10:25,833 --> 00:10:28,669 It’s such an interesting concept. 369 00:10:28,669 --> 00:10:31,380 Like, I think next year will be the first year 370 00:10:31,380 --> 00:10:33,382 that when you work at a company, 371 00:10:33,382 --> 00:10:34,717 you will be a manager, 372 00:10:34,717 --> 00:10:36,052 and you will not just have 373 00:10:36,052 --> 00:10:36,844 a human workforce 374 00:10:36,844 --> 00:10:38,095 in which you're managing. 375 00:10:38,095 --> 00:10:39,430 And, agents 376 00:10:39,430 --> 00:10:40,973 are going to be really responsible 377 00:10:40,973 --> 00:10:42,683 for driving a lot of the 378 00:10:42,683 --> 00:10:43,976 what we call at EY 379 00:10:43,976 --> 00:10:46,270 the toil that nobody wants to do 380 00:10:46,270 --> 00:10:47,229 and to start to drive 381 00:10:47,229 --> 00:10:49,065 a lot of that execution path. 382 00:10:49,065 --> 00:10:52,109 But agents are still subject to the same 383 00:10:52,109 --> 00:10:53,861 statistical sameness 384 00:10:53,861 --> 00:10:54,779 if you use them 385 00:10:54,779 --> 00:10:56,280 to do your critical thinking. 386 00:10:56,280 --> 00:10:58,616 So the real sequence of work 387 00:10:58,616 --> 00:11:01,702 should be human, agent, and then human. 388 00:11:01,702 --> 00:11:03,537 And so for that reason, 389 00:11:03,537 --> 00:11:05,665 I don't really see it changing 390 00:11:05,665 --> 00:11:08,751 the need to really focus on the mindset 391 00:11:08,751 --> 00:11:09,794 and the skill set, 392 00:11:09,794 --> 00:11:11,170 because what companies are going to be 393 00:11:11,170 --> 00:11:13,589 after is driving differentiation 394 00:11:13,589 --> 00:11:15,007 from their competitors 395 00:11:15,007 --> 00:11:17,426 and being able to create new markets. 396 00:11:17,426 --> 00:11:19,345 And, the AI is going to create 397 00:11:19,345 --> 00:11:20,680 the same predictable output 398 00:11:20,680 --> 00:11:22,390 for you as it would for somebody else 399 00:11:22,390 --> 00:11:24,725 if you're not using that context with it. 400 00:11:24,725 --> 00:11:26,977 So how does that progression 401 00:11:26,977 --> 00:11:27,812 that you've described 402 00:11:27,812 --> 00:11:31,857 help companies become Frontier Firms? 403 00:11:31,857 --> 00:11:33,359 You know, transition away 404 00:11:33,359 --> 00:11:35,027 from the way they used to do things? 405 00:11:35,027 --> 00:11:35,486 Yeah. 406 00:11:35,486 --> 00:11:37,613 When it starts with the strategy of 407 00:11:37,613 --> 00:11:39,990 what is it that we want to do 408 00:11:39,990 --> 00:11:42,660 and how do we intend to create value? 409 00:11:42,660 --> 00:11:43,828 What we often say to 410 00:11:43,828 --> 00:11:45,538 our clients is create 411 00:11:45,538 --> 00:11:46,414 a point of view 412 00:11:46,414 --> 00:11:47,456 that you would be comfortable 413 00:11:47,456 --> 00:11:48,958 taking to your investors 414 00:11:48,958 --> 00:11:50,751 on what your strategy would be. 415 00:11:50,751 --> 00:11:52,378 Like, the value that you're creating with 416 00:11:52,378 --> 00:11:54,714 AI is not in your portfolio of things 417 00:11:54,714 --> 00:11:55,798 that you're doing. 418 00:11:55,798 --> 00:11:57,341 I mean, it's good and it's valuable. 419 00:11:57,341 --> 00:11:58,884 It's kind of like going to the gym 420 00:11:58,884 --> 00:12:00,261 if you're trying to run the 421 00:12:00,261 --> 00:12:01,470 the New York Marathon, 422 00:12:01,470 --> 00:12:03,597 like gym work and practice runs, 423 00:12:03,597 --> 00:12:04,181 they're helpful, 424 00:12:04,181 --> 00:12:05,516 but they're not the marathon. 425 00:12:05,516 --> 00:12:08,185 And instead, start to think about 426 00:12:08,185 --> 00:12:09,603 what the main objective is 427 00:12:09,603 --> 00:12:11,021 and where value is going to be created. 428 00:12:11,021 --> 00:12:12,606 And that often manifests itself 429 00:12:12,606 --> 00:12:15,609 in 2 to 3 pages of like just plain text. 430 00:12:15,776 --> 00:12:16,819 When you have that, 431 00:12:16,819 --> 00:12:17,361 that helps 432 00:12:17,361 --> 00:12:19,071 you set the mindset, skill set, 433 00:12:19,071 --> 00:12:20,906 and the tool set objective 434 00:12:20,906 --> 00:12:22,491 because you shift from an approach 435 00:12:22,491 --> 00:12:24,660 of just implementing AI everywhere, 436 00:12:24,660 --> 00:12:25,745 to start to think 437 00:12:25,745 --> 00:12:27,246 my marketing function, 438 00:12:27,246 --> 00:12:28,748 I'm going to completely reinvent 439 00:12:28,748 --> 00:12:30,124 my marketing function. 440 00:12:30,124 --> 00:12:31,125 I'm going to target 441 00:12:31,125 --> 00:12:33,335 not just people, but I'm going to target 442 00:12:33,335 --> 00:12:35,755 being able to market to people’s agents 443 00:12:35,755 --> 00:12:36,338 that are going to buy 444 00:12:36,338 --> 00:12:38,007 the products on their behalf. 445 00:12:38,007 --> 00:12:39,967 And you start to get into 446 00:12:39,967 --> 00:12:41,135 just a different territory 447 00:12:41,135 --> 00:12:42,178 in a different space than where the 448 00:12:42,178 --> 00:12:43,679 narrative has been placed in time. 449 00:12:43,679 --> 00:12:44,555 It's so interesting 450 00:12:44,555 --> 00:12:45,806 as you're describing this, 451 00:12:45,806 --> 00:12:47,349 because it sounds like 452 00:12:47,349 --> 00:12:48,309 that's how you should always 453 00:12:48,309 --> 00:12:49,602 be thinking about business. 454 00:12:50,728 --> 00:12:52,062 But I understand that 455 00:12:52,062 --> 00:12:54,190 when a tool like this comes along, 456 00:12:54,190 --> 00:12:55,065 people can have one of 457 00:12:55,065 --> 00:12:55,941 two responses, right? 458 00:12:55,941 --> 00:12:56,650 One is just like, 459 00:12:56,650 --> 00:12:57,985 we got to put it on everything. 460 00:12:57,985 --> 00:12:59,862 We got to smear some of this 461 00:12:59,862 --> 00:13:01,447 peanut butter and jelly on across 462 00:13:01,447 --> 00:13:02,490 everything that we're doing. 463 00:13:02,490 --> 00:13:04,658 Or we might tiptoe 464 00:13:04,658 --> 00:13:05,826 in with a couple of pilots 465 00:13:05,826 --> 00:13:06,368 and then kind of 466 00:13:06,368 --> 00:13:08,078 wait for other firms to figure it out 467 00:13:08,078 --> 00:13:10,206 and then come in all the way. 468 00:13:10,206 --> 00:13:12,750 And I really hear you describing a third 469 00:13:12,750 --> 00:13:13,834 and better way. 470 00:13:13,834 --> 00:13:16,378 I think the practical reality is 471 00:13:16,378 --> 00:13:17,296 the first two 472 00:13:17,296 --> 00:13:18,964 is what we've seen over the course 473 00:13:18,964 --> 00:13:20,174 of the last three years. 474 00:13:20,174 --> 00:13:21,258 And that's partly 475 00:13:21,258 --> 00:13:23,427 because this is an extremely 476 00:13:23,427 --> 00:13:24,595 powerful technology 477 00:13:24,595 --> 00:13:25,971 that we are still learning 478 00:13:25,971 --> 00:13:26,847 all the right 479 00:13:26,847 --> 00:13:27,890 controls to be able 480 00:13:27,890 --> 00:13:29,433 to put this at scale 481 00:13:29,433 --> 00:13:31,185 inside of organizations. 482 00:13:31,185 --> 00:13:32,853 We at EY have something we call, 483 00:13:32,853 --> 00:13:34,647 we refer to as the blueprint. 484 00:13:34,647 --> 00:13:35,981 So when you shift away 485 00:13:35,981 --> 00:13:37,650 and you think about a function that runs 486 00:13:37,650 --> 00:13:38,692 AI natively 487 00:13:38,692 --> 00:13:39,735 as if you've built it 488 00:13:39,735 --> 00:13:41,987 for the era in which we're in today, 489 00:13:41,987 --> 00:13:44,114 then that's not just a process 490 00:13:44,114 --> 00:13:45,241 that's AI powered. 491 00:13:45,241 --> 00:13:46,659 You have multiple layers, 492 00:13:46,659 --> 00:13:48,828 you have connectivity into the sources 493 00:13:48,828 --> 00:13:50,538 that you engage with today, because 494 00:13:50,538 --> 00:13:52,289 you know, it becomes a big question. 495 00:13:52,289 --> 00:13:53,916 Do you want to change and rip out 496 00:13:53,916 --> 00:13:55,417 everything that you've invested 497 00:13:55,417 --> 00:13:57,211 in from a technology perspective? 498 00:13:57,211 --> 00:13:58,921 But then you have an AI native platform, 499 00:13:58,921 --> 00:14:00,172 you have an intelligence layer, 500 00:14:00,172 --> 00:14:01,549 you have a control layer. 501 00:14:01,549 --> 00:14:03,759 The control layer is actually responsible 502 00:14:03,759 --> 00:14:06,095 for maintaining how much autonomy 503 00:14:06,095 --> 00:14:07,680 do you give these agents? 504 00:14:07,680 --> 00:14:09,139 And, like, simple things like 505 00:14:09,139 --> 00:14:10,391 where do you put the agents? 506 00:14:10,391 --> 00:14:12,434 Do you put the agents in the HR master, 507 00:14:12,434 --> 00:14:13,561 or do you put them in 508 00:14:13,561 --> 00:14:15,062 some other registration? 509 00:14:15,062 --> 00:14:16,605 And what access do they have 510 00:14:16,605 --> 00:14:17,731 to be able to run your business? 511 00:14:17,731 --> 00:14:18,858 And then you start to layer 512 00:14:18,858 --> 00:14:20,109 in the process, 513 00:14:20,109 --> 00:14:22,069 what the new jobs are of the future, 514 00:14:22,069 --> 00:14:23,988 and where and how you create value. 515 00:14:23,988 --> 00:14:25,990 And when you stack that up together, 516 00:14:25,990 --> 00:14:27,408 that is the playbook 517 00:14:27,408 --> 00:14:28,826 for how you become 518 00:14:28,826 --> 00:14:31,412 a much more Frontier-focused business 519 00:14:31,412 --> 00:14:32,913 in the area that you want to, 520 00:14:32,913 --> 00:14:34,832 that you want to start to compete in. 521 00:14:34,832 --> 00:14:37,251 Over time, doing that in different places 522 00:14:37,251 --> 00:14:38,085 allows you to work 523 00:14:38,085 --> 00:14:39,628 towards becoming the Frontier Firm. 524 00:14:39,628 --> 00:14:40,671 When you talk to your clients 525 00:14:40,671 --> 00:14:41,714 about their competition, 526 00:14:41,714 --> 00:14:44,258 is it firms that are moving faster 527 00:14:44,258 --> 00:14:45,634 to become Frontier Firms, 528 00:14:45,634 --> 00:14:47,595 or is it AI-first companies 529 00:14:47,595 --> 00:14:48,846 that are coming up behind them? 530 00:14:48,846 --> 00:14:51,849 I would say that that all, of course 531 00:14:51,849 --> 00:14:53,517 Molly, that depends on the industries 532 00:14:53,517 --> 00:14:54,518 in which we're focused on. 533 00:14:54,518 --> 00:14:57,271 But most of my clients 534 00:14:57,271 --> 00:14:59,106 are really concerned 535 00:14:59,106 --> 00:15:00,399 about the competitors 536 00:15:00,399 --> 00:15:02,693 and the disruptors that they do not see 537 00:15:02,693 --> 00:15:04,528 and they are not competing with today. 538 00:15:04,528 --> 00:15:05,821 It's the AI natives. 539 00:15:05,821 --> 00:15:07,281 I mean, there are many companies 540 00:15:07,281 --> 00:15:09,825 that are 40 or 50 people companies 541 00:15:09,825 --> 00:15:12,286 that have multibillion dollar valuations, 542 00:15:12,286 --> 00:15:13,412 and they are starting to be 543 00:15:13,412 --> 00:15:14,788 a very disruptive force 544 00:15:14,788 --> 00:15:16,582 for established businesses. 545 00:15:16,582 --> 00:15:17,666 And you don't see them. 546 00:15:17,666 --> 00:15:18,876 And then all of a sudden 547 00:15:18,876 --> 00:15:20,794 they are $1 billion company 548 00:15:20,794 --> 00:15:21,837 and starting to really eat 549 00:15:21,837 --> 00:15:23,380 into your business model. 550 00:15:23,380 --> 00:15:25,174 I would say that's driving a majority 551 00:15:25,174 --> 00:15:26,717 of the strategic 552 00:15:26,717 --> 00:15:28,469 imperative inside these organizations. 553 00:15:28,469 --> 00:15:28,844 Yeah. 554 00:15:28,844 --> 00:15:30,137 That's always been 555 00:15:30,137 --> 00:15:31,388 a hard thing to keep up with. 556 00:15:31,388 --> 00:15:32,932 You're kind of trying to imagine 557 00:15:32,932 --> 00:15:34,642 the anatomy of your disruptor 558 00:15:34,642 --> 00:15:37,686 as if it's this, like, shadow box of a person, 559 00:15:37,686 --> 00:15:39,396 or a company. 560 00:15:39,396 --> 00:15:41,273 And it is really challenging. 561 00:15:41,273 --> 00:15:43,233 But what I have seen, 562 00:15:43,233 --> 00:15:44,777 I would say over the last six months 563 00:15:44,777 --> 00:15:46,195 that is quite different now, 564 00:15:46,195 --> 00:15:47,696 is that in the beginning, 565 00:15:47,696 --> 00:15:49,281 everybody at the executive 566 00:15:49,281 --> 00:15:51,075 team needed to know about AI. 567 00:15:51,075 --> 00:15:52,368 So the education sessions, 568 00:15:52,368 --> 00:15:53,786 I referred to those master classes, 569 00:15:53,786 --> 00:15:55,788 those were supported by the executives, 570 00:15:55,788 --> 00:15:57,206 in many cases by the boards. 571 00:15:57,206 --> 00:15:59,333 Then slowly, it became a technology thing, 572 00:15:59,333 --> 00:16:00,209 where it became 573 00:16:00,209 --> 00:16:01,710 the responsibility of the CIO 574 00:16:01,710 --> 00:16:02,795 or the CTO to be able 575 00:16:02,795 --> 00:16:04,922 to scale out the technology. 576 00:16:04,922 --> 00:16:05,589 As we start 577 00:16:05,589 --> 00:16:07,675 to get more into mindset, skill set, 578 00:16:07,675 --> 00:16:10,886 being really needed investment 579 00:16:10,886 --> 00:16:12,680 buckets to balance out, 580 00:16:12,680 --> 00:16:14,890 you know, the true transformative power. 581 00:16:14,890 --> 00:16:15,891 It seems to be something 582 00:16:15,891 --> 00:16:18,143 that is going back up to the CEO 583 00:16:18,143 --> 00:16:20,813 and the executive leaders in the company 584 00:16:20,813 --> 00:16:22,189 to start to set the vision 585 00:16:22,189 --> 00:16:23,357 and the strategy. 586 00:16:23,357 --> 00:16:25,317 So, that natural progression, you know, 587 00:16:25,317 --> 00:16:26,944 we tend to overestimate things 588 00:16:26,944 --> 00:16:27,569 in the short term 589 00:16:27,569 --> 00:16:29,029 and underestimate them in the long term. 590 00:16:29,029 --> 00:16:29,905 Like perhaps 591 00:16:29,905 --> 00:16:30,572 that is what 592 00:16:30,572 --> 00:16:32,116 we should have predicted over time. 593 00:16:32,116 --> 00:16:33,784 But we do feel there's an inflection 594 00:16:33,784 --> 00:16:34,535 point happening 595 00:16:34,535 --> 00:16:36,286 where companies are starting to revisit 596 00:16:36,286 --> 00:16:37,621 the way they're thinking about AI 597 00:16:37,621 --> 00:16:38,789 in their organizations. 598 00:16:38,789 --> 00:16:39,832 Interesting. 599 00:16:39,832 --> 00:16:41,250 Before we move off of that, 600 00:16:41,250 --> 00:16:42,334 what are some of the benefits 601 00:16:42,334 --> 00:16:44,420 that a legacy firm 602 00:16:44,420 --> 00:16:46,088 can bring to this conversation? 603 00:16:46,088 --> 00:16:46,922 Like, you know, 604 00:16:46,922 --> 00:16:48,340 we should not assume 605 00:16:48,340 --> 00:16:50,801 that every company will be disrupted 606 00:16:50,801 --> 00:16:53,220 by a brand new AI native company. 607 00:16:53,220 --> 00:16:55,806 Are there things that are built-in benefits 608 00:16:55,806 --> 00:16:56,557 for a company 609 00:16:56,557 --> 00:16:57,683 that's been around for a long time? 610 00:16:57,683 --> 00:16:58,559 Maybe their data set, 611 00:16:58,559 --> 00:17:00,686 maybe, you know, their context? 612 00:17:00,686 --> 00:17:01,061 Yeah. 613 00:17:01,061 --> 00:17:03,147 I mean, I think really what it comes down 614 00:17:03,147 --> 00:17:06,567 to is their scale in a lot of ways. 615 00:17:07,067 --> 00:17:08,777 You know, organizations 616 00:17:08,777 --> 00:17:10,154 I've seen, you know, compete 617 00:17:10,154 --> 00:17:12,197 against some of these AI native startups, 618 00:17:12,197 --> 00:17:13,449 the AI native startups 619 00:17:13,449 --> 00:17:14,950 don't like the messiness, 620 00:17:14,950 --> 00:17:16,702 which is a corporate reality. 621 00:17:16,702 --> 00:17:17,911 Many of these companies 622 00:17:17,911 --> 00:17:19,413 have learned in B2B 623 00:17:19,413 --> 00:17:20,873 constructs, have learned to be able 624 00:17:20,873 --> 00:17:22,791 to sell to an enterprise, 625 00:17:22,791 --> 00:17:24,376 to be able to take technology 626 00:17:24,376 --> 00:17:26,712 to a complex organization. 627 00:17:26,712 --> 00:17:28,547 I’d say that the data flywheel 628 00:17:28,547 --> 00:17:30,049 inside of organizations 629 00:17:30,049 --> 00:17:31,967 is critically important, 630 00:17:31,967 --> 00:17:34,470 because that organizational nuance 631 00:17:34,470 --> 00:17:37,139 and context is what drives differentiation 632 00:17:37,139 --> 00:17:39,391 from just using a general-purpose model. 633 00:17:39,391 --> 00:17:40,809 And then I'd say also it's 634 00:17:40,809 --> 00:17:42,561 the customer reach and contracts. 635 00:17:42,561 --> 00:17:43,395 You know, often 636 00:17:43,395 --> 00:17:44,605 these are incredible 637 00:17:44,605 --> 00:17:46,398 endowments inside of organizations 638 00:17:46,398 --> 00:17:48,650 that really are 639 00:17:48,650 --> 00:17:51,236 the points that allow them to be able 640 00:17:51,236 --> 00:17:52,905 to kind of move into a new market. 641 00:17:52,905 --> 00:17:54,490 Like, there are many 642 00:17:54,490 --> 00:17:56,784 multi-conglomerate technology companies 643 00:17:56,784 --> 00:17:58,118 and some of them find that 644 00:17:58,118 --> 00:18:01,246 their most valuable asset in the AI space 645 00:18:01,538 --> 00:18:03,916 are the game consoles that they have, 646 00:18:03,916 --> 00:18:07,419 and the following of consumers 647 00:18:07,753 --> 00:18:09,004 engaging in gaming 648 00:18:09,004 --> 00:18:10,380 on their game consoles, 649 00:18:10,380 --> 00:18:11,632 because that implicitly 650 00:18:11,632 --> 00:18:12,758 has this community 651 00:18:12,758 --> 00:18:14,760 that can become the flywheel 652 00:18:14,760 --> 00:18:16,637 in which you introduce AI innovation. 653 00:18:16,637 --> 00:18:18,138 Let's talk about employees, 654 00:18:18,138 --> 00:18:19,014 because so far 655 00:18:19,014 --> 00:18:20,557 we've talked about leaders, 656 00:18:20,557 --> 00:18:23,060 and this is a leadership challenge, 657 00:18:23,060 --> 00:18:24,144 bringing employees along. 658 00:18:24,144 --> 00:18:26,688 EY has launched an initiative to upskill 659 00:18:26,688 --> 00:18:30,150 tens of thousands of professionals in AI. 660 00:18:30,150 --> 00:18:31,485 Talk about how important this is 661 00:18:31,485 --> 00:18:33,946 and how you get it done in organizations. 662 00:18:33,946 --> 00:18:36,240 Yeah, this is something that is 663 00:18:36,240 --> 00:18:37,866 as we are a people-based business 664 00:18:37,866 --> 00:18:40,160 and we will be a people-based business, 665 00:18:40,160 --> 00:18:41,120 this is something 666 00:18:41,120 --> 00:18:42,955 that is of critical importance 667 00:18:42,955 --> 00:18:44,790 to us in our organization. 668 00:18:44,790 --> 00:18:48,043 I'll speak for our consulting organization. 669 00:18:48,043 --> 00:18:50,879 Last year, we built a full curriculum 670 00:18:50,879 --> 00:18:53,382 for all of our employees at EY 671 00:18:53,382 --> 00:18:55,342 to get introduced, 672 00:18:55,342 --> 00:18:56,552 to get the foundations, 673 00:18:56,552 --> 00:18:57,803 but then to start to teach 674 00:18:57,803 --> 00:19:00,806 AI to them in the context of their jobs. 675 00:19:00,973 --> 00:19:03,559 And I referred to using AI 676 00:19:03,559 --> 00:19:05,394 to move into a creator-based economy 677 00:19:05,394 --> 00:19:07,646 and to be able to do what's 678 00:19:07,646 --> 00:19:09,648 what's not possible in AI itself. 679 00:19:09,648 --> 00:19:11,859 We call that the “power of the and.” 680 00:19:11,859 --> 00:19:14,444 So, we’re working on teaching our people 681 00:19:14,444 --> 00:19:16,363 how to find their “and.” 682 00:19:16,363 --> 00:19:18,198 How to take their deep 683 00:19:18,198 --> 00:19:20,117 domain expertise and turn that 684 00:19:20,117 --> 00:19:22,327 into a strategic differentiator 685 00:19:22,327 --> 00:19:24,163 in the way that they engage with AI 686 00:19:24,163 --> 00:19:25,664 to create unique content. 687 00:19:25,664 --> 00:19:26,874 So we rolled out this out 688 00:19:26,874 --> 00:19:27,541 to all of our people, 689 00:19:27,666 --> 00:19:29,376 and we feel really good about it 690 00:19:29,376 --> 00:19:32,254 because we've seen our employee 691 00:19:32,254 --> 00:19:33,922 engagement scores go up 692 00:19:33,922 --> 00:19:35,174 as a result of that. 693 00:19:35,174 --> 00:19:37,217 We feel that people feel more in 694 00:19:37,217 --> 00:19:38,051 the driver's seat 695 00:19:38,051 --> 00:19:40,095 of how they can start to shape AI, 696 00:19:40,095 --> 00:19:42,181 as opposed to have I happen to them. 697 00:19:42,181 --> 00:19:43,682 So it's been an investment 698 00:19:43,682 --> 00:19:44,892 that we will continue to make 699 00:19:44,892 --> 00:19:45,726 and all of our people 700 00:19:45,726 --> 00:19:47,394 across the organization every year. 701 00:19:47,394 --> 00:19:48,770 This is such a great point 702 00:19:48,770 --> 00:19:49,396 that you're bringing up, 703 00:19:49,396 --> 00:19:52,316 because there can be a lot of built-in 704 00:19:52,649 --> 00:19:55,277 resistance or skepticism or concern. 705 00:19:55,277 --> 00:19:56,403 You know, 706 00:19:56,403 --> 00:19:57,237 we would be lying 707 00:19:57,237 --> 00:19:58,488 if we said that didn't exist 708 00:19:58,488 --> 00:19:59,656 within organizations. 709 00:19:59,656 --> 00:20:02,034 And it really is a leadership challenge 710 00:20:02,034 --> 00:20:05,579 to champion this, to do it in partnership 711 00:20:05,579 --> 00:20:06,788 with your employees. 712 00:20:06,788 --> 00:20:08,415 Yeah, we run this poll 713 00:20:08,415 --> 00:20:09,833 asking employees 714 00:20:09,833 --> 00:20:11,585 how engaged they are, and how much 715 00:20:11,585 --> 00:20:14,588 they're getting what they need from AI. 716 00:20:14,588 --> 00:20:16,673 Recently, about 85% of them 717 00:20:16,673 --> 00:20:17,841 said they were really excited 718 00:20:17,841 --> 00:20:20,260 for agentic AI, but 86% of them 719 00:20:20,260 --> 00:20:22,012 said they had to learn it on their own. 720 00:20:22,012 --> 00:20:22,846 Most of their learning 721 00:20:22,846 --> 00:20:23,847 was happening on their own. 722 00:20:23,847 --> 00:20:25,557 This is not EY specific. 723 00:20:25,557 --> 00:20:28,227 This is broadly across workers. 724 00:20:28,227 --> 00:20:30,979 So, in order to really engage with people, 725 00:20:30,979 --> 00:20:32,231 you need to have a strategy 726 00:20:32,231 --> 00:20:34,191 with clear intent, which is, 727 00:20:34,191 --> 00:20:36,026 I think, more of a growth strategy 728 00:20:36,026 --> 00:20:37,778 than a productivity strategy. 729 00:20:37,778 --> 00:20:39,529 You need to have the right investments 730 00:20:39,529 --> 00:20:42,282 in helping people develop those skills 731 00:20:42,282 --> 00:20:43,617 and give them the opportunity 732 00:20:43,617 --> 00:20:45,202 and the tooling to be able to 733 00:20:45,202 --> 00:20:47,037 to build that muscle. 734 00:20:47,037 --> 00:20:48,830 And then I think, you have to address 735 00:20:48,830 --> 00:20:50,666 the fact that this is going to be 736 00:20:50,666 --> 00:20:53,627 an ever-going cycle of change. 737 00:20:53,627 --> 00:20:55,462 And, like, change agility 738 00:20:55,462 --> 00:20:57,631 and investing in building out 739 00:20:57,631 --> 00:20:59,800 that muscle is critically important 740 00:20:59,800 --> 00:21:01,426 and something that, you know, I'd say 741 00:21:01,426 --> 00:21:03,136 we're still tackling inside of EY. 742 00:21:03,136 --> 00:21:04,221 How do you communicate that 743 00:21:04,221 --> 00:21:05,555 to leaders at other companies? 744 00:21:05,555 --> 00:21:07,557 That “You may bring them along” to 745 00:21:07,557 --> 00:21:08,850 “You need to start with your strategy 746 00:21:08,850 --> 00:21:09,977 and your desired outcomes 747 00:21:09,977 --> 00:21:12,271 and really go deep on the functions 748 00:21:12,271 --> 00:21:13,605 that you want to change, 749 00:21:13,605 --> 00:21:15,607 but don't leave your employees behind.” 750 00:21:15,607 --> 00:21:17,359 Yeah, I mean, this is the story 751 00:21:17,359 --> 00:21:20,237 of 2025 right now with AI. 752 00:21:20,237 --> 00:21:23,740 It's how do we create more as opposed to, 753 00:21:23,740 --> 00:21:25,909 you know, try to use AI to do the same, 754 00:21:25,909 --> 00:21:26,994 but with less? 755 00:21:26,994 --> 00:21:28,954 What we often do inside of EY 756 00:21:28,954 --> 00:21:30,455 is we believe that, you know, 757 00:21:30,455 --> 00:21:31,957 we can talk all we want 758 00:21:31,957 --> 00:21:33,875 about what a company should do, 759 00:21:33,875 --> 00:21:35,127 but we need to be able to walk 760 00:21:35,127 --> 00:21:36,378 the talk as well. 761 00:21:36,378 --> 00:21:37,713 And we've invested in something 762 00:21:37,713 --> 00:21:39,965 we call our Client Zero Program, 763 00:21:39,965 --> 00:21:42,050 which is where we are doing this 764 00:21:42,050 --> 00:21:43,260 to ourselves first 765 00:21:43,260 --> 00:21:45,137 and then showing our clients 766 00:21:45,137 --> 00:21:47,389 what's worked and what hasn't worked. 767 00:21:47,389 --> 00:21:48,724 And that has been 768 00:21:48,724 --> 00:21:49,975 a really effective tool 769 00:21:49,975 --> 00:21:51,768 of being able to really drive that. 770 00:21:51,768 --> 00:21:52,936 I think the second is 771 00:21:52,936 --> 00:21:54,896 when you can come in with a blueprint, 772 00:21:54,896 --> 00:21:56,064 these, these blueprints 773 00:21:56,064 --> 00:21:57,357 I was referring to say, 774 00:21:57,357 --> 00:21:59,276 this is how you can create value 775 00:21:59,276 --> 00:22:00,986 in an AI native way, 776 00:22:00,986 --> 00:22:02,487 then you automatically shift 777 00:22:02,487 --> 00:22:03,447 to the growth agenda 778 00:22:03,447 --> 00:22:04,614 as opposed to just focusing 779 00:22:04,614 --> 00:22:06,033 on the productivity agenda. 780 00:22:06,033 --> 00:22:07,617 What can you tell us about what has 781 00:22:07,617 --> 00:22:08,910 worked and what hasn't worked? 782 00:22:08,910 --> 00:22:11,204 Okay, so, inside of EY? 783 00:22:11,204 --> 00:22:12,247 Yeah. 784 00:22:12,247 --> 00:22:13,749 So, I'd say at EY 785 00:22:13,749 --> 00:22:14,666 We won't tell anybody. 786 00:22:14,666 --> 00:22:15,625 Don't tell anyone. 787 00:22:15,625 --> 00:22:16,001 No. 788 00:22:16,001 --> 00:22:17,085 Please. This is off the record. 789 00:22:17,085 --> 00:22:17,794 Just between us. 790 00:22:17,794 --> 00:22:18,754 Yes. Okay. 791 00:22:18,754 --> 00:22:20,422 So, in that case, 792 00:22:20,422 --> 00:22:22,174 I think we've done a really good job 793 00:22:22,174 --> 00:22:23,633 with our leadership buy-in 794 00:22:23,633 --> 00:22:24,885 and engagement. 795 00:22:24,885 --> 00:22:26,094 You know, our leaders, 796 00:22:26,094 --> 00:22:28,138 our CEO is very active 797 00:22:28,138 --> 00:22:30,932 in driving and shaping our AI agenda. 798 00:22:30,932 --> 00:22:33,685 Her direct report is responsible 799 00:22:33,685 --> 00:22:35,812 for leading all of the programs 800 00:22:35,812 --> 00:22:36,480 that we're doing 801 00:22:36,480 --> 00:22:38,315 all across our service lines. 802 00:22:38,315 --> 00:22:39,608 And we've cascaded 803 00:22:39,608 --> 00:22:41,276 that down into priorities 804 00:22:41,276 --> 00:22:43,362 for every geography around the world. 805 00:22:43,362 --> 00:22:45,822 So I think leadership buy-in 806 00:22:45,822 --> 00:22:47,616 the investments that we're making 807 00:22:47,616 --> 00:22:50,202 in people, in process, in technology. 808 00:22:50,202 --> 00:22:51,912 Like last year, we've invested over 809 00:22:51,912 --> 00:22:53,246 a billion dollars of capital 810 00:22:53,246 --> 00:22:54,998 into getting ourselves ready 811 00:22:54,998 --> 00:22:56,958 to become that Frontier Firm. 812 00:22:58,168 --> 00:23:00,712 The challenging part that you asked for, 813 00:23:00,712 --> 00:23:02,756 I'd say, you know, and this is 814 00:23:02,756 --> 00:23:04,674 this is not unique to EY, 815 00:23:04,674 --> 00:23:06,760 but this is a massive 816 00:23:06,760 --> 00:23:09,763 and fundamental change of the business. 817 00:23:09,971 --> 00:23:12,516 For us, we are a business model 818 00:23:12,516 --> 00:23:14,601 that has been built on the billable hour, 819 00:23:14,601 --> 00:23:17,396 where people monetize their efforts. 820 00:23:17,396 --> 00:23:18,522 The harder the problem, 821 00:23:18,522 --> 00:23:19,898 the harder you have to work, 822 00:23:19,898 --> 00:23:20,899 the more you get paid 823 00:23:20,899 --> 00:23:22,526 for that particular problem. 824 00:23:22,526 --> 00:23:25,445 And we are going to, through AI, 825 00:23:25,445 --> 00:23:27,322 start to break that business model, 826 00:23:27,322 --> 00:23:29,366 but it fundamentally changes 827 00:23:29,366 --> 00:23:30,992 how we price our services 828 00:23:30,992 --> 00:23:32,702 and how we value our services. 829 00:23:32,702 --> 00:23:33,745 And it's not just us 830 00:23:33,745 --> 00:23:34,871 that needs to change, 831 00:23:34,871 --> 00:23:36,957 it's also the clients that are going to buy 832 00:23:36,957 --> 00:23:38,291 our services in the future 833 00:23:38,291 --> 00:23:39,084 need to be along with 834 00:23:39,084 --> 00:23:40,544 with us for that journey. 835 00:23:40,544 --> 00:23:43,380 So that kind of change management, 836 00:23:43,380 --> 00:23:45,715 change agility and breaking down 837 00:23:45,715 --> 00:23:48,718 the muscle memory of, you know, 838 00:23:48,718 --> 00:23:51,179 being in a business for decades 839 00:23:51,179 --> 00:23:53,223 under a consistent business model 840 00:23:53,223 --> 00:23:54,808 is something that I would say 841 00:23:54,808 --> 00:23:56,017 is the biggest challenge 842 00:23:56,017 --> 00:23:57,310 that we are facing, 843 00:23:57,310 --> 00:23:58,895 but it's something that is critical 844 00:23:58,895 --> 00:24:01,273 for our long-term thriving with AI. 845 00:24:01,273 --> 00:24:03,775 For leaders who want to start 846 00:24:04,151 --> 00:24:06,319 or maybe accelerate their organization’s 847 00:24:06,319 --> 00:24:07,696 AI transformation, 848 00:24:07,696 --> 00:24:09,823 what are some concrete places 849 00:24:09,823 --> 00:24:10,991 that they can begin? 850 00:24:10,991 --> 00:24:12,284 Like, where do you start? 851 00:24:12,284 --> 00:24:13,452 Yeah, look at where 852 00:24:13,452 --> 00:24:15,036 the company creates value 853 00:24:15,036 --> 00:24:16,872 inside the organization today. 854 00:24:16,872 --> 00:24:19,082 I would say it's a value-based story. 855 00:24:19,082 --> 00:24:20,709 It needs to be about growth. 856 00:24:20,709 --> 00:24:21,877 Start in those areas. 857 00:24:21,877 --> 00:24:22,669 So for many 858 00:24:22,669 --> 00:24:24,254 consumer product-based companies 859 00:24:24,254 --> 00:24:26,047 that'll be, what products do you build 860 00:24:26,047 --> 00:24:27,841 and make inside your organization? 861 00:24:27,841 --> 00:24:29,050 And that'll put you down a path 862 00:24:29,050 --> 00:24:30,719 of looking at AI to do product 863 00:24:30,719 --> 00:24:32,471 innovation and R&D, 864 00:24:32,471 --> 00:24:34,014 and to be able to help the sales 865 00:24:34,014 --> 00:24:35,098 and marketing function 866 00:24:35,098 --> 00:24:36,766 or the supply chain function. 867 00:24:36,766 --> 00:24:38,810 If you're in a banking function, 868 00:24:38,810 --> 00:24:39,811 it becomes 869 00:24:39,811 --> 00:24:40,979 a little bit of a different story. 870 00:24:40,979 --> 00:24:43,023 Oil and gas is a different story. 871 00:24:43,023 --> 00:24:44,232 So I'd say it's 872 00:24:44,232 --> 00:24:45,817 a very sector specific story of 873 00:24:45,817 --> 00:24:47,652 think about where you create value. 874 00:24:47,652 --> 00:24:48,695 I know you're going to say that 875 00:24:48,695 --> 00:24:50,739 I'm giving you like an easy answer 876 00:24:50,739 --> 00:24:52,032 and I'm not getting specific enough. 877 00:24:52,032 --> 00:24:52,866 Well, I have an idea 878 00:24:52,866 --> 00:24:53,992 about how we can drill down. 879 00:24:53,992 --> 00:24:55,368 I wonder, is there a temptation 880 00:24:55,368 --> 00:24:56,995 for companies to start 881 00:24:56,995 --> 00:24:58,079 with an underperforming 882 00:24:58,079 --> 00:24:58,914 part of the business, 883 00:24:58,914 --> 00:25:00,999 because that might feel a little bit safer? 884 00:25:00,999 --> 00:25:02,834 Like, are you sort of saying, listen, 885 00:25:02,834 --> 00:25:03,668 go up the gut, 886 00:25:03,668 --> 00:25:05,045 take the thing that you already do 887 00:25:05,045 --> 00:25:06,129 the best and try to figure out 888 00:25:06,129 --> 00:25:07,088 how you can make it better? 889 00:25:07,088 --> 00:25:09,257 Yeah, that that is a great way to say it. 890 00:25:10,258 --> 00:25:11,635 In a lot of ways, 891 00:25:11,635 --> 00:25:13,595 what we see is organizations 892 00:25:13,595 --> 00:25:15,138 wanting to test it out 893 00:25:15,138 --> 00:25:17,557 by experimenting in their back office. 894 00:25:17,557 --> 00:25:18,517 And then when you do that, 895 00:25:18,517 --> 00:25:19,267 you get into this 896 00:25:19,267 --> 00:25:20,685 like cost out productivity. 897 00:25:20,685 --> 00:25:23,688 AI is going to show returns on its P&L 898 00:25:23,897 --> 00:25:26,233 by driving down costs. 899 00:25:26,900 --> 00:25:27,943 I think, you know, 900 00:25:27,943 --> 00:25:29,528 the strategic companies that we see, 901 00:25:29,528 --> 00:25:30,278 they are taking on 902 00:25:30,278 --> 00:25:31,821 challenging business questions 903 00:25:31,821 --> 00:25:33,365 that are existential to their 904 00:25:33,365 --> 00:25:34,824 business strategy, 905 00:25:34,824 --> 00:25:36,201 And they're using that to start 906 00:25:36,201 --> 00:25:37,619 to power their business. 907 00:25:37,619 --> 00:25:40,747 And I think getting to a 2 or 3 page 908 00:25:40,747 --> 00:25:42,624 reinvention of a function 909 00:25:42,624 --> 00:25:45,252 agenda is an easy and tangible way— 910 00:25:45,252 --> 00:25:46,378 well, I shouldn't say easy. 911 00:25:46,378 --> 00:25:47,045 I was going to say. 912 00:25:47,045 --> 00:25:48,964 Sounds like an easy thing to do, 913 00:25:48,964 --> 00:25:51,258 but it is an objective 914 00:25:51,258 --> 00:25:52,968 target that you can set 915 00:25:52,968 --> 00:25:54,970 that allows you to start to push 916 00:25:54,970 --> 00:25:56,888 and move that mindset shift 917 00:25:56,888 --> 00:25:58,181 in the organization, 918 00:25:58,181 --> 00:26:01,268 that this is not about just doing AI, but 919 00:26:01,268 --> 00:26:04,271 it's about changing how we work with AI. 920 00:26:04,604 --> 00:26:06,481 And then if you are an employee, 921 00:26:06,481 --> 00:26:08,567 for employees who want to thrive in 922 00:26:08,567 --> 00:26:09,985 an AI-first workplace, 923 00:26:10,986 --> 00:26:11,903 even if they have been 924 00:26:11,903 --> 00:26:13,822 mandated to upskill. 925 00:26:13,989 --> 00:26:16,074 What are some of the things 926 00:26:16,074 --> 00:26:17,742 that they should focus on right now? 927 00:26:17,742 --> 00:26:19,536 This is probably 928 00:26:19,536 --> 00:26:23,748 the biggest revolution of management 929 00:26:23,957 --> 00:26:27,043 that has ever happened in our society. 930 00:26:27,043 --> 00:26:29,170 And these are really big, bold words. 931 00:26:29,170 --> 00:26:32,507 But, the corporate ladder used to be 932 00:26:32,507 --> 00:26:34,134 that you took a job 933 00:26:34,134 --> 00:26:36,386 and you worked hard by building 934 00:26:36,386 --> 00:26:37,762 credibility and experience. 935 00:26:37,762 --> 00:26:38,888 And ultimately 936 00:26:38,888 --> 00:26:40,181 if you did that really well, 937 00:26:40,181 --> 00:26:41,474 you became a manager. 938 00:26:41,474 --> 00:26:44,102 And then you managed and oversaw people. 939 00:26:44,102 --> 00:26:45,854 And today, the corporate ladder 940 00:26:45,854 --> 00:26:48,440 is being completely kicked over. 941 00:26:48,440 --> 00:26:50,525 People that will join companies 942 00:26:50,525 --> 00:26:53,528 next year will be managers on day one. 943 00:26:53,528 --> 00:26:55,572 They will just be managing a workforce 944 00:26:55,572 --> 00:26:57,699 that is an agentic-based workforce, 945 00:26:57,699 --> 00:26:59,242 one that is extremely powerful 946 00:26:59,242 --> 00:27:00,869 and sometimes clumsy. 947 00:27:00,869 --> 00:27:01,620 And they'll have to have 948 00:27:01,620 --> 00:27:02,787 the requisite skills 949 00:27:02,787 --> 00:27:04,748 to be able to do that 950 00:27:04,748 --> 00:27:06,625 technological management. 951 00:27:06,625 --> 00:27:08,960 So that's where I get into those four 952 00:27:08,960 --> 00:27:10,378 that I described earlier. 953 00:27:10,378 --> 00:27:12,088 I think that really requires 954 00:27:12,088 --> 00:27:13,506 that critical thinking, 955 00:27:13,506 --> 00:27:14,924 that creativity, 956 00:27:14,924 --> 00:27:16,384 that systems thinking 957 00:27:16,384 --> 00:27:18,094 and the domain expertise 958 00:27:18,094 --> 00:27:19,012 to make that happen. 959 00:27:19,012 --> 00:27:20,722 And I'll just add a fifth one in here 960 00:27:20,722 --> 00:27:22,349 because it feels right. 961 00:27:22,349 --> 00:27:26,394 But there's got to be a real structured 962 00:27:26,394 --> 00:27:28,313 and a real investment 963 00:27:28,313 --> 00:27:30,982 in developing the delegation skills. 964 00:27:30,982 --> 00:27:33,610 Because giving agents instructions 965 00:27:33,610 --> 00:27:35,320 to be able to go do the work, 966 00:27:35,320 --> 00:27:36,738 and then critically evaluating 967 00:27:36,738 --> 00:27:38,073 if that happened in the appropriate 968 00:27:38,073 --> 00:27:39,282 way is critical 969 00:27:39,282 --> 00:27:41,117 for how a worker can thrive 970 00:27:41,117 --> 00:27:42,911 by being able to accomplish much more 971 00:27:42,911 --> 00:27:43,953 than what they'd be without 972 00:27:43,953 --> 00:27:45,497 what was possible yesterday. 973 00:27:45,497 --> 00:27:47,374 This is just partly me 974 00:27:47,374 --> 00:27:48,208 and how I like to work, 975 00:27:48,208 --> 00:27:49,834 but this sounds like a workplace 976 00:27:49,834 --> 00:27:51,169 I would want to be a part of. 977 00:27:51,169 --> 00:27:52,003 As opposed to, like, I'm 978 00:27:52,003 --> 00:27:53,213 you know, I'm an entry level worker 979 00:27:53,213 --> 00:27:53,880 who's going to come in 980 00:27:53,880 --> 00:27:55,465 and do a bunch of rote skills 981 00:27:55,465 --> 00:27:57,008 and regurgitate things. 982 00:27:57,008 --> 00:27:58,927 To be able to come in and say, 983 00:27:58,927 --> 00:28:00,637 have creative thinking, right? 984 00:28:00,637 --> 00:28:03,181 Have critical thinking skills, 985 00:28:03,181 --> 00:28:06,184 set strategy for an agent. 986 00:28:06,434 --> 00:28:07,894 It seems like a good story. 987 00:28:07,894 --> 00:28:09,270 I think there's a lot of upside. 988 00:28:09,270 --> 00:28:11,439 I mean, really, at the end of the day, 989 00:28:11,439 --> 00:28:12,816 I think this technology 990 00:28:12,816 --> 00:28:15,777 will start to power a new economy 991 00:28:15,777 --> 00:28:17,028 just like the internet did. 992 00:28:17,028 --> 00:28:18,029 You know, at first 993 00:28:18,029 --> 00:28:19,739 when the internet first came along, 994 00:28:19,739 --> 00:28:21,116 we were really worried 995 00:28:21,116 --> 00:28:22,283 that it was going to replace 996 00:28:22,283 --> 00:28:23,576 all the mail carriers. 997 00:28:23,576 --> 00:28:24,786 And then it created 998 00:28:24,786 --> 00:28:26,788 trillion-dollar businesses. 999 00:28:26,788 --> 00:28:27,747 It's hard to know 1000 00:28:27,747 --> 00:28:29,165 exactly what those businesses 1001 00:28:29,165 --> 00:28:30,208 are going to be, 1002 00:28:30,208 --> 00:28:31,668 but I know those businesses 1003 00:28:31,668 --> 00:28:33,336 will be created by people 1004 00:28:33,336 --> 00:28:34,087 that have learned 1005 00:28:34,087 --> 00:28:36,548 how to scale their impact 1006 00:28:36,548 --> 00:28:39,342 and their creative thinking by using AI. 1007 00:28:39,342 --> 00:28:41,636 In any technological revolution, 1008 00:28:41,636 --> 00:28:43,263 there's always in the beginning, 1009 00:28:43,263 --> 00:28:45,515 first fear and then reinvention. 1010 00:28:45,515 --> 00:28:47,142 And I think we're just coming out of 1011 00:28:47,142 --> 00:28:48,476 that fear phase right now. 1012 00:28:48,476 --> 00:28:49,227 Dan Diasio, 1013 00:28:49,227 --> 00:28:50,770 thank you so much for the time today. 1014 00:28:50,770 --> 00:28:51,604 It's my pleasure. 1015 00:28:51,604 --> 00:28:52,522 Thank you. 1016 00:28:52,522 --> 00:28:54,190 For more conversations like this one, 1017 00:28:54,190 --> 00:28:54,983 follow the show 1018 00:28:54,983 --> 00:28:56,276 and find every episode 1019 00:28:56,276 --> 00:28:58,486 at Microsoft.com/worklab. 1020 00:28:58,486 --> 00:28:59,821 I'm your host, Molly Wood. 1021 00:28:59,821 --> 00:29:00,739 Thank you for listening. 1022 00:29:01,698 --> 00:29:03,199 If you've got a question or a comment, 1023 00:29:03,199 --> 00:29:04,117 drop us an email 1024 00:29:04,117 --> 00:29:06,244 at worklab@microsoft.com 1025 00:29:06,244 --> 00:29:06,828 and check out 1026 00:29:06,828 --> 00:29:07,579 Microsoft's Work 1027 00:29:07,579 --> 00:29:09,247 Trend Indexes and the WorkLab 1028 00:29:09,247 --> 00:29:10,582 digital publication, 1029 00:29:10,582 --> 00:29:11,166 where you'll find 1030 00:29:11,166 --> 00:29:12,834 all of our past episodes, 1031 00:29:12,834 --> 00:29:14,294 along with thoughtful stories 1032 00:29:14,294 --> 00:29:15,003 that explore 1033 00:29:15,003 --> 00:29:16,838 how business leaders are thriving in 1034 00:29:16,838 --> 00:29:18,089 today's AI era. 1035 00:29:18,089 --> 00:29:19,674 You can find all of that 1036 00:29:19,674 --> 00:29:21,926 at Microsoft.com/worklab. 1037 00:29:21,926 --> 00:29:23,094 As for this podcast, 1038 00:29:23,094 --> 00:29:24,721 please rate us, review us, 1039 00:29:24,721 --> 00:29:26,055 follow us wherever you listen. 1040 00:29:26,055 --> 00:29:28,183 It helps us out a ton. 1041 00:29:28,183 --> 00:29:30,143 The WorkLab Podcast is a place for experts 1042 00:29:30,143 --> 00:29:32,270 to share their insights and opinions. 1043 00:29:32,270 --> 00:29:33,104 As students 1044 00:29:33,104 --> 00:29:33,897 of the future of work, 1045 00:29:33,897 --> 00:29:34,856 Microsoft values 1046 00:29:34,856 --> 00:29:37,108 inputs from a diverse set of voices. 1047 00:29:37,108 --> 00:29:38,276 That said, the opinions 1048 00:29:38,276 --> 00:29:40,403 and findings of our guests are their own, 1049 00:29:40,403 --> 00:29:41,070 and they may not 1050 00:29:41,070 --> 00:29:42,447 necessarily reflect Microsoft's 1051 00:29:42,447 --> 00:29:44,908 own research or positions. 1052 00:29:44,908 --> 00:29:46,576 WorkLab is produced by Microsoft 1053 00:29:46,576 --> 00:29:47,577 with Trifilm. 1054 00:29:47,577 --> 00:29:48,369 Sharon Kallander 1055 00:29:48,369 --> 00:29:49,454 and Matthew Duncan produce 1056 00:29:49,454 --> 00:29:51,456 the podcast with editorial support 1057 00:29:51,456 --> 00:29:52,707 from Jon Ellenberg. 1058 00:29:52,707 --> 00:29:55,043 Jessica Voelker is the WorkLab editor.