Transform your strategic vision in the age of AI

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WEBVTT 1 00:00:00.315 --> 00:00:01.925 [Carolyn Goerner] Well, let me start with an overview. 2 00:00:02.555 --> 00:00:04.685 Tell us what this Leading with AI: 3 00:00:05.325 --> 00:00:06.805 Strategy course is all about. 4 00:00:07.295 --> 00:00:09.805 [Will Geoghegan] [Irish accent] Great question. So I'm particularly excited about this 5 00:00:09.805 --> 00:00:13.925 course mainly because I've been teaching strategy for 15 6 00:00:13.985 --> 00:00:18.045 or 20 years, and now with the addition of generative AI, 7 00:00:18.195 --> 00:00:22.005 it's made strategy so much more exciting and fun 8 00:00:22.425 --> 00:00:24.645 and engaging and insightful for me. 9 00:00:25.065 --> 00:00:26.965 So when we think of, think about strategy, 10 00:00:26.975 --> 00:00:30.245 we're we're talking about creating and developing value 11 00:00:30.345 --> 00:00:32.125 and competitive advantage, you. 12 00:00:32.125 --> 00:00:34.245 We're, we're thinking about it in different contexts, 13 00:00:34.275 --> 00:00:36.805 like establishing a vision or goal. 14 00:00:37.175 --> 00:00:39.645 We're thinking about analysis of the external 15 00:00:39.705 --> 00:00:40.965 and the internal environment. 16 00:00:40.965 --> 00:00:42.405 And we're talking about implementation. 17 00:00:42.945 --> 00:00:46.735 And strategy can benefit hugely from GenAI. 18 00:00:46.875 --> 00:00:49.575 And I, I think what we've struggled with over the last, 19 00:00:50.055 --> 00:00:52.975 I guess, century in terms of business strategy is what, 20 00:00:53.085 --> 00:00:55.735 what, what in essence we call bounded rationality. 21 00:00:56.355 --> 00:00:59.575 And when you think of the strategists, their, 22 00:00:59.665 --> 00:01:03.295 their cognitive abilities are bounded by the information 23 00:01:03.295 --> 00:01:05.295 that they have and the world 24 00:01:05.295 --> 00:01:06.775 that they see in their experiences. 25 00:01:07.635 --> 00:01:11.815 And GenAI helps to, to push out that boundary, uh, so 26 00:01:11.815 --> 00:01:14.935 that we're less bounded by the, the constraints 27 00:01:14.935 --> 00:01:16.975 that have traditionally been in place 28 00:01:17.565 --> 00:01:19.775 with strategy development and implementation. 29 00:01:20.395 --> 00:01:25.215 So for me, as I look to strategy development and formulation, 30 00:01:25.215 --> 00:01:26.495 and strategy implementation, 31 00:01:27.075 --> 00:01:29.615 the ways in which generative AI can aid in 32 00:01:30.865 --> 00:01:35.625 creating effective strategies are so huge, right? 33 00:01:35.765 --> 00:01:38.745 So yeah, as we think about it in terms of strategy 34 00:01:38.975 --> 00:01:41.985 that benefits from GenAI as a, a researcher, 35 00:01:42.445 --> 00:01:45.185 as an interpreter, as a, a thought partner, 36 00:01:45.525 --> 00:01:48.305 as a simulator, and yeah. 37 00:01:48.625 --> 00:01:49.745 Ultimately as a communicator 38 00:01:50.045 --> 00:01:52.705 and leveraging it across all of those things 39 00:01:53.165 --> 00:01:56.785 to ultimately develop successful strategies, I think it's, 40 00:01:56.785 --> 00:01:58.985 it's taken away a lot of our excuses as strategists. 41 00:01:59.165 --> 00:02:02.305 Um, so yeah, hugely excited about trying 42 00:02:02.305 --> 00:02:04.305 to create meaningful experiences 43 00:02:04.765 --> 00:02:09.325 for folks within this context to enable them 44 00:02:09.325 --> 00:02:11.125 to become better strategists 45 00:02:11.145 --> 00:02:15.205 and to develop better strategies using that 46 00:02:16.595 --> 00:02:19.525 huge a, aid that is generative AI. [Carolyn] Wow. 47 00:02:19.945 --> 00:02:22.445 It sounds simultaneously exciting and terrifying. [Will] Yes. 48 00:02:22.745 --> 00:02:26.525 [Carolyn] It, that, that opens up so many possibilities in a world 49 00:02:26.525 --> 00:02:28.365 that's already had so many possibilities. 50 00:02:29.025 --> 00:02:30.565 So I, let's say 51 00:02:30.805 --> 00:02:33.325 that I took my last strategy class five years ago. 52 00:02:33.475 --> 00:02:35.285 It's actually been more than that, but be nice. [Will chuckles] 53 00:02:35.905 --> 00:02:40.045 And I now am hearing, okay, GenAI has come in 54 00:02:40.045 --> 00:02:41.165 and changed [Will] Mmhmm [Carolyn] that. 55 00:02:41.835 --> 00:02:43.685 What are some of the things that would surprise me? 56 00:02:44.565 --> 00:02:45.925 [Will] I think first of all, 57 00:02:46.705 --> 00:02:48.405 and maybe I'll, I'll parse this across 58 00:02:48.415 --> 00:02:49.685 three different sections. [Carolyn] Please. 59 00:02:50.345 --> 00:02:53.365 [Will] The first thing is the, the time to insight. 60 00:02:53.785 --> 00:02:57.225 So I think if you took a strategy class five years ago, 61 00:02:57.485 --> 00:02:59.765 you're stuck for, you know, 62 00:02:59.765 --> 00:03:01.405 four weeks working on a strategy. 63 00:03:02.105 --> 00:03:04.485 And what I like to think about GenAI is 64 00:03:04.485 --> 00:03:09.305 that it's accelerated that analysis time, that it, if I like 65 00:03:09.305 --> 00:03:12.025 to think about it in the context of a five mile race, that 66 00:03:12.755 --> 00:03:15.225 GenAI pretty much puts us at mile marker 67 00:03:15.405 --> 00:03:16.625 four, instantaneously. 68 00:03:17.655 --> 00:03:19.835 That's not to say that we've don't have 69 00:03:19.835 --> 00:03:20.955 to run the last mile, 70 00:03:21.855 --> 00:03:26.265 but we're immediately transported to closer 71 00:03:26.365 --> 00:03:29.505 to the finish line with a relatively simple prompt. 72 00:03:29.645 --> 00:03:33.225 And relatively simple data uploads and, 73 00:03:33.285 --> 00:03:34.625 and information uploads. 74 00:03:35.045 --> 00:03:38.235 And then that last mile means that we can sprint it, 75 00:03:38.905 --> 00:03:40.885 and we can, we deploy our time. 76 00:03:41.835 --> 00:03:45.165 That honestly, traditionally was part of the, 77 00:03:45.305 --> 00:03:46.925 the drudgery of strategy. 78 00:03:47.065 --> 00:03:51.645 You know, reading 10-K after 10-K, reading industry analyses 79 00:03:51.645 --> 00:03:52.805 after industry analyses, 80 00:03:53.345 --> 00:03:55.845 and now being able to develop an agent 81 00:03:55.865 --> 00:04:00.565 or a custom, being able to mine, compare contrast, 82 00:04:01.465 --> 00:04:05.045 and synthesize immediately brings us to that mile marker four. 83 00:04:05.525 --> 00:04:08.645 I like to run [Carolyn] Absolutely. [Will] As a running context. 84 00:04:08.825 --> 00:04:11.845 And yeah, I I'm saving all my energy for that last model, 85 00:04:11.845 --> 00:04:14.525 whereas right now with generative AI, 86 00:04:14.645 --> 00:04:16.445 I think understanding the tools 87 00:04:16.505 --> 00:04:19.885 and understanding the processes, still having that 88 00:04:20.405 --> 00:04:25.085 strategy understanding allows us to then secondly 89 00:04:26.325 --> 00:04:27.445 leverage information and data. 90 00:04:28.185 --> 00:04:31.525 So I think, you know, the, the context of data 91 00:04:32.265 --> 00:04:34.005 is even more important. 92 00:04:34.355 --> 00:04:38.005 [Carolyn] Yeah. [Will] in a GenAI. Like just a, a simple prompt in, 93 00:04:38.345 --> 00:04:42.365 in any LLM bot will get you some good insights, being able 94 00:04:42.385 --> 00:04:44.285 to upload documents and [Carolyn] Yeah. 95 00:04:44.285 --> 00:04:47.485 [Will] information and data with the, uh, you know, 96 00:04:48.125 --> 00:04:49.605 retrieval augmented generation context. 97 00:04:49.735 --> 00:04:54.405 [Carolyn] Right. [Will] And then thirdly, I think it enables us just 98 00:04:54.405 --> 00:04:57.695 to develop better decisions [Carolyn] Oh. 99 00:04:57.715 --> 00:04:58.735 [Will] and insights. [Carolyn] For sure. 100 00:04:58.875 --> 00:05:02.495 [Will] So those are the three things that I think that GenAI has, 101 00:05:02.715 --> 00:05:05.335 has accelerated hugely. 102 00:05:06.265 --> 00:05:08.005 And I think anyone 103 00:05:08.005 --> 00:05:11.605 that isn't using GenAI in a strategic context 104 00:05:12.835 --> 00:05:15.095 is running all five miles by themselves. 105 00:05:15.395 --> 00:05:18.255 [Carolyn[ Wow. [Will] And you're competing against, you know, someone who is 106 00:05:19.185 --> 00:05:20.295 [Carolyn] Fresh at mile four. 107 00:05:20.365 --> 00:05:25.095 [Will] Yeah, exactly. [Carolyn] Yeah. [Will] So yeah, it, it, it's tough. 108 00:05:25.165 --> 00:05:29.735 Like, [Carolyn] Yeah. [Will] So [Carolyn] I can see that [Will] the, the comparative effect that, 109 00:05:29.955 --> 00:05:33.285 you know, and I know the trope is that, that, you know, 110 00:05:33.285 --> 00:05:34.805 GenAI is gonna replace everyone. 111 00:05:34.965 --> 00:05:38.445 I, I think that the more common appreciation that most 112 00:05:38.445 --> 00:05:40.605 of us have is that someone who is 113 00:05:41.195 --> 00:05:44.405 effectively used gen, using GenAI in a strategic context 114 00:05:44.465 --> 00:05:47.325 at least, that's the person you should be worried about. 115 00:05:47.385 --> 00:05:51.965 So that's the person to me you should be, rather than, 116 00:05:52.865 --> 00:05:56.005 you know, the, the person that is worried about it 117 00:05:56.005 --> 00:05:57.165 in a substitute context. 118 00:05:58.225 --> 00:06:00.045 [Carolyn] People often say that one of the things 119 00:06:00.045 --> 00:06:02.165 that makes organizational change, 120 00:06:02.165 --> 00:06:05.565 particularly strategic change so hard, is that it just takes 121 00:06:05.625 --> 00:06:07.645 so long to figure out the direction that you're going. 122 00:06:08.265 --> 00:06:10.885 Now, it seems like what you're saying is we can start to get 123 00:06:10.885 --> 00:06:13.725 to change implementation significantly more quickly 124 00:06:14.475 --> 00:06:16.365 than we could otherwise. [Will] Yeah. 125 00:06:16.385 --> 00:06:19.125 And I, I still think that the change is difficult, 126 00:06:19.125 --> 00:06:23.125 obviously, because you've got, you know, control mechanisms, 127 00:06:23.185 --> 00:06:26.285 and you've got structural, and you've got politics, 128 00:06:26.385 --> 00:06:28.165 and you've got inertia. 129 00:06:28.265 --> 00:06:30.125 Uh, but I think GenAI 130 00:06:30.325 --> 00:06:34.405 can help you make a persuasive case for change. 131 00:06:34.405 --> 00:06:36.605 [Carolyn] Right. [Will] And can help you keep track of change, 132 00:06:37.225 --> 00:06:39.845 it can enable your, your change process, 133 00:06:40.345 --> 00:06:43.525 [Carolyn] Manage stakeholders, get communication aligned. 134 00:06:44.325 --> 00:06:46.685 I love that. And it's clearer. 135 00:06:46.745 --> 00:06:49.685 That's so much easier when you have that strategic vision 136 00:06:50.235 --> 00:06:52.205 articulated with data [Will] Yes. 137 00:06:52.385 --> 00:06:54.685 [Carolyn] to set the whole process up to move forward. [Will] Yeah. 138 00:06:54.685 --> 00:06:57.125 Going back [Carolyn] Wow. [Will] to the second consideration, I think that [Carolyn] yeah 139 00:06:57.225 --> 00:07:00.245 [Will] having access to data, being able to interpret data, 140 00:07:01.115 --> 00:07:04.765 when it comes to, you know, data analytics that, you know, 141 00:07:04.785 --> 00:07:06.405 we all spend a, a huge amount of time. 142 00:07:06.635 --> 00:07:08.005 Similarly, being able 143 00:07:08.005 --> 00:07:11.405 to understand data in a more effective manner 144 00:07:11.405 --> 00:07:13.925 through GenAI creates that shortcut. 145 00:07:14.105 --> 00:07:16.965 And I know we talk about GenAI as a complement, 146 00:07:17.065 --> 00:07:21.125 and to me it is so effective as a thought partner. 147 00:07:21.235 --> 00:07:23.885 Like if I'm a, I mean, I'm working in a strategy context, 148 00:07:24.035 --> 00:07:26.845 then it's, it's like an army of GAs. 149 00:07:27.105 --> 00:07:30.045 [Carolyn] Yes. [Will] There are interns that are doing all of the work that, 150 00:07:30.075 --> 00:07:32.925 that I don't necessarily have the bandwidth 151 00:07:33.025 --> 00:07:34.965 or the time to do, and, 152 00:07:35.145 --> 00:07:36.365 [Carolyn] And they're coming up with ideas 153 00:07:36.605 --> 00:07:37.685 I may never have thought of. [Will] Yes. 154 00:07:38.545 --> 00:07:41.045 [Carolyn] Yes, I agree wholeheartedly. I need to know what to ask. 155 00:07:41.705 --> 00:07:43.645 [Will] Oh, yeah. [Carolyn] But once I do [Will] yeah. 156 00:07:43.755 --> 00:07:45.885 [Carolyn] they can be just incredibly insightful. 157 00:07:45.885 --> 00:07:47.445 That's, that's really cool. [Will] And 158 00:07:47.445 --> 00:07:49.445 I think GenAI is also, like, 159 00:07:49.545 --> 00:07:53.565 the newer models are actually becoming even more effective 160 00:07:54.115 --> 00:07:56.405 with regard to prompt engineering. 161 00:07:56.405 --> 00:07:59.205 That when you look at your chain of thought prompting, 162 00:07:59.205 --> 00:08:02.045 and we look at the way in which, you know, some 163 00:08:02.045 --> 00:08:05.085 of the more advanced deep research models, they're asking 164 00:08:06.065 --> 00:08:08.405 for clarification on any ambiguities, 165 00:08:08.465 --> 00:08:11.325 and then the iterative process that you will have 166 00:08:11.355 --> 00:08:13.045 with an, a GenAI tool 167 00:08:13.045 --> 00:08:16.605 or an LLM allows for, for it to be 168 00:08:17.125 --> 00:08:18.405 a dialogue that [Carolyn] Right. 169 00:08:18.635 --> 00:08:21.245 [Will] will unearth what you are looking for for the most part. 170 00:08:21.385 --> 00:08:22.445 [Carolyn] Wow. [Will] So yeah, I'm, 171 00:08:22.705 --> 00:08:24.765 I'm obviously hugely excited about GenAI. 172 00:08:24.785 --> 00:08:29.365 [Carolyn] Me too. [Will] So, yes, my, my completely one-sided argument as 173 00:08:29.365 --> 00:08:32.215 to why I think GenAI is instrumental 174 00:08:32.595 --> 00:08:35.735 to effective strategy development and implementation. 175 00:08:35.885 --> 00:08:40.175 [Carolyn] Totally makes sense. So I let, let's do devil's advocate 176 00:08:40.175 --> 00:08:42.095 for a minute because I know you and I are advocates. 177 00:08:42.165 --> 00:08:45.535 [Will] Yeah. [Carolyn] What are some things that you might have to say 178 00:08:45.535 --> 00:08:46.735 to someone who's skeptical 179 00:08:46.885 --> 00:08:49.255 that you are outsourcing the real work? 180 00:08:49.515 --> 00:08:52.015 [Will] Oh, yeah. So I, I think you still have 181 00:08:52.015 --> 00:08:53.255 to run the last mile. 182 00:08:53.395 --> 00:08:57.565 [Carolyn] Yep. [Will] So it's not necessarily a panacea that 183 00:08:58.315 --> 00:09:02.165 most of the studies show that it's the, the A players 184 00:09:02.195 --> 00:09:04.525 that are going to benefit most from GenAI. 185 00:09:04.915 --> 00:09:06.005 [Carolyn] Tell me more. [Will] Yeah. 186 00:09:06.005 --> 00:09:08.765 Because ultimately as, as you think about 187 00:09:09.965 --> 00:09:11.535 looking at people 188 00:09:11.595 --> 00:09:16.125 who are ineffective within your organization, what I've seen 189 00:09:16.125 --> 00:09:18.205 and what the research validates is that most 190 00:09:18.205 --> 00:09:20.245 of them are using it as a substitute. 191 00:09:20.395 --> 00:09:23.665 [Carolyn] Oo. [Will] And that, that word 192 00:09:23.695 --> 00:09:25.745 that I think has emerged over the last six months 193 00:09:25.745 --> 00:09:28.825 of work slop, where you are copying 194 00:09:28.825 --> 00:09:31.025 and pasting the output of a GenAI 195 00:09:31.525 --> 00:09:34.065 and you're representing that as your own thoughts 196 00:09:34.065 --> 00:09:37.945 and ideas, rather than, you know, you don't get a medal. 197 00:09:38.355 --> 00:09:40.785 We're arriving at the fourth mile of the five mile race, 198 00:09:40.845 --> 00:09:45.675 and that to me is where work slop, um, can tarnish reputation 199 00:09:45.685 --> 00:09:47.275 [Carolyn] Right. [Will] and legitimacy. [Carolyn] Right. 200 00:09:47.295 --> 00:09:49.795 [Will] So you still have to, to take all 201 00:09:49.795 --> 00:09:53.075 of the insights from your GAs or your, your interns. 202 00:09:53.375 --> 00:09:56.595 [Carolyn] Yep. [Will] And that's where the, the real value can be redeployed, 203 00:09:56.775 --> 00:09:58.595 at least in my opinion, that [Carolyn] It's fascinating. 204 00:09:58.655 --> 00:10:00.715 [Will] you, you still have to run the last mile, 205 00:10:01.135 --> 00:10:03.835 but you've been given a platform to run it 206 00:10:04.015 --> 00:10:06.715 so much faster than traditional five miles. 207 00:10:07.435 --> 00:10:08.915 [Carolyn] I am intrigued by that analogy 208 00:10:09.185 --> 00:10:12.555 because in in academia in particular, it's assumed 209 00:10:12.785 --> 00:10:14.355 that you use GAs 210 00:10:14.355 --> 00:10:16.155 and you use, you know, that, that kind 211 00:10:16.155 --> 00:10:17.195 of research assistance. 212 00:10:17.655 --> 00:10:20.035 But we never really say, I mean, on the paper, 213 00:10:20.515 --> 00:10:22.235 I used research assistants for this, 214 00:10:22.575 --> 00:10:26.035 but now we are expected to say, I used AI for some of this, 215 00:10:26.125 --> 00:10:29.075 which maybe that's more honest than we were before. 216 00:10:29.835 --> 00:10:32.515 [Will] I, I, I love the GenAI attestation 217 00:10:32.515 --> 00:10:36.315 because to, to me, it shows that you're using 218 00:10:36.895 --> 00:10:39.035 the tools that are at your disposal, 219 00:10:39.135 --> 00:10:41.435 and I like to know how you've used them as well. 220 00:10:41.435 --> 00:10:45.475 And if it is a research paper or if it is, you know, 221 00:10:45.615 --> 00:10:48.315 and a media report, then yeah. 222 00:10:48.465 --> 00:10:51.475 Like, as a thought partner, as a complement that's a, 223 00:10:51.815 --> 00:10:55.715 you know, citation or bibliographic tool as, as a mechanism 224 00:10:55.895 --> 00:10:59.115 to make your, well, at least my writing style is quite, 225 00:10:59.805 --> 00:11:02.715 quite winding, so it helps me to be more concise 226 00:11:03.055 --> 00:11:07.315 and yeah, I think, you know, the, again, some 227 00:11:07.315 --> 00:11:09.675 of the classic technologies that we have, whether it's the, 228 00:11:09.935 --> 00:11:12.555 the calculator or Excel [Carolyn] Exactly. [Will] like 229 00:11:13.655 --> 00:11:17.315 we have moves into leveraging those tools 230 00:11:17.895 --> 00:11:19.315 in productive manners. 231 00:11:19.315 --> 00:11:22.675 And if you're not using Excel 20 years ago, 232 00:11:23.255 --> 00:11:24.475 you're at a disadvantage. 233 00:11:24.625 --> 00:11:26.075 [Carolyn] Exactly. [Will] the same right now. 234 00:11:26.175 --> 00:11:30.075 But yeah, I, I think it's really, really important to, 235 00:11:30.215 --> 00:11:33.915 to use that as an aid or as a complement, for sure. 236 00:11:34.305 --> 00:11:36.435 [Carolyn] That, that, that's really cool. 237 00:11:36.815 --> 00:11:41.195 And so folks come to the class, they get strategy 2026, 238 00:11:41.505 --> 00:11:44.355 literally because it's with a partner that we, 239 00:11:44.575 --> 00:11:46.315 we didn't have prior to that. 240 00:11:46.735 --> 00:11:48.395 I'm finding that absolutely intriguing. 241 00:11:49.545 --> 00:11:53.525 What has been for you, some of the biggest, um, 242 00:11:54.725 --> 00:11:57.525 I, I guess not biggest, some of your favorite things 243 00:11:57.635 --> 00:12:00.325 that you've found that AI can do that you didn't expect? 244 00:12:00.985 --> 00:12:05.445 [Will] Oh, wow. So when I, when I teach AI, 245 00:12:05.605 --> 00:12:06.965 I have a, a list of all 246 00:12:06.965 --> 00:12:09.205 of the ways in which I've used it in the last month. 247 00:12:09.535 --> 00:12:13.725 [Carolyn] Uhhuh. [Will] and everything from writing 248 00:12:14.685 --> 00:12:18.525 creative bedtime stories for my five-year-old, uh, to, 249 00:12:19.305 --> 00:12:23.085 you know, animating photographs within those stories 250 00:12:23.185 --> 00:12:27.665 for my five-year-olds to travel planning to, 251 00:12:28.975 --> 00:12:32.355 uh, my work context, which obviously writing letters 252 00:12:32.375 --> 00:12:34.475 of recommendation, [Carolyn] Right. 253 00:12:34.625 --> 00:12:37.795 [Will] helping me to prepare classes, helping me to come up 254 00:12:37.795 --> 00:12:41.915 with examples, helping me to brainstorm different ways 255 00:12:41.935 --> 00:12:44.195 of thinking of my material, 256 00:12:44.615 --> 00:12:47.035 and then some others that I borrowed from you as to, well, 257 00:12:47.035 --> 00:12:48.635 helping me understand my own biases. 258 00:12:49.235 --> 00:12:52.315 [Carolyn] Absolutely. [Will] You know, a class that I'll record as, uh, 259 00:12:52.345 --> 00:12:53.835 putting it into the LLM 260 00:12:53.835 --> 00:12:56.835 and asking me [Carolyn] Yup. [Will] ways in which I can be more inclusive 261 00:12:57.095 --> 00:13:01.805 or ways in which my pedagogical style can improve for me, 262 00:13:01.865 --> 00:13:06.225 the, the opportunities with GenAI are limitless, 263 00:13:06.455 --> 00:13:08.665 with a caveat that obviously it hallucinates 264 00:13:08.665 --> 00:13:10.825 and obviously there are its own biases, 265 00:13:12.315 --> 00:13:17.295 but taking GenAI as that thought partner 266 00:13:17.545 --> 00:13:18.575 [Carolyn] Right. [Will] you know, and, 267 00:13:18.575 --> 00:13:21.575 and even for like my own mental health, like being, 268 00:13:21.775 --> 00:13:23.975 I know I've talked to you about this, being a better dad. 269 00:13:24.895 --> 00:13:27.495 I don't feel comfortable talking to most people about all 270 00:13:27.495 --> 00:13:31.185 of my foible as the mistakes I'm making with my five-year-old, 271 00:13:31.185 --> 00:13:34.345 but I'm very comfortable putting in, in, in, into an LLM 272 00:13:34.415 --> 00:13:36.625 with, again, the usual caveats about, 273 00:13:37.245 --> 00:13:40.705 and you know, it helping me think about things a 274 00:13:40.705 --> 00:13:41.825 little more differently. 275 00:13:42.005 --> 00:13:44.025 [Carolyn] Yes. [Will] And it knows me pretty well, so [Carolyn] Yes. 276 00:13:44.285 --> 00:13:48.695 [Will] Uh, something I've, I've taken as, uh, um, from Ray Luther, 277 00:13:48.825 --> 00:13:53.735 which is asking that GenAI tool to, to basically roast me, 278 00:13:53.875 --> 00:13:56.695 uh, is, is particularly insightful as to 279 00:13:56.755 --> 00:13:57.935 how much it knows about me. 280 00:13:58.035 --> 00:14:01.095 [Carolyn] Yes. [Will] and it knows my deep insecurities. [Carolyn] Mm-hmm. 281 00:14:02.005 --> 00:14:04.375 Mine too! [Carolyn laughs] [Will] Can be fun. 282 00:14:04.555 --> 00:14:08.015 Uh, I, I guess, uh, it's one of those that, yeah, I, 283 00:14:08.135 --> 00:14:12.755 I use it on an hourly basis in a similar way 284 00:14:12.755 --> 00:14:14.635 that I would use that GA. 285 00:14:15.215 --> 00:14:19.995 Um, I'm looking for ways in which I can cut down the amount 286 00:14:19.995 --> 00:14:21.595 of time I'm spending on tasks and, 287 00:14:21.615 --> 00:14:25.035 and ultimately like we talked about, develop better insights 288 00:14:25.335 --> 00:14:27.475 and more creative insights 289 00:14:27.575 --> 00:14:32.165 or more, you know, uh, uh, realistic insights. 290 00:14:32.725 --> 00:14:35.685 [Carolyn] I love that. One, one of the things I've, I've found is 291 00:14:35.685 --> 00:14:38.645 that just having to write a good prompt prompts me 292 00:14:38.645 --> 00:14:41.485 to think in ways that I typically would not have. 293 00:14:42.185 --> 00:14:43.525 And so even sitting down 294 00:14:43.525 --> 00:14:46.325 and saying, I need to write an email that does these things, 295 00:14:47.425 --> 00:14:49.965 and I probably wouldn't have thought about all the things it 296 00:14:49.965 --> 00:14:53.045 needed to do until I went through that process. 297 00:14:53.665 --> 00:14:56.205 Um, by the way, I want to be your five-year-old. 298 00:14:56.565 --> 00:14:59.165 I have just, I, if you're creating unique stories 299 00:14:59.385 --> 00:15:01.405 and animation that, that's, 300 00:15:01.665 --> 00:15:03.365 that's taking parenting up a step. 301 00:15:03.545 --> 00:15:05.485 I'm just gonna put that out there. [Will] Yeah. 302 00:15:05.485 --> 00:15:08.125 I'm not sure. It's, it's definitely helped me 303 00:15:08.125 --> 00:15:10.165 with my five-year-old and, 304 00:15:10.165 --> 00:15:12.525 and feedback on my golf game, not so much, 305 00:15:12.665 --> 00:15:16.125 but my five-year-old hopefully is benefiting from [Carolyn] I love it. 306 00:15:16.155 --> 00:15:17.565 [Will] ways in which I can engage him 307 00:15:17.565 --> 00:15:20.445 and think more about the world that he lives in. 308 00:15:20.765 --> 00:15:23.845 rather than the world that I live in. For sure. 309 00:15:24.105 --> 00:15:26.285 [Carolyn] And so you're not doing stories about back in the day 310 00:15:26.395 --> 00:15:29.045 when you walked uphill. I love that. 311 00:15:29.135 --> 00:15:31.525 [Will] Ironically, he looks for a lot of those stories as well 312 00:15:31.545 --> 00:15:34.045 to contextualize my childhood, David's childhood. 313 00:15:34.465 --> 00:15:36.925 Uh, so yeah, there's, there's some, 314 00:15:36.925 --> 00:15:39.725 some gingerbread man travels that are happening right now 315 00:15:39.725 --> 00:15:44.465 that are made even more, I guess, contextual to his world 316 00:15:44.525 --> 00:15:46.905 as the gingerbread man is traveling around the world. 317 00:15:47.625 --> 00:15:50.665 [Carolyn] I, I think you have a second career burgeoning here, right? 318 00:15:50.665 --> 00:15:52.545 That, that's, that's actually really cool. 319 00:15:53.365 --> 00:15:56.865 So if, if I am considering taking the course, 320 00:15:56.935 --> 00:15:59.865 give me an unabashed sales pitch, why should I sign up? 321 00:16:00.125 --> 00:16:03.505 [Will] Uh, so I think you will develop 322 00:16:05.005 --> 00:16:07.825 and improve your strategic thinking capability 323 00:16:08.565 --> 00:16:11.785 and that acumen that you have for strategic thinking, which 324 00:16:12.325 --> 00:16:14.385 as we look at the basis 325 00:16:14.445 --> 00:16:16.945 of success in individual competitive advantage going 326 00:16:16.945 --> 00:16:20.505 forward, it's, it's, it's the key criterion. 327 00:16:20.505 --> 00:16:22.945 It's what we look for in our staff. 328 00:16:22.975 --> 00:16:24.505 It's what I see time 329 00:16:24.625 --> 00:16:26.825 and time again that organizations are looking for, 330 00:16:27.245 --> 00:16:30.065 you'll become more entrepreneurial, or well at least 331 00:16:30.065 --> 00:16:31.865 that's my hope. You'll become more innovative. 332 00:16:32.085 --> 00:16:35.095 You'll have the support 333 00:16:35.955 --> 00:16:39.895 and the ability to leverage a tool that will 334 00:16:40.685 --> 00:16:45.585 create meaningful, impactful differences between you 335 00:16:45.645 --> 00:16:47.345 and, and your colleagues. 336 00:16:48.705 --> 00:16:52.025 [Carolyn] I love that, that support, that hands-on coach, um, 337 00:16:52.165 --> 00:16:54.985 for folks who, who have not di dove in 338 00:16:54.985 --> 00:16:57.345 as deeply really is an important component. 339 00:16:57.405 --> 00:16:59.105 And so to have both the live day 340 00:16:59.105 --> 00:17:01.465 and the online day where you can now, 341 00:17:01.465 --> 00:17:03.825 then you truly do get something more like a golf coach [Will laughing] Yeah! 342 00:17:04.155 --> 00:17:07.745 [Carolyn] where you can have somebody show you the, the, 343 00:17:07.745 --> 00:17:09.185 the pros and cons of how that's working. 344 00:17:09.675 --> 00:17:12.945 Thank you. I am so excited about this class and our lineup, 345 00:17:13.045 --> 00:17:14.985 and just excited for everybody to meet you. 346 00:17:15.015 --> 00:17:17.705 [Will] Yeah, me too. I could not be more excited about your 347 00:17:17.705 --> 00:17:19.625 leadership in this initiative Carolyn, 348 00:17:19.645 --> 00:17:21.945 and all of the amazing work that you're doing. 349 00:17:22.015 --> 00:17:22.865 [Carolyn] It's fun. Thanks.