1 00:00:00,186 --> 00:00:03,476 Most digital transformations fail, not because of the technology, 2 00:00:03,676 --> 00:00:05,426 but because change is hard. 3 00:00:06,016 --> 00:00:08,956 And now, with artificial intelligence accelerating change 4 00:00:08,966 --> 00:00:12,526 at an unprecedented pace, the resistance is stronger than ever. 5 00:00:13,106 --> 00:00:16,386 How do you get employees to embrace AI instead of fearing it? 6 00:00:17,266 --> 00:00:21,016 My guest today, a veteran business operations leader, shares the hard 7 00:00:21,096 --> 00:00:25,596 earned lessons of making transformations stick, starting with the human side. 8 00:00:26,106 --> 00:00:30,226 My name is Alexandre Nevski, and this is Innovation Tales. 9 00:00:31,366 --> 00:00:33,946 Navigating Change one story at a time. 10 00:00:33,976 --> 00:00:38,176 We share insights from leaders tackling the challenges of today's digital world. 11 00:00:38,446 --> 00:00:41,956 Welcome to Innovation Tales, the podcast exploring the human 12 00:00:41,956 --> 00:00:43,816 side of digital transformation. 13 00:00:59,625 --> 00:01:01,935 AI is transforming business at lightning speed. 14 00:01:02,215 --> 00:01:04,245 But technology isn't the hardest part. 15 00:01:04,915 --> 00:01:07,765 Rather, it is people's ability to keep up and adapt. 16 00:01:08,565 --> 00:01:12,045 Today's guest, Nicole Hilgenkamp, has spent over 20 years 17 00:01:12,295 --> 00:01:13,835 leading major transformations. 18 00:01:14,375 --> 00:01:18,205 She knows that real success comes from more than just adopting technology. 19 00:01:18,855 --> 00:01:22,495 It's about guiding teams through change and making sure companies see 20 00:01:22,505 --> 00:01:24,815 real value, not just big promises. 21 00:01:25,605 --> 00:01:29,115 She's mastered the art of combining AI with smart business strategies 22 00:01:29,355 --> 00:01:32,825 to make operations smoother, more efficient, and future ready. 23 00:01:33,545 --> 00:01:37,465 In this episode, Nicole shares how leaders can help employees embrace 24 00:01:37,465 --> 00:01:42,115 AI, avoid common pitfalls, and create a culture of innovation. 25 00:01:42,805 --> 00:01:45,525 If you want to make AI work for your team, not against it, 26 00:01:45,775 --> 00:01:46,995 this conversation is for you. 27 00:01:47,825 --> 00:01:51,025 Without further ado, here's my conversation with Nicole Hilgenkamp. 28 00:01:51,216 --> 00:01:52,536 Nicole, welcome to the show. 29 00:01:52,664 --> 00:01:53,304 Thanks, Alex. 30 00:01:53,304 --> 00:01:54,184 Thanks for having me. 31 00:01:54,585 --> 00:01:55,475 It's great to have you. 32 00:01:55,866 --> 00:01:59,476 Let's start with your extensive experience in business operations. 33 00:02:00,156 --> 00:02:03,066 What have been the main challenges you've had to navigate as a 34 00:02:03,066 --> 00:02:05,276 change agent in large enterprises? 35 00:02:05,830 --> 00:02:10,020 Yeah, I work for some of the largest companies in the world, and every year 36 00:02:10,020 --> 00:02:12,230 is different from one year to the next. 37 00:02:12,230 --> 00:02:21,865 And I think in transformation of any kind, and which is consistent, in business is 38 00:02:21,875 --> 00:02:24,295 really starting with the people at mind. 39 00:02:24,295 --> 00:02:28,545 And so I, there has been really successful transformations I've been 40 00:02:28,545 --> 00:02:32,945 part of, but it all goes back to the people there and their willingness 41 00:02:32,945 --> 00:02:35,455 to adapt and change themselves. 42 00:02:35,975 --> 00:02:39,725 as a business operations leader, we can bring some of the best 43 00:02:40,185 --> 00:02:45,585 process or technology or operating models to our organizations. 44 00:02:46,410 --> 00:02:50,330 But if the individuals aren't ready to accept it, they don't 45 00:02:50,330 --> 00:02:55,080 understand why the transformation is happening, then you're not going to 46 00:02:55,080 --> 00:02:57,460 get the best return on investment. 47 00:02:57,470 --> 00:03:03,600 So from what is the hardest when we look at transforming and thinking about, 48 00:03:03,650 --> 00:03:08,260 The next transformation really has to start with the people because the people 49 00:03:08,260 --> 00:03:10,580 have to be supportive and on board. 50 00:03:10,580 --> 00:03:13,640 And I think through the transformations that were the harder for the ones 51 00:03:13,640 --> 00:03:17,960 that I've done over the years, it really was the individuals 52 00:03:17,960 --> 00:03:20,850 weren't ready to take that leap. 53 00:03:21,397 --> 00:03:25,157 Okay, so we focus on the people, that's, I think, what the 54 00:03:25,157 --> 00:03:26,637 show is about, that's perfect. 55 00:03:27,167 --> 00:03:32,587 And is there a trend now that is making, it even harder for 56 00:03:32,607 --> 00:03:38,917 people to be on board now that the transformations involve AI technologies? 57 00:03:39,277 --> 00:03:44,137 Do you see an evolution in the way you've had to do change management? 58 00:03:44,606 --> 00:03:51,056 Absolutely, always looking to find better ways to help people through 59 00:03:51,056 --> 00:03:57,666 that change curve, and artificial intelligence, the largest transformation 60 00:03:57,666 --> 00:04:06,681 that will happen within my time, is one of those that is really easy to 61 00:04:06,771 --> 00:04:12,851 start to work with, but it also has a tremendous fear factor out there. 62 00:04:12,901 --> 00:04:18,771 And so when we talk about transforming and meaning the people to understand and 63 00:04:18,781 --> 00:04:24,796 support when they're hearing, the good and a lot of the, bad that can happen through 64 00:04:24,816 --> 00:04:31,496 artificial intelligence, then they're even more fearful to want to transform. 65 00:04:32,096 --> 00:04:36,066 some of the things that come to mind are, it's going to take my job. 66 00:04:36,651 --> 00:04:38,911 It's going to take my information. 67 00:04:39,411 --> 00:04:41,301 It's going to know too much about me. 68 00:04:41,301 --> 00:04:43,711 My privacy will be in jeopardy. 69 00:04:44,191 --> 00:04:47,081 there could be used for non good. 70 00:04:47,971 --> 00:04:50,591 are we going to be a society ran by machines? 71 00:04:50,811 --> 00:04:54,101 Those are the things that you're hearing when it comes to people 72 00:04:54,101 --> 00:04:55,801 fearful of artificial intelligence. 73 00:04:56,551 --> 00:04:58,841 And that is. 74 00:04:59,431 --> 00:05:03,591 Some of those are very real and will make it much harder in this 75 00:05:03,591 --> 00:05:08,031 largest transformation of all time, I feel, as artificial intelligence, 76 00:05:08,031 --> 00:05:11,981 with some of those looming that you wouldn't have gotten in some 77 00:05:11,981 --> 00:05:16,851 of the other transformations that we have been through in businesses. 78 00:05:17,178 --> 00:05:23,708 And what is the role that you see for business leaders um, I think 79 00:05:23,708 --> 00:05:29,098 the term is AI literacy how do they develop their employees AI literacy? 80 00:05:29,148 --> 00:05:33,008 How do they help those employees get familiar with those tools 81 00:05:33,018 --> 00:05:34,148 without overwhelming them? 82 00:05:35,012 --> 00:05:38,432 Great question and definitely a consideration. 83 00:05:38,452 --> 00:05:42,702 Here's my best practice to AI-enable your team. 84 00:05:43,042 --> 00:05:48,211 Your team in the world are, let's just say you have a team of a hundred people. 85 00:05:48,221 --> 00:05:51,251 Some of those hundred people are already utilizing artificial 86 00:05:51,251 --> 00:05:55,131 intelligence in their personal lives and even in their professional lives. 87 00:05:55,601 --> 00:05:56,671 They're just not telling you. 88 00:05:57,961 --> 00:06:03,211 So there's the other portion of that team that doesn't even know 89 00:06:03,421 --> 00:06:05,271 what artificial intelligence is. 90 00:06:05,991 --> 00:06:12,221 As a leader, you have to show up for your team and you have to enable them 91 00:06:12,221 --> 00:06:17,001 all with the tools to help them in their professional, and by the way, 92 00:06:17,081 --> 00:06:21,926 in their personal life as well, that will help them in their personal life. 93 00:06:22,501 --> 00:06:25,191 I think we always think it's business related, but there's a 94 00:06:25,191 --> 00:06:28,641 lot of things that can happen that I use artificial intelligence that 95 00:06:30,391 --> 00:06:34,261 enables me in my personal life that I'm able to do better with AI. 96 00:06:34,756 --> 00:06:39,146 And so we really want to, as a leader, show up and say, I'm here 97 00:06:39,146 --> 00:06:41,716 to support artificial intelligence. 98 00:06:41,716 --> 00:06:45,476 They need to hear that from leadership first, that we are 99 00:06:45,836 --> 00:06:47,266 going to AI enable ourself. 100 00:06:47,316 --> 00:06:53,466 I want to, we as a company want to, because it is part 101 00:06:53,466 --> 00:06:54,726 of how we will have to work. 102 00:06:55,396 --> 00:06:58,146 And so really excitingly. 103 00:06:58,621 --> 00:07:05,211 Be that cheerleader to say, let's learn together as one big team and then let's 104 00:07:05,351 --> 00:07:09,421 train everyone, all hundred people, even the ones that are more proficient 105 00:07:09,561 --> 00:07:13,381 already because they personally chose to do that and others that don't even 106 00:07:13,381 --> 00:07:14,811 know what artificial intelligence is. 107 00:07:15,321 --> 00:07:19,851 Let's give them a baseline knowledge of those parameters and guardrails that they 108 00:07:19,851 --> 00:07:23,661 need to put in place so that they're not putting in personal information into the 109 00:07:23,671 --> 00:07:25,921 AI and they know some of those risks. 110 00:07:26,601 --> 00:07:32,331 Once they know those risks, let's play, let's explore, let's start utilizing 111 00:07:32,581 --> 00:07:37,641 it in their personal and professional life so that we can uncover those use 112 00:07:37,641 --> 00:07:42,881 cases that will really help us from a business perspective or help the 113 00:07:42,911 --> 00:07:48,591 individual become immediately efficient at their workstation and their desktop. 114 00:07:50,051 --> 00:07:52,031 So I heard three things. 115 00:07:52,091 --> 00:07:58,191 Model for the employees, ensure that there is, the right amount of 116 00:07:58,601 --> 00:08:01,601 training and other supporting enablers. 117 00:08:02,521 --> 00:08:09,571 And then focus, I guess I heard on the benefits that the organization and its 118 00:08:09,581 --> 00:08:11,771 people can get out of the technology. 119 00:08:11,771 --> 00:08:16,421 So let's unpack or focus on that for a second. 120 00:08:16,421 --> 00:08:23,821 So if you're not part of IT, if you're not a technical employee and engineer 121 00:08:23,821 --> 00:08:29,471 or something, you're within operations or another function, how do you identify 122 00:08:29,491 --> 00:08:37,116 those use cases, those opportunities to do something better, faster, create more 123 00:08:37,116 --> 00:08:39,376 value if you're a non technical user. 124 00:08:39,833 --> 00:08:40,463 Absolutely. 125 00:08:40,508 --> 00:08:42,318 And so many people are non technical. 126 00:08:42,328 --> 00:08:45,418 There's more non technical than there is technical at every company. 127 00:08:45,888 --> 00:08:51,393 And so what I would say is that, how to start utilizing AI is to allow AI to 128 00:08:51,393 --> 00:08:52,863 help you if you don't know how to use it. 129 00:08:53,353 --> 00:08:58,083 it can, it is your coach, your teacher, your tutor, your 130 00:08:58,093 --> 00:09:02,563 psychologist, your tax, your tax advisor you can use it for so much. 131 00:09:02,613 --> 00:09:06,363 What I love about the exploration piece is that everyone's exploring 132 00:09:06,363 --> 00:09:08,063 together and learning together. 133 00:09:08,693 --> 00:09:12,833 One of the things I didn't mention, you said that the three, was to model, 134 00:09:13,663 --> 00:09:18,063 to train of the risk, and then to allow the team to explore, is to do 135 00:09:18,063 --> 00:09:22,793 it together as a team and to have a way to bring in those use cases. 136 00:09:23,123 --> 00:09:26,283 So that some of those great use cases that are coming from the team 137 00:09:26,283 --> 00:09:30,443 and have been very transparent of those use cases that are coming in 138 00:09:30,933 --> 00:09:33,203 that how we're going to scale them. 139 00:09:33,503 --> 00:09:37,773 That with one person found this great use case, then let's utilize 140 00:09:37,773 --> 00:09:39,843 it across the other 99 individuals. 141 00:09:40,203 --> 00:09:44,463 But if we do it together, and we understand that maybe that use case is 142 00:09:44,463 --> 00:09:49,008 going to take a 10 percent efficiency across our team of 100, What are 143 00:09:49,008 --> 00:09:52,528 we going to do with that 10 percent efficiency that we just gained? 144 00:09:52,908 --> 00:09:56,888 So that individuals can then connect that, Oh, we can now 145 00:09:56,908 --> 00:09:59,648 do something more value added. 146 00:10:00,178 --> 00:10:01,898 We can drive more sales. 147 00:10:01,898 --> 00:10:04,268 We can drive a better experience. 148 00:10:04,268 --> 00:10:08,308 We can get into an area that we haven't had time to get into because 149 00:10:08,308 --> 00:10:12,878 we're doing more of those other tasks that took our manual support. 150 00:10:13,868 --> 00:10:19,028 And once you do that together, that's and I'm really transparent and people 151 00:10:19,028 --> 00:10:21,148 can see those use cases, et cetera. 152 00:10:21,418 --> 00:10:23,068 then they can feel that they're part of it. 153 00:10:23,218 --> 00:10:24,428 They can feel that they're part of it. 154 00:10:24,428 --> 00:10:27,918 And that's that human aspect of change management that really is 155 00:10:27,918 --> 00:10:29,738 going to help your team propel. 156 00:10:30,068 --> 00:10:31,508 Jobs will change. 157 00:10:32,038 --> 00:10:35,598 And I'm really transparent with my team that they will change. 158 00:10:35,598 --> 00:10:38,488 What you're doing today is not what you're going to be doing tomorrow. 159 00:10:38,808 --> 00:10:41,858 So we want to evolve with that, but let's do that together. 160 00:10:42,058 --> 00:10:46,138 Let me not do that in the seat that I have as a leader or manager. 161 00:10:46,168 --> 00:10:51,838 Let's do it as a team of 101 and how we can, because the best 162 00:10:51,838 --> 00:10:55,648 places to get those use cases is the individual doing the work. 163 00:10:57,608 --> 00:11:05,218 And so that if you can promote that type of exploration and recognize those 164 00:11:05,218 --> 00:11:10,788 great use cases that are coming forward with the team, then you're going to get 165 00:11:10,808 --> 00:11:14,898 a lot of engagement and you're going to be able to then start to realize 166 00:11:14,898 --> 00:11:17,538 the benefits from an ROI perspective. 167 00:11:17,908 --> 00:11:18,878 That makes sense, yes. 168 00:11:20,058 --> 00:11:24,008 So now that we've spent a bit of time talking about the people, I'd like 169 00:11:24,008 --> 00:11:27,698 to expand the conversation as you and I were preparing this interview. 170 00:11:28,658 --> 00:11:33,828 We've also talked about the challenges, other organizational challenges 171 00:11:34,048 --> 00:11:39,263 around, for example, the readiness of organizations around data. 172 00:11:39,773 --> 00:11:42,593 Can you elaborate on that for our audience? 173 00:11:43,055 --> 00:11:43,275 Yeah. 174 00:11:43,275 --> 00:11:47,830 And we do, we talk about in the business world, digital transformation, it's 175 00:11:47,830 --> 00:11:52,640 not a new term, artificial intelligence and it's going to help accelerate that. 176 00:11:52,700 --> 00:11:56,120 But what we still have is the pitfalls that have always been there when it 177 00:11:56,120 --> 00:12:02,385 comes to any digital transformation, any technology introduction is technologies 178 00:12:02,385 --> 00:12:06,320 are great, but you have to put, you have an input that you put into the 179 00:12:06,320 --> 00:12:10,700 technology that then allows it to do what, what you purchased it for. 180 00:12:11,130 --> 00:12:16,310 And if you're putting, if your data's not prepared to be that input, if you 181 00:12:16,310 --> 00:12:22,350 have duplicate records, if you have not maintained your records that you're going 182 00:12:22,350 --> 00:12:28,900 to use as those inputs in the technology that you're using, AI being one of 183 00:12:28,900 --> 00:12:35,410 them, then that's going to affect the results you get out of that technology 184 00:12:35,450 --> 00:12:37,470 or out of that artificial intelligence. 185 00:12:38,120 --> 00:12:43,970 No digital transformation or technology is going to clean your data or your inputs. 186 00:12:44,170 --> 00:12:49,430 You could use it to clean, but you need clean data then to be able to do the, 187 00:12:49,640 --> 00:12:51,360 any type of digital transformation. 188 00:12:51,360 --> 00:12:56,710 And so that's where a lot of people in businesses don't. 189 00:12:57,400 --> 00:12:59,570 It's not sexy to invest in that. 190 00:12:59,950 --> 00:13:05,320 It's not sexy to invest in having individuals work on governing, 191 00:13:05,320 --> 00:13:10,580 maintaining, ensuring that there's no duplication, ensuring accuracy, gathering 192 00:13:10,790 --> 00:13:17,020 information and emails and phone numbers, et cetera, from their client base or their 193 00:13:17,020 --> 00:13:19,430 business, to business partners, et cetera. 194 00:13:19,780 --> 00:13:28,210 And, It's an under invested area that then will not allow individuals to 195 00:13:28,210 --> 00:13:33,070 have the return on investment that they were promised for that technology 196 00:13:33,070 --> 00:13:34,170 that they're bringing forward. 197 00:13:34,990 --> 00:13:38,340 And the other thing, besides data, that people have to 198 00:13:38,340 --> 00:13:40,780 really consider is the process. 199 00:13:41,050 --> 00:13:45,080 If you have 10 different processes and you're trying to now go to one 200 00:13:45,120 --> 00:13:49,480 technology that's going to execute that process, then you have 10 different 201 00:13:49,480 --> 00:13:54,590 change managements that you have to work through and standardize, so that 202 00:13:54,820 --> 00:14:00,730 you're not customizing 10 different use cases with the technology. 203 00:14:01,470 --> 00:14:07,060 I think a lot of people spend a lot of money trying to utilize a technology 204 00:14:07,060 --> 00:14:11,160 where they try to customize it for how their process works versus changing their 205 00:14:11,160 --> 00:14:14,020 process to be standard across the board. 206 00:14:14,775 --> 00:14:17,515 And if they did that, they would get more and they would get 207 00:14:17,515 --> 00:14:18,695 more out of that investment. 208 00:14:20,055 --> 00:14:24,535 So those are two things that are very needed in any digital transformation. 209 00:14:24,555 --> 00:14:28,575 Good clean data and good standard processes. 210 00:14:29,034 --> 00:14:34,034 And what do you think is going to be then, the impact, of, smarter tools, 211 00:14:34,064 --> 00:14:40,054 artificial intelligence of some sort, in this digital transformation context? 212 00:14:41,124 --> 00:14:45,084 Do you expect to have these? 213 00:14:45,729 --> 00:14:48,149 exceptions be amplified even more? 214 00:14:48,589 --> 00:14:54,569 Or are you maybe optimistic and hopeful that, because the tools are smarter, 215 00:14:54,949 --> 00:15:00,799 maybe you can detect when a process goes outside of its control boundaries earlier? 216 00:15:02,914 --> 00:15:07,904 Yeah, I think you'll see there's so much more transparency and so much faster 217 00:15:08,214 --> 00:15:09,804 than what we would have seen before. 218 00:15:10,334 --> 00:15:14,934 And artificial intelligence, I hope in individuals will start 219 00:15:14,934 --> 00:15:18,521 to utilize it for that readiness piece for in order to scale right? 220 00:15:18,521 --> 00:15:19,921 You hear AI is awesome. 221 00:15:19,921 --> 00:15:25,611 It's going to save 30%, 40%, et cetera, but it can do that. 222 00:15:26,391 --> 00:15:28,591 And then what you're not hearing from some of the business leaders 223 00:15:28,591 --> 00:15:31,471 that are trying to get that return on investment is that you're not getting 224 00:15:31,471 --> 00:15:33,801 that a 30 percent return on investment. 225 00:15:33,811 --> 00:15:36,531 You're getting a 3 percent return on investment for the 226 00:15:36,531 --> 00:15:38,001 reasons that I'm talking about. 227 00:15:39,589 --> 00:15:45,818 You you can utilize AI for a lot of efficiency on your desktop, but 228 00:15:46,078 --> 00:15:50,308 then what you want to do is you become hungry for automation, more 229 00:15:50,308 --> 00:15:54,298 automation, let it do more of my tasks for me, let me let it automate more. 230 00:15:54,548 --> 00:15:57,768 And that's where people are starting to get hung up in the business 231 00:15:57,768 --> 00:15:59,668 world because that's the hard part. 232 00:15:59,688 --> 00:16:01,568 Now you got to go standardize the process. 233 00:16:01,598 --> 00:16:05,218 Now you got to go clean the data to get that 30 percent return. 234 00:16:05,428 --> 00:16:10,228 So you're going to get a return first just by enabling generative AI with 235 00:16:10,238 --> 00:16:14,668 your team of a hundred because they're going to be able to research faster. 236 00:16:14,668 --> 00:16:18,328 They're going to be able to create content faster. 237 00:16:18,378 --> 00:16:21,888 They're going to be able to pull a lot of great insights in together right 238 00:16:21,888 --> 00:16:27,408 away, but then it stalls out if you're not then going to move into automation. 239 00:16:27,853 --> 00:16:31,183 If you're not ready for automation because you have bad data and process. 240 00:16:31,841 --> 00:16:32,131 Yeah. 241 00:16:33,221 --> 00:16:39,071 I wonder, is that like a risk of over reliance a little bit 242 00:16:39,071 --> 00:16:41,441 of on artificial intelligence? 243 00:16:41,471 --> 00:16:45,951 Because like now there's just a managed, an expectation from management that 244 00:16:46,051 --> 00:16:48,901 we're just gonna keep on automating. 245 00:16:48,901 --> 00:16:52,641 and so does that create a, a dangerous feedback loop? 246 00:16:53,024 --> 00:16:53,854 It does. 247 00:16:53,879 --> 00:16:54,659 I think it does. 248 00:16:54,659 --> 00:17:01,369 I think, the C-suites are really excited about artificial intelligence. 249 00:17:02,049 --> 00:17:05,349 I think that we need to start to think about artificial intelligence more 250 00:17:05,349 --> 00:17:10,979 as a strategic partner on how we do the plan, how we create the roadmap, 251 00:17:11,039 --> 00:17:13,529 what we want to utilize it for. 252 00:17:14,339 --> 00:17:22,929 And be really crisp on what that means for the organization and then to start 253 00:17:22,939 --> 00:17:26,842 to work through those, bottlenecks that you're going to uncover that 254 00:17:26,842 --> 00:17:30,532 don't allow for the automation, which you have to do at some point. 255 00:17:30,682 --> 00:17:35,662 There's got, there was always going to be that point where you're, you'll, people 256 00:17:35,662 --> 00:17:40,712 wanted to, Become more efficient by investing in technology to run processes. 257 00:17:40,792 --> 00:17:45,806 And this is just, because it's so easy to utilize, it uncovers so 258 00:17:45,806 --> 00:17:48,413 many things that we can do with it. 259 00:17:48,413 --> 00:17:51,345 Where, how do you prioritize the return on investment? 260 00:17:51,345 --> 00:17:55,582 A lot of companies are going to get sucked into all those use 261 00:17:55,582 --> 00:18:00,272 cases because they're like, Oh my gosh, yes, we've got to fix that. 262 00:18:00,272 --> 00:18:00,992 We've got to fix that. 263 00:18:00,992 --> 00:18:04,887 But there's a lot of things that we might need to fix, document, 264 00:18:05,267 --> 00:18:10,977 put guardrails around, ensure that everyone's compliant, and get data 265 00:18:10,977 --> 00:18:12,927 prepared, get processes prepared. 266 00:18:12,987 --> 00:18:16,807 And there's a lot of preparation that happens to go to the next level. 267 00:18:16,817 --> 00:18:20,057 So I would say that next level is that automation. 268 00:18:20,097 --> 00:18:23,267 And last year we were talking about automation in 2024. 269 00:18:23,607 --> 00:18:26,227 2025 is talking about the year of the agent. 270 00:18:27,722 --> 00:18:29,992 And so it's happening so fast. 271 00:18:30,192 --> 00:18:31,722 2024 hasn't even caught up. 272 00:18:31,722 --> 00:18:36,065 we started, generative AI in 2022 and people don't even know what, they're 273 00:18:36,255 --> 00:18:41,145 using that of my hundred, just a hundred people that, we're just trying 274 00:18:41,145 --> 00:18:44,395 to get them to use generative AI to make their jobs a little easier. 275 00:18:44,605 --> 00:18:45,955 Not to automate things yet. 276 00:18:46,455 --> 00:18:50,515 Now we're creating those use cases of things to automate, but then 277 00:18:50,515 --> 00:18:52,275 we're running into those bottlenecks. 278 00:18:52,625 --> 00:18:56,825 And now we're on to the next agent where we're replacing, some of the 279 00:18:57,475 --> 00:19:00,565 customer facing individuals with agents. 280 00:19:00,895 --> 00:19:04,215 And that's a whole, that's two steps ahead of where people really 281 00:19:04,215 --> 00:19:05,865 are in running their business. 282 00:19:07,110 --> 00:19:11,390 So it's happening really fast and it's about how the company, where they're 283 00:19:11,390 --> 00:19:14,650 going to, where they're going to make that investment because everyone 284 00:19:14,650 --> 00:19:16,160 wants to jump on the shiny penny. 285 00:19:16,180 --> 00:19:22,330 Every C suite is going to go understand agents and go, great, I can use agents 286 00:19:22,340 --> 00:19:24,270 and augment 20 percent of my team. 287 00:19:24,280 --> 00:19:28,100 And then that team that I free up, I can get them to working on more sales and more 288 00:19:28,100 --> 00:19:30,150 growth and, some of those types of things. 289 00:19:30,150 --> 00:19:30,390 But. 290 00:19:30,845 --> 00:19:35,865 That's three steps ahead from just generative to automation to agent. 291 00:19:36,495 --> 00:19:36,905 Now. 292 00:19:37,625 --> 00:19:40,975 So it sounds a bit like, I don't know, to me, at least as a consultant, that reminds 293 00:19:40,985 --> 00:19:44,975 me of like maturity matrices that we would have applied, you know, for other things. 294 00:19:44,975 --> 00:19:48,435 So is that like one of the approaches or strategies that you use with 295 00:19:48,445 --> 00:19:53,495 leadership to, sequence, let's say, or to talk about the logical sequence 296 00:19:53,785 --> 00:19:55,745 based on the organization's readiness? 297 00:19:56,368 --> 00:20:00,018 Definitely, yeah, I definitely think you need to utilize, that's a great 298 00:20:00,048 --> 00:20:05,168 use case for maturity matrices to inform the C suite and set the right 299 00:20:05,168 --> 00:20:13,088 expectation with them as to when and how it is recommended to utilize AI. 300 00:20:14,443 --> 00:20:19,233 Or any digital transformation, in regards to the company's objectives, but it 301 00:20:19,233 --> 00:20:24,743 really is a discussion because there's a big gap between what the C suites want 302 00:20:24,753 --> 00:20:29,133 to invest in that they're hearing in the market and from their other CEOs, et 303 00:20:29,133 --> 00:20:37,273 cetera, to what reality is in operations of the day to day and you want to have 304 00:20:37,273 --> 00:20:42,003 that alignment They need to understand how long that it will take for that 305 00:20:42,003 --> 00:20:47,678 investment to pay off and they want to have a really good prioritization process. 306 00:20:48,428 --> 00:20:53,678 With understanding all those use cases and where you're going to leverage your 307 00:20:53,758 --> 00:20:56,268 resources to enable those use cases. 308 00:20:56,738 --> 00:21:00,468 And if you don't have that, but you have a lot of departments running on their 309 00:21:00,468 --> 00:21:05,318 own priorities, et cetera, then you're going to make incremental improvements 310 00:21:05,368 --> 00:21:08,708 versus larger scale improvements. 311 00:21:08,758 --> 00:21:15,058 And because AI, as one of those transformation options, is moving so fast, 312 00:21:15,918 --> 00:21:18,728 you, then you're getting further behind. 313 00:21:19,358 --> 00:21:23,528 Sounds like a very cautious, but reasonable approach. 314 00:21:23,738 --> 00:21:24,778 What is exciting. 315 00:21:24,818 --> 00:21:29,878 I will tell you, as an operations leader, it, there's a lot to consider, but it's 316 00:21:29,878 --> 00:21:37,408 exciting that we can, and that we have things like, artificial intelligence 317 00:21:37,428 --> 00:21:39,378 to help us run our operations. 318 00:21:39,828 --> 00:21:44,478 Now we really just got to be that leader that helps the team engage 319 00:21:44,478 --> 00:21:46,678 and enable and move us forward. 320 00:21:46,808 --> 00:21:48,368 And so it is super exciting. 321 00:21:48,368 --> 00:21:53,438 It's the most exciting time to be an operations leader is now, we've seen 322 00:21:53,438 --> 00:21:57,268 great things happen over, over the years, but this is the one that I've 323 00:21:57,268 --> 00:22:01,758 seen over my 20 years in corporate America that I'm the most excited 324 00:22:01,758 --> 00:22:04,858 about what it can do for businesses. 325 00:22:05,497 --> 00:22:11,598 Yeah to, to, to step back, have a broader view and let, the technology 326 00:22:11,598 --> 00:22:14,843 and the tools help you with the, the more operational side of things. 327 00:22:14,933 --> 00:22:16,253 That's, a great summary. 328 00:22:16,563 --> 00:22:22,238 As out as we're about to wrap up, I usually ask for a book, a tool or 329 00:22:22,238 --> 00:22:26,788 a habit that has made a particular impact on you in the last 12 months 330 00:22:28,723 --> 00:22:29,773 Okay, I'm going to give you two. 331 00:22:29,873 --> 00:22:35,043 I'm going to give you this book, written by Reid Hoffman called Superagency where 332 00:22:35,043 --> 00:22:40,428 he really talks about what could possibly go right with the AI future, because 333 00:22:40,428 --> 00:22:46,438 what we talked about in the beginning of this podcast was around people wanting 334 00:22:46,438 --> 00:22:49,208 to adopt, needing to enable themselves. 335 00:22:49,248 --> 00:22:53,138 And so this is like, how do you enable and prepare for the future? 336 00:22:53,518 --> 00:22:57,568 so I I think that's a great read for individuals and businesses that 337 00:22:57,568 --> 00:22:59,018 are in management and leadership. 338 00:22:59,018 --> 00:23:02,838 I also think that what I would start to do is utilize it every 339 00:23:02,838 --> 00:23:06,768 day and ask yourself as a leader, how can AI be my strategic partner? 340 00:23:07,083 --> 00:23:15,893 And start to just ask, prompt, prompt the AI for help to lead your team, through 341 00:23:15,893 --> 00:23:21,863 the change and everything that you need from a strategy perspective, even taking 342 00:23:21,863 --> 00:23:24,843 a picture of your refrigerator and saying, what should I make for dinner based on 343 00:23:24,843 --> 00:23:26,673 the ingredients I have in my refrigerator? 344 00:23:27,263 --> 00:23:31,283 Yeah, it's going to help you strategically manage your 345 00:23:31,283 --> 00:23:33,093 direction with your organization. 346 00:23:33,093 --> 00:23:37,103 It's going to help you personally manage your time better and faster. 347 00:23:37,123 --> 00:23:40,493 And so number two, continue to read, continue to learn. 348 00:23:40,843 --> 00:23:44,983 But my number two is continue to use, continue, use every day, 349 00:23:45,513 --> 00:23:48,463 ask every day what AI can do. 350 00:23:48,473 --> 00:23:49,733 How would AI do this? 351 00:23:50,608 --> 00:23:56,818 Find, simple, practical tools for your everyday life, and that will help in the 352 00:23:56,818 --> 00:23:58,961 long term help with the fears, I guess. 353 00:23:58,961 --> 00:24:00,211 Is that what you're saying, yes? 354 00:24:00,391 --> 00:24:04,252 Absolutely You'll get better and better and you'll be able to utilize it for more 355 00:24:04,252 --> 00:24:09,212 and more as you get better but you have to make it a habit and habits are hard. 356 00:24:09,262 --> 00:24:10,192 They take 21 days. 357 00:24:11,162 --> 00:24:14,017 And that's 21 days consistently. 358 00:24:14,297 --> 00:24:19,544 So that's, that's my advice, is to make it a habit, making utilizing 359 00:24:19,544 --> 00:24:21,104 AI par of your daily habit. 360 00:24:22,019 --> 00:24:22,409 Great. 361 00:24:22,829 --> 00:24:27,419 And last but not least, is there one thing that you see remaining 362 00:24:27,419 --> 00:24:28,729 constant 10 years from now? 363 00:24:28,930 --> 00:24:31,440 Uh, change is constant, change is constant. 364 00:24:31,550 --> 00:24:35,980 And, we talk about soft skills and talent and what type of talents 365 00:24:35,980 --> 00:24:37,110 that we're needing to hire. 366 00:24:37,480 --> 00:24:42,880 We were going to consistently see that change agility is a skill 367 00:24:43,360 --> 00:24:49,100 that is going to be very valuable in human capital in the future. 368 00:24:49,120 --> 00:24:57,330 So if you're one of those individuals that are not able to be adaptive to change, 369 00:24:57,640 --> 00:25:03,730 that's a skill, a soft skill that you'll want to start to work on that muscle. 370 00:25:04,500 --> 00:25:09,080 Because change will continue to happen rapidly and you'll 371 00:25:09,080 --> 00:25:11,080 need to always be ready for it. 372 00:25:11,650 --> 00:25:14,430 I visualized almost like change yoga now. 373 00:25:14,860 --> 00:25:17,380 So that's a great point to finish on. 374 00:25:18,020 --> 00:25:19,590 Nicole, thank you very much. 375 00:25:20,205 --> 00:25:20,725 Thank you. 376 00:25:20,875 --> 00:25:21,675 Have a great day. 377 00:25:22,548 --> 00:25:26,208 Artificial intelligence can make businesses run smoother, but 378 00:25:26,288 --> 00:25:28,338 only if teams are ready for it. 379 00:25:28,938 --> 00:25:33,398 Nicole explained that AI adoption isn't just about installing new tools. 380 00:25:33,688 --> 00:25:37,608 It's about preparing people, fixing broken processes, and making 381 00:25:37,608 --> 00:25:39,928 sure data is clean and usable. 382 00:25:40,342 --> 00:25:43,912 If you're looking for practical ways to get started, Nicole and her team 383 00:25:44,232 --> 00:25:48,702 offer expert coaching and training to help businesses make AI work for them. 384 00:25:49,122 --> 00:25:50,592 The link is in the description. 385 00:25:51,432 --> 00:25:54,592 As always, we have more exciting topics and guests lined up. 386 00:25:54,942 --> 00:25:59,812 So stay tuned for more tales of innovation that inspire, challenge, and transform. 387 00:26:00,352 --> 00:26:02,302 Until next time, peace.