1 00:00:08,650 --> 00:00:12,414 Welcome to the Talent Development Think Tank Podcast, the 2 00:00:12,452 --> 00:00:16,270 number one podcast for learning and talent development professionals. 3 00:00:16,850 --> 00:00:19,950 Now, here's your host, Andy Storch. 4 00:00:20,690 --> 00:00:24,526 Welcome to the talent development. Think Tank podcast. I'm your host, Andy Storch, and 5 00:00:24,548 --> 00:00:27,942 I'm excited that you're joining me for another episode to help you up your game 6 00:00:27,996 --> 00:00:31,766 and improve your capabilities in the world of talent development. And 7 00:00:31,788 --> 00:00:35,606 I got to tell you, over the last several weeks, I've been interviewing lots of 8 00:00:35,628 --> 00:00:39,378 different people from different facets of talent development, lots of great interviews we've 9 00:00:39,394 --> 00:00:43,126 published, and many more coming. And I often ask people about the trend that they're 10 00:00:43,158 --> 00:00:46,486 following or excited about. And it has been consistently 11 00:00:46,678 --> 00:00:50,282 AI across the board for, I'd say the last three to four months, 12 00:00:50,336 --> 00:00:53,920 if not longer. I've been doing this for five years, and I have never 13 00:00:54,290 --> 00:00:58,094 seen anything like this in the past where everybody is 14 00:00:58,132 --> 00:01:01,982 talking about the exact same thing. Certainly there's been some commonalities, there's been some 15 00:01:02,036 --> 00:01:05,550 trends that are mentioned by multiple people, but usually 16 00:01:05,700 --> 00:01:09,266 it's a smattering of lots of different things. Over the course of 17 00:01:09,288 --> 00:01:12,306 several weeks, if I go back and look at the history of this podcast, people 18 00:01:12,328 --> 00:01:15,934 have talked about lots of different things back in 2018, 1921, 19 00:01:15,982 --> 00:01:18,946 22, as I was recording this. But in 20 00:01:18,968 --> 00:01:22,582 2023, it has been almost 100% people 21 00:01:22,636 --> 00:01:26,326 saying AI is the trend that is captivating them, which means that if 22 00:01:26,348 --> 00:01:29,574 they're thinking about it, you're thinking about it. Andy, really, everybody is trying to figure 23 00:01:29,612 --> 00:01:33,210 this out. How do I take advantage of this in talent development? 24 00:01:33,790 --> 00:01:37,126 What does it mean for me in my role? How can we best utilize 25 00:01:37,238 --> 00:01:40,918 this new technology that's out there's so many different platforms and 26 00:01:40,944 --> 00:01:44,702 things going on. So I have two different things for you. Number 27 00:01:44,756 --> 00:01:48,170 one is that I am hosting a webinar 28 00:01:48,330 --> 00:01:52,094 coming up on August 29 at 01:00 29 00:01:52,132 --> 00:01:55,558 P.m. Eastern Time with my friend Josh Ermler 30 00:01:55,594 --> 00:01:59,106 about AI in talent development and how learning and 31 00:01:59,128 --> 00:02:02,626 development professionals are using AI to get five X more work done and 32 00:02:02,648 --> 00:02:06,462 lowering their expenses, all while developing a healthier work life balance. 33 00:02:06,526 --> 00:02:09,442 This is going to be really fantastic. It's really the first time I've ever done 34 00:02:09,576 --> 00:02:13,094 a webinar before, and hopefully you have time to catch it by the time you 35 00:02:13,132 --> 00:02:16,438 hear this or at least come sign up and get the replay because we're going 36 00:02:16,444 --> 00:02:19,674 to cover some great stuff. You can find out all the information for that at 37 00:02:19,712 --> 00:02:22,886 TDT us slash AI. That's 38 00:02:22,918 --> 00:02:26,666 TDTT us slash AI. And 39 00:02:26,688 --> 00:02:30,374 then the other resource that I'm giving you is this interview today, because my interview 40 00:02:30,422 --> 00:02:34,234 today is all about leveraging AI in talent development 41 00:02:34,282 --> 00:02:37,838 and talent acquisition. My guest today is Sarah Tilly, who is the 42 00:02:37,844 --> 00:02:41,326 Senior Vice President of Global Talent Acquisition and Development for 43 00:02:41,348 --> 00:02:44,802 ServiceNow, the digital workflow company with over 24,000 44 00:02:44,856 --> 00:02:48,546 employees. In her role, Sarah is responsible for leading a 45 00:02:48,568 --> 00:02:51,966 newly integrated talent organization which includes all external 46 00:02:51,998 --> 00:02:55,726 recruitment and internal mobility, learning and development inclusive 47 00:02:55,758 --> 00:02:59,366 of leadership development, talent and succession planning, and all efforts to 48 00:02:59,388 --> 00:03:03,058 lead ServiceNow forward on a skills based talent strategy. Sarah's 49 00:03:03,074 --> 00:03:06,694 team is responsible for holistically looking across the talent lifecycle for 50 00:03:06,732 --> 00:03:10,426 employees to ensure delivery on what matters most to them, while also meeting the 51 00:03:10,448 --> 00:03:13,786 talent needs of ServiceNow's critical business priorities. Prior to 52 00:03:13,808 --> 00:03:17,654 ServiceNow, Sarah spent 16 years at the Walt Disney Company, where she led enterprise 53 00:03:17,702 --> 00:03:21,226 talent strategies and efforts including centralized talent acquisition and 54 00:03:21,248 --> 00:03:24,990 sourcing functions, corporate talent management and diversity and inclusion, and the opportunity 55 00:03:25,060 --> 00:03:28,874 to lead several company wide functional talent and talent acquisition strategies. 56 00:03:28,922 --> 00:03:32,666 She has done a lot of really interesting stuff, and throughout her career, Sarah 57 00:03:32,698 --> 00:03:36,434 has earned a stellar reputation for creating new opportunities for top talent and 58 00:03:36,472 --> 00:03:40,030 fostering an inclusive environment where teams can thrive. 59 00:03:40,190 --> 00:03:43,966 As a working mom, she understands the importance of flexibility and tailored career 60 00:03:43,998 --> 00:03:47,778 paths for all people. And Sarah has a Bachelor's degree in Psychology from the University 61 00:03:47,794 --> 00:03:51,010 of Arkansas and a PHR professional in Human Resources 62 00:03:51,090 --> 00:03:54,422 certification as well. And Sarah, since she came to 63 00:03:54,476 --> 00:03:58,230 ServiceNow, has really dived deep into all things AI 64 00:03:58,310 --> 00:04:01,974 and how ServiceNow especially is using AI 65 00:04:02,022 --> 00:04:05,818 to help themselves. Andy other organizations with talent development and 66 00:04:05,824 --> 00:04:09,398 talent acquisition. In this conversation we are covering 67 00:04:09,574 --> 00:04:13,274 lots of topics around this, like how organizations can 68 00:04:13,312 --> 00:04:16,634 start to think about the skills that are needed in the future, how to assess 69 00:04:16,682 --> 00:04:20,206 what skills are needed and what skills already exist in an organization, how you can 70 00:04:20,228 --> 00:04:23,982 leverage AI for a talent. You know, 71 00:04:24,036 --> 00:04:27,746 fair to note that Sarah comes from ServiceNow, which is 72 00:04:27,768 --> 00:04:31,394 a big player in this space. They acquired a company called Hitch, which is 73 00:04:31,432 --> 00:04:35,058 involved in building talent marketplaces and the platforms that 74 00:04:35,144 --> 00:04:38,962 you may need to build your own talent marketplace inside your company. So 75 00:04:39,016 --> 00:04:41,650 take it with a grain of salt. It is coming from someone in an organization 76 00:04:41,730 --> 00:04:45,126 that is heavily involved in this, but I thought it would be great to talk 77 00:04:45,148 --> 00:04:48,422 to somebody who's right in it, seeing what's going on in her own 78 00:04:48,556 --> 00:04:52,154 organization with many thousands of people, as well as working with other 79 00:04:52,192 --> 00:04:55,978 organizations as well. So I hope you enjoy this conversation. I'm going 80 00:04:55,984 --> 00:04:59,466 to invite Sarah also to come speak in the talent development think tank community to 81 00:04:59,488 --> 00:05:02,998 share more about what's going on, because just so many interesting avenues 82 00:05:03,094 --> 00:05:06,398 to explore here. So keep an eye out for that if you're a member. If 83 00:05:06,404 --> 00:05:09,886 you're not, come check us out. Our website is TDTT us 84 00:05:09,988 --> 00:05:13,614 slash community. All right, without further ado, here is my interview with 85 00:05:13,652 --> 00:05:17,294 Sarah Tilly from ServiceNow. All right. I'm joined now by 86 00:05:17,332 --> 00:05:20,974 Sarah Tilley, who is senior vice president of global talent acquisition 87 00:05:21,022 --> 00:05:24,642 and development for ServiceNow. Sarah, welcome to the show. 88 00:05:24,776 --> 00:05:28,514 Thank you, Andy. I'm thrilled to be here. I am really excited 89 00:05:28,562 --> 00:05:31,862 to have you on because I know that not only are you in a very 90 00:05:31,916 --> 00:05:35,686 senior role in talent acquisition and talent development, and 91 00:05:35,708 --> 00:05:39,494 I always love interviewing and having conversations with people 92 00:05:39,532 --> 00:05:43,322 who are in it and leading it and thinking about the strategy behind 93 00:05:43,376 --> 00:05:46,986 it. Andy doing different things because that's what the show is all about, sharing the 94 00:05:47,008 --> 00:05:50,746 strategies and the tactics that are working and even not working so that we 95 00:05:50,768 --> 00:05:54,174 can help other people in talent development improve their skills and 96 00:05:54,212 --> 00:05:58,062 abilities and find more success in their careers. But I'm especially 97 00:05:58,116 --> 00:06:01,742 excited because I know that you have been heavily immersed in 98 00:06:01,876 --> 00:06:05,726 AI and using that for developing, hiring the right 99 00:06:05,748 --> 00:06:09,566 people, developing people, and identifying the skills of the future. And that's 100 00:06:09,598 --> 00:06:13,246 something that's on just about everybody's mind, no matter what level they're 101 00:06:13,278 --> 00:06:16,738 at. So I'm excited to dig into that. But before we do, I'd love to 102 00:06:16,744 --> 00:06:20,262 just start with a little bit of background. How did you get into this field 103 00:06:20,316 --> 00:06:23,720 of talent development and acquisition in the first place? Sure, 104 00:06:24,810 --> 00:06:28,162 like, I think a lot of people, it wasn't the 105 00:06:28,236 --> 00:06:31,674 career course that I mapped out for 106 00:06:31,712 --> 00:06:35,114 myself. Found my way into talent acquisition, started 107 00:06:35,152 --> 00:06:38,506 working on the agency side for a couple of years outside of 108 00:06:38,528 --> 00:06:42,246 college, then moved to a large retained search firm, Hydra. 109 00:06:42,278 --> 00:06:45,882 Andy struggles in their media and entertainment practice, then 110 00:06:45,936 --> 00:06:49,646 in house for almost five years at Warner Bros. Entertainment. And then the 111 00:06:49,668 --> 00:06:53,140 last well, not the last year and a half at ServiceNow, 112 00:06:53,510 --> 00:06:57,026 but about 16 years at the Walt Disney Company, 113 00:06:57,208 --> 00:07:00,110 where I oversaw a couple of enterprise talent 114 00:07:00,190 --> 00:07:03,634 functions. So I think I've always had 115 00:07:03,672 --> 00:07:07,506 1ft squarely planted in the talent acquisition side of the 116 00:07:07,528 --> 00:07:11,014 house. When I was at Disney, there were some of the work that we did. 117 00:07:11,052 --> 00:07:14,374 So, for example, centralizing the recruitment of 118 00:07:14,412 --> 00:07:17,914 technologists across all of the business units. So if you think 119 00:07:17,952 --> 00:07:21,786 about an engineer in our theme parks or 120 00:07:21,888 --> 00:07:25,482 ESPN or Pixar, whatever, it was 121 00:07:25,536 --> 00:07:28,922 basically realized that we needed to be a lot more 122 00:07:28,976 --> 00:07:32,686 coordinated and organized. And as we got clear on how do 123 00:07:32,708 --> 00:07:36,394 you compete for technologists from a hiring 124 00:07:36,442 --> 00:07:40,094 perspective, we also realized, oh, okay, there's a lot that we need to do 125 00:07:40,132 --> 00:07:43,210 from a talent development perspective to attract 126 00:07:43,370 --> 00:07:46,994 technologists, to keep them, et cetera. So that sort of expanded my 127 00:07:47,032 --> 00:07:50,126 role into some talent management leadership 128 00:07:50,158 --> 00:07:53,906 responsibilities and then some other hats I wore on and 129 00:07:53,928 --> 00:07:57,606 off in the HR function over the years. So made the 130 00:07:57,628 --> 00:08:00,630 move to ServiceNow, as I mentioned, about a year and a half ago. 131 00:08:00,780 --> 00:08:04,614 And it was really the experience with 132 00:08:04,652 --> 00:08:08,486 the technology talent that made me kind of lift my 133 00:08:08,508 --> 00:08:12,154 head up and think, all right, if I were to think about something 134 00:08:12,352 --> 00:08:15,802 beyond Disney, which I absolutely loved my 135 00:08:15,856 --> 00:08:19,594 experience there, and the people it was. Okay, I think I'm going to go 136 00:08:19,632 --> 00:08:23,258 for a pure play technology organization and 137 00:08:23,344 --> 00:08:26,638 got introduced to Jackie Kenny, who is the chief people officer. We know a lot 138 00:08:26,644 --> 00:08:30,174 of the same people. And then the rest was history. Really? Yeah. Oh, 139 00:08:30,212 --> 00:08:33,806 that's curious. You know, Disney has such a strong brand and 140 00:08:33,828 --> 00:08:37,586 reputation, not just a consumer brand, but I think on the 141 00:08:37,608 --> 00:08:41,266 working side of having a really strong culture that maybe some 142 00:08:41,288 --> 00:08:44,514 people don't like, a lot of people love. And I'm sure there are many things 143 00:08:44,552 --> 00:08:48,134 you learned from working in that experience. What are some things that you learned from 144 00:08:48,252 --> 00:08:52,054 that very strong Disney working culture that you take 145 00:08:52,092 --> 00:08:54,840 with you? Yeah, it's very strong. 146 00:08:56,250 --> 00:08:59,946 A very strong culture in terms of, I 147 00:08:59,968 --> 00:09:03,562 think the people dynamic of it. 148 00:09:03,696 --> 00:09:06,140 Everyone really supports one another. 149 00:09:06,830 --> 00:09:10,494 Andy, you're very much expected to 150 00:09:10,612 --> 00:09:14,346 operate in a collaborative way. That's how the connected 151 00:09:14,378 --> 00:09:16,960 business strategy comes to life. If you think about 152 00:09:18,610 --> 00:09:22,014 intellectual property that sort of spans across 153 00:09:22,212 --> 00:09:25,860 all of the different business units, trying to think of a recent one, and 154 00:09:26,230 --> 00:09:29,326 Frozen keeps popping in my head, which is not super recent, 155 00:09:29,438 --> 00:09:32,962 but it's a 156 00:09:33,096 --> 00:09:36,754 film, television, consumer product, theme park 157 00:09:36,802 --> 00:09:40,294 experiences, et cetera. So you have to really be connected to create the 158 00:09:40,332 --> 00:09:44,134 franchises across all. So it's very collaborative, it's a very 159 00:09:44,172 --> 00:09:47,926 optimistic culture, very polite. I think 160 00:09:47,948 --> 00:09:51,546 I already mentioned the word supportive. And some of the things that drew me to 161 00:09:51,568 --> 00:09:55,146 ServiceNow from a cultural perspective, what I definitely learned at 162 00:09:55,168 --> 00:09:58,810 Disney is there's a very high bar for quality. So 163 00:09:58,880 --> 00:10:02,622 everything that you do and it's something that you learn pretty quickly. In fact, 164 00:10:02,676 --> 00:10:06,350 my first year, I thought, I don't know if I'm going to make it 165 00:10:06,420 --> 00:10:09,360 because there's a lot of 166 00:10:09,890 --> 00:10:13,454 attention to every detail, because the 167 00:10:13,492 --> 00:10:16,340 creative process sort of bleeds into everything, 168 00:10:16,790 --> 00:10:20,610 where you really have to have a high bar. And so 169 00:10:20,680 --> 00:10:24,434 I would say that's definitely what I learned. Right? Yeah, it makes sense. I've heard 170 00:10:24,472 --> 00:10:27,918 that about the culture, Andy, the standard of 171 00:10:27,944 --> 00:10:31,554 quality and things like that, which comes with pros and cons. I'm curious 172 00:10:31,602 --> 00:10:35,446 after moving to ServiceNow, if I understand correctly, it looks like 173 00:10:35,468 --> 00:10:39,186 you started in running talent acquisition, but then picked up talent 174 00:10:39,218 --> 00:10:42,682 development. I work with a lot of different organizations, and 175 00:10:42,816 --> 00:10:46,362 often those two are connected but run by different people. 176 00:10:46,496 --> 00:10:50,154 How did that come about, that you ended up overseeing both. Yeah, so I 177 00:10:50,192 --> 00:10:53,662 definitely didn't expect, when I joined, to be 178 00:10:53,716 --> 00:10:57,546 leading both, but there were some changes that happened in the organization, 179 00:10:57,658 --> 00:11:01,402 and Jackie and I started talking about what we felt 180 00:11:01,466 --> 00:11:04,990 were the benefits. Andy really just pressing ourselves, 181 00:11:05,070 --> 00:11:08,674 like, does this make sense? Do we lose focus or 182 00:11:08,792 --> 00:11:12,270 do we gain more by having an integrated organization? 183 00:11:12,430 --> 00:11:16,162 And we really ruminated on that for a little while and realized, okay, 184 00:11:16,216 --> 00:11:19,330 now we think we have a real opportunity, especially with 185 00:11:19,400 --> 00:11:23,174 Skills. I mean, skills was kind of the motivating factor, too, as 186 00:11:23,212 --> 00:11:26,934 we think about it, a skills intelligence strategy to say, all right, 187 00:11:26,972 --> 00:11:30,762 what is the connected thread from 188 00:11:30,816 --> 00:11:34,374 everything from branding to executive 189 00:11:34,422 --> 00:11:35,900 development. Really? 190 00:11:38,670 --> 00:11:42,266 Andy, we said, to your point, I think there was a lot of 191 00:11:42,288 --> 00:11:46,094 collaboration that was happening, but we felt like we could drive 192 00:11:46,132 --> 00:11:49,790 it a little bit further and a little bit faster with an integrated organization. 193 00:11:50,130 --> 00:11:53,950 And I've realized it is a bit of a growing trend and 194 00:11:54,020 --> 00:11:57,858 talking to some really talented colleagues in the industry. But I think a 195 00:11:57,864 --> 00:12:01,694 lot of people are still trying to figure out how is it truly integrated 196 00:12:01,742 --> 00:12:05,426 and not just on paper. And I do think the skills piece of 197 00:12:05,448 --> 00:12:09,086 it is the key. Yeah, it's all part of the employee 198 00:12:09,118 --> 00:12:12,806 lifecycle, right? You've got the acquisition, bringing people in, and then we want to keep 199 00:12:12,828 --> 00:12:15,958 them not only engaged, but keep developing them so they feel like they're growing in 200 00:12:15,964 --> 00:12:19,762 their careers and they stay engaged and with the organization longer. So 201 00:12:19,836 --> 00:12:23,626 it's obviously all connected. You mentioned skills. This is something that's coming 202 00:12:23,648 --> 00:12:26,870 up more and more often. Skills mapping, skills development, 203 00:12:26,950 --> 00:12:30,474 identifying skills of the future. Another topic that has been coming 204 00:12:30,512 --> 00:12:33,918 up almost every week when I run interviews is 205 00:12:34,004 --> 00:12:37,854 AI, of course, right, in generative AI. And I know it's something that you and 206 00:12:37,892 --> 00:12:41,610 your team has been leaning into and using a lot. So I'm curious, 207 00:12:41,770 --> 00:12:45,314 how has AI impacted this and how do you think about 208 00:12:45,352 --> 00:12:48,500 skills development in the workforce? So I think 209 00:12:49,030 --> 00:12:52,834 it's interesting because this is 210 00:12:52,872 --> 00:12:56,402 the topic of conversation. Right. I attended, iforcp 211 00:12:56,546 --> 00:12:59,800 I read the white papers, all the 212 00:13:00,410 --> 00:13:03,814 conferences, all the conversations that are happening. And at 213 00:13:03,852 --> 00:13:07,574 first I was a little intimidated thinking some of these 214 00:13:07,612 --> 00:13:11,114 organizations seem like they're pretty far along on their 215 00:13:11,152 --> 00:13:14,986 journey. And then as you look under the hood a little 216 00:13:15,008 --> 00:13:18,826 bit more, they conceptually know where they want 217 00:13:18,848 --> 00:13:22,346 to go. Some organizations, I would say some just see it as kind of an 218 00:13:22,368 --> 00:13:26,174 abstract idea that's elusive and they can't really figure out how to get there. 219 00:13:26,212 --> 00:13:29,726 Yeah, we'll let others figure this out first or something. Yeah. I think 220 00:13:29,828 --> 00:13:33,594 what has become abundantly clear is that you can't 221 00:13:33,642 --> 00:13:37,266 do it without the underlying technology. I mean, that seems like a no 222 00:13:37,288 --> 00:13:40,980 brainer, but I think a lot of people were starting from a very manual process 223 00:13:41,510 --> 00:13:44,580 in terms of, okay, how do we actually 224 00:13:45,050 --> 00:13:48,774 get to a set of skills as a baseline? Right? And I 225 00:13:48,812 --> 00:13:52,358 think you've got to have a skills intelligence system 226 00:13:52,524 --> 00:13:56,214 that helps predict, identify, and 227 00:13:56,332 --> 00:14:00,006 ultimately tie to how you deliver the talent. 228 00:14:00,118 --> 00:14:03,926 And so I think you've got to have a skills intelligence system that's actually powered 229 00:14:03,958 --> 00:14:06,170 by AI and ML 230 00:14:07,550 --> 00:14:10,998 and then that helps bring everything together and connect the various 231 00:14:11,174 --> 00:14:13,600 systems and teams. So I think 232 00:14:15,650 --> 00:14:19,086 if I'm going to get a little technical here, I guess I'm going to try 233 00:14:19,108 --> 00:14:22,414 to keep it simple. And by no means am I the 234 00:14:22,452 --> 00:14:25,898 expert. I think this idea of 235 00:14:26,084 --> 00:14:29,442 skills intelligence strategy and how do you take it from 236 00:14:29,496 --> 00:14:33,026 abstract into reality? First and 237 00:14:33,048 --> 00:14:36,814 foremost, I think organizations, some organizations have realized, 238 00:14:36,862 --> 00:14:40,486 all right, we actually do have a lot of information on the 239 00:14:40,508 --> 00:14:43,942 skills of our employees, like a lot more than we 240 00:14:43,996 --> 00:14:47,506 realized. And it sits in so many different places. But I'll take an 241 00:14:47,548 --> 00:14:51,242 obvious example. So if you think about a job 242 00:14:51,296 --> 00:14:54,714 description that correlates with someone in 243 00:14:54,752 --> 00:14:58,586 role, so you can pretty much determine what are the 244 00:14:58,608 --> 00:15:02,394 baseline skills that this person has because they're in this role. 245 00:15:02,522 --> 00:15:05,854 And then using technology to 246 00:15:05,892 --> 00:15:09,066 actually pull and aggregate to create a skills 247 00:15:09,098 --> 00:15:12,722 architecture. And so I think it's like one using 248 00:15:12,776 --> 00:15:16,514 AI to pull from all the existing places where, you know, you 249 00:15:16,552 --> 00:15:20,206 have some information on skills. Again, there's external 250 00:15:20,318 --> 00:15:23,922 resources and databases too that 251 00:15:23,976 --> 00:15:27,766 hold information around skills. But at the end of the day, 252 00:15:27,948 --> 00:15:31,462 what you're trying to do is break down every single job 253 00:15:31,516 --> 00:15:35,266 description into a set of skills that ultimately rolls 254 00:15:35,298 --> 00:15:38,454 up into the skills architecture and then break down 255 00:15:38,572 --> 00:15:42,266 every individual into a set of skills. Like how do you 256 00:15:42,288 --> 00:15:45,660 help them some of it has to come from them. 257 00:15:46,430 --> 00:15:49,706 How do you help them break down their experience, their 258 00:15:49,728 --> 00:15:52,830 capabilities into a set of skills? And then you use 259 00:15:52,900 --> 00:15:56,686 AI to really ensure that you're doing all the things that you want 260 00:15:56,708 --> 00:16:00,126 to do for them, for their leaders, and 261 00:16:00,148 --> 00:16:03,914 ultimately for the organization. Yeah. And because you're 262 00:16:03,962 --> 00:16:07,730 talking about new skills that are being identified and needed 263 00:16:07,800 --> 00:16:11,474 in the future as things continue to change, it's not just what 264 00:16:11,512 --> 00:16:15,060 skills already exist in the organization, right, but what potential do you have, 265 00:16:15,430 --> 00:16:19,254 what are people interested in? You really need to find out from the people 266 00:16:19,292 --> 00:16:23,062 that work in your organization. So you've got to find a way to create 267 00:16:23,116 --> 00:16:26,214 some type of talent marketplace or platform where people can 268 00:16:26,332 --> 00:16:30,086 identify and look for those roles or those 269 00:16:30,108 --> 00:16:33,754 upskilling or development opportunities. Right. Do you think about how do we take the people 270 00:16:33,792 --> 00:16:36,662 that we have and help them get to where they want to go in roles 271 00:16:36,726 --> 00:16:40,154 that will also provide more value to our organization? Yeah, 272 00:16:40,192 --> 00:16:44,014 100%. So there's some of the back end work that is 273 00:16:44,052 --> 00:16:47,070 required that I was referencing and then 274 00:16:47,140 --> 00:16:50,958 ultimately you're using that to feed into or we are right, 275 00:16:51,044 --> 00:16:54,402 and we do have the very fortunate benefit of 276 00:16:54,456 --> 00:16:57,826 having the ServiceNow platform. And 277 00:16:58,008 --> 00:17:01,634 we acquired a company called a Hitch last year which 278 00:17:01,752 --> 00:17:05,362 had already figured a lot of this, how to leverage 279 00:17:05,426 --> 00:17:08,982 AI to match skills to roles, to 280 00:17:09,036 --> 00:17:12,614 trainings, to opportunities, so that you can more 281 00:17:12,652 --> 00:17:16,326 effectively and intentionally develop the talent, the 282 00:17:16,348 --> 00:17:19,878 skills that they want right. For today and the skills that the organization 283 00:17:19,974 --> 00:17:23,370 needs for the future. So we reengineered 284 00:17:23,870 --> 00:17:27,626 the Hitch technology into our platform. So I 285 00:17:27,648 --> 00:17:31,306 think that is part of the reason that we are so far in front of 286 00:17:31,408 --> 00:17:35,134 this and ahead of the game is because we have that advantage. But 287 00:17:35,172 --> 00:17:38,862 ultimately all of that, our platform feeds into 288 00:17:38,916 --> 00:17:42,746 apps that do what you're talking about. So they create a connected 289 00:17:42,778 --> 00:17:46,498 experience for employees to say, all right, because here's the 290 00:17:46,504 --> 00:17:50,242 skills that we have. Right, and so to your point, it's matching to existing needs 291 00:17:50,376 --> 00:17:53,842 if I'm our CTO and I 292 00:17:53,896 --> 00:17:57,630 say we need to strengthen our cybersecurity, I'm making this up, right? We need to 293 00:17:57,640 --> 00:18:01,414 strengthen our cybersecurity skills, then today you're limited to those people 294 00:18:01,452 --> 00:18:05,174 that have that title, right? And this is going to open 295 00:18:05,212 --> 00:18:08,578 up a whole world of people that have some skills 296 00:18:08,674 --> 00:18:12,298 that wouldn't be reflected in their title. So you can use it to help 297 00:18:12,384 --> 00:18:16,186 meet the business needs of today. But to your point, then you 298 00:18:16,208 --> 00:18:18,902 can see, all right, ultimately 299 00:18:19,046 --> 00:18:22,702 organizations will have the inventory, a full 300 00:18:22,756 --> 00:18:26,430 picture, what skills exist across the organization, 301 00:18:26,770 --> 00:18:30,606 and then where the gaps are. And then in turn, you can also use 302 00:18:30,628 --> 00:18:33,920 the skills intelligence for people's aspirations. So 303 00:18:34,230 --> 00:18:37,618 here's what I have today, here's what I want. Oh, 304 00:18:37,704 --> 00:18:41,362 boom. AI serves up well, then 305 00:18:41,496 --> 00:18:45,122 here's how you can develop those things, whether it be content from a training 306 00:18:45,176 --> 00:18:48,514 perspective or programs or serving up matching 307 00:18:48,562 --> 00:18:52,178 mentors, et cetera. So I think it's meeting 308 00:18:52,274 --> 00:18:55,990 the needs of today but also tomorrow. And that's really 309 00:18:56,060 --> 00:18:59,606 how we think about it. And of course, naturally, because and I'm not trying to 310 00:18:59,708 --> 00:19:03,306 shamelessly plug service now, but we can't talk about it 311 00:19:03,328 --> 00:19:07,046 without talking about our platform because it's underpinning everything we're 312 00:19:07,078 --> 00:19:10,526 doing. But then we're also selling it to customers. So we think about it, of 313 00:19:10,548 --> 00:19:14,270 course, from an employee perspective and also 314 00:19:14,340 --> 00:19:18,026 from a manager hands on manager perspective. 315 00:19:18,138 --> 00:19:21,642 And then at the C suite level, organizations. 316 00:19:21,786 --> 00:19:25,060 So how are you quantifying within 317 00:19:25,510 --> 00:19:29,074 those three areas and what are the priorities? Because I think 318 00:19:29,112 --> 00:19:32,354 there's a lot of emphasis on the employee experience, 319 00:19:32,472 --> 00:19:36,322 naturally. So tremendous benefits that are being less talked 320 00:19:36,376 --> 00:19:40,130 about for leaders and C suite 321 00:19:40,290 --> 00:19:43,782 executives. Yeah. Oh, absolutely. CEOs even, 322 00:19:43,916 --> 00:19:47,622 right. It's every level, but especially at the top. And 323 00:19:47,676 --> 00:19:51,398 I didn't realize I should have done more homework. That ServiceNow 324 00:19:51,414 --> 00:19:55,126 had acquired hitch. We had the hitch. Founder 325 00:19:55,158 --> 00:19:58,938 Kelly Steven Waste. Oh, I know Kelly well. Podcast quite a 326 00:19:58,944 --> 00:20:02,646 while back. I looked it up, episode 164 that was published 327 00:20:02,678 --> 00:20:06,158 in June of 2020. So just over three years ago, 328 00:20:06,324 --> 00:20:09,646 she was on here and has obviously done some remarkable work there in 329 00:20:09,668 --> 00:20:13,202 developing that platform. Andy, of course, we've been talking with other people about 330 00:20:13,256 --> 00:20:16,926 different platforms and companies that are looking to develop their talent 331 00:20:16,958 --> 00:20:20,274 marketplaces. Talent mobility being a hot topic. Getting back to 332 00:20:20,312 --> 00:20:23,774 skills for leaders and talent development 333 00:20:23,822 --> 00:20:27,526 professionals, listening and thinking about this, what's the best way for them to 334 00:20:27,548 --> 00:20:31,394 go about maybe don't have all the technology yet, but how can leaders assess 335 00:20:31,522 --> 00:20:35,126 the level of skills and what's needed for the 336 00:20:35,148 --> 00:20:37,240 future? That's a good question. 337 00:20:39,710 --> 00:20:43,258 We're customer zero for ourselves on some of this stuff, 338 00:20:43,344 --> 00:20:47,002 too. But I think it really is about 339 00:20:47,136 --> 00:20:50,620 starting to get your arms around 340 00:20:50,990 --> 00:20:54,686 what intel you have already. Because I 341 00:20:54,708 --> 00:20:58,222 think about some of the conversations that I've been in over the 342 00:20:58,276 --> 00:21:02,122 years, and I think a lot of organizations sort of default 343 00:21:02,186 --> 00:21:05,854 to self reporting, right, for individuals 344 00:21:05,902 --> 00:21:09,314 from a skills perspective, which I think is a 345 00:21:09,352 --> 00:21:13,010 component in it. But I think it's again starting 346 00:21:13,080 --> 00:21:16,742 to think about how do we stockpile what we 347 00:21:16,796 --> 00:21:19,750 already know about all of our 348 00:21:19,820 --> 00:21:23,400 employees. I know you said without the technology, 349 00:21:23,930 --> 00:21:27,206 but I think if without the technology, it's going to 350 00:21:27,228 --> 00:21:30,422 be years and years of a very manual 351 00:21:30,486 --> 00:21:33,962 process. So of course I think ours is the best. 352 00:21:34,016 --> 00:21:37,706 But whatever the approach, I don't think you could do it 353 00:21:37,728 --> 00:21:41,358 without a digital platform to help sort of pull, 354 00:21:41,444 --> 00:21:45,006 aggregate, analyze. But I think it starts with getting your 355 00:21:45,028 --> 00:21:48,702 arms around all of the information, just really 356 00:21:48,756 --> 00:21:52,142 thinking creatively about all the places where you already have 357 00:21:52,276 --> 00:21:56,058 skills, intel. You need some form of data analytics, basically like take, let's 358 00:21:56,074 --> 00:21:59,714 take all the data we have, whatever technology or platform you're using, find 359 00:21:59,752 --> 00:22:03,506 somebody in your organization who has some skills around analytics so that we can 360 00:22:03,528 --> 00:22:07,134 look at this data and see, okay, what skills are becoming more valuable? 361 00:22:07,262 --> 00:22:10,982 What are people talking about, what are leaders asking for? What's more common 362 00:22:11,036 --> 00:22:14,738 in the roles that we're posting? Are there ways that we can leverage the skills 363 00:22:14,754 --> 00:22:18,426 and abilities and experience we already have in this organization before we start looking to 364 00:22:18,448 --> 00:22:22,006 hire from outside? Yes, that's right. So I'm 365 00:22:22,038 --> 00:22:25,622 curious, I know you work obviously there directly 366 00:22:25,686 --> 00:22:29,210 running talent acquisition, talent development there in HR, but also 367 00:22:29,360 --> 00:22:33,162 talk with people from other organizations. How are the best HR 368 00:22:33,226 --> 00:22:36,474 leaders using AI powered skills 369 00:22:36,522 --> 00:22:40,366 intelligence or AI tools in general to be more effective in 370 00:22:40,388 --> 00:22:43,474 what they're doing? Well, I think what we've obviously 371 00:22:43,592 --> 00:22:47,426 seen is that where I see 372 00:22:47,608 --> 00:22:51,346 the most obviously is organizations that 373 00:22:51,368 --> 00:22:54,914 are using our platform. But I will 374 00:22:54,952 --> 00:22:58,646 say it really is about, okay, there's the 375 00:22:58,668 --> 00:23:02,486 skills piece of it, right? But even if you were to do something and 376 00:23:02,508 --> 00:23:05,894 this is where I think organizations I was just having a conversation this 377 00:23:05,932 --> 00:23:08,230 week, organizations 378 00:23:08,590 --> 00:23:12,362 recognizing that there has to be, 379 00:23:12,416 --> 00:23:16,202 even if it's a portal, right, something way more simple for 380 00:23:16,256 --> 00:23:19,890 people, to employees to access all that's 381 00:23:19,990 --> 00:23:23,742 available to them. So I think one is, even 382 00:23:23,796 --> 00:23:27,406 without the skills intelligence piece of it, how are 383 00:23:27,428 --> 00:23:30,974 you getting a more coordinated sort of 384 00:23:31,012 --> 00:23:34,794 approach to everything that's available to 385 00:23:34,852 --> 00:23:38,386 employees, to leaders? And I think there's some creative things 386 00:23:38,488 --> 00:23:42,270 that some organizations are doing in pockets to use AI 387 00:23:42,350 --> 00:23:46,166 for that. I had another thought too on that and 388 00:23:46,188 --> 00:23:49,000 I forgot it. I think 389 00:23:49,850 --> 00:23:52,998 what I'm seeing too is people are getting a lot 390 00:23:53,084 --> 00:23:56,886 smarter about how to build 391 00:23:56,988 --> 00:24:00,234 the business case for it. So I think, 392 00:24:00,272 --> 00:24:04,026 again, I can't give a lot of examples of like, all right, this is 393 00:24:04,048 --> 00:24:07,322 where it's really cutting edge outside, of 394 00:24:07,376 --> 00:24:11,166 course, the work that we're a part of. But I 395 00:24:11,188 --> 00:24:14,942 do see more and more people getting smarter about 396 00:24:15,076 --> 00:24:18,334 how to articulate the business case 397 00:24:18,532 --> 00:24:22,090 for gen AI, for a skills intelligence 398 00:24:22,170 --> 00:24:24,980 strategy. And I think it is 399 00:24:25,510 --> 00:24:28,926 A, acknowledging that HR 400 00:24:29,118 --> 00:24:32,958 is moving away from being transactional, 401 00:24:33,134 --> 00:24:36,358 like difficult to measure and 402 00:24:36,444 --> 00:24:39,762 really understanding. Okay, we've got the skills 403 00:24:39,826 --> 00:24:43,378 shortage. The reality is we have that globally 404 00:24:43,554 --> 00:24:47,126 and helping the most senior business leaders in the 405 00:24:47,148 --> 00:24:50,826 organization understand, hey, the business strategy is the 406 00:24:50,848 --> 00:24:54,650 talent strategy, and the talent strategy is the business strategy. And without 407 00:24:54,720 --> 00:24:58,330 this, we're not going to get very far on our business 408 00:24:58,400 --> 00:25:02,206 strategy. So I'd say that's kind of the thing that 409 00:25:02,228 --> 00:25:05,486 I'm impressed by in my conversations with 410 00:25:05,588 --> 00:25:09,374 organizations. Yeah. And I think it's going to be interesting because 411 00:25:09,572 --> 00:25:13,386 we're talking about leveraging AI in talent mobility 412 00:25:13,498 --> 00:25:16,818 and hiring and talent development. And I want to get to talent acquisition in a 413 00:25:16,824 --> 00:25:20,626 moment. But I'm also thinking that with AI being 414 00:25:20,648 --> 00:25:24,066 such a hot topic, every organization is scrambling to figure out, okay, how do we 415 00:25:24,088 --> 00:25:27,506 leverage AI better? Not just in talent development, but in everything that we do. 416 00:25:27,688 --> 00:25:31,174 And we need more workers who are skilled and 417 00:25:31,212 --> 00:25:34,486 knowledgeable on how to use these tools right. And how to leverage these tools so 418 00:25:34,508 --> 00:25:38,086 we can grow our organization. And that's becoming a huge need. And 419 00:25:38,108 --> 00:25:41,674 then we need to figure out, okay, how do we identify the people that either 420 00:25:41,712 --> 00:25:45,066 have the skills, which they're probably not enough of right now, 421 00:25:45,248 --> 00:25:48,954 or can develop those skills pretty quickly to be able to help 422 00:25:48,992 --> 00:25:52,398 the organization leverage AI more. Yeah, 423 00:25:52,564 --> 00:25:56,042 that's a great point too, because interestingly, 424 00:25:56,106 --> 00:25:59,914 as we're standing up this skills intelligence strategy, 425 00:26:00,042 --> 00:26:03,822 one of the questions that we're asking ourselves is what are the baseline 426 00:26:03,886 --> 00:26:07,346 skills that we think most every employee in the 427 00:26:07,368 --> 00:26:09,300 organization needs to have? Right. 428 00:26:12,070 --> 00:26:15,410 Some of them can kind of skills can 429 00:26:15,480 --> 00:26:19,290 span across attributes, capabilities. 430 00:26:19,390 --> 00:26:23,030 It's interchangeable to a certain degree if you're talking about 431 00:26:23,100 --> 00:26:26,514 technical skills. Yes. How do we equip 432 00:26:26,562 --> 00:26:30,314 employees and leaders with more from a gen AI perspective, but 433 00:26:30,352 --> 00:26:34,166 it's also a mindset too. So it's like if you're 434 00:26:34,198 --> 00:26:37,946 sitting in finance, right. What is the 435 00:26:37,968 --> 00:26:41,786 fundamental knowledge you need to have, even no matter what 436 00:26:41,808 --> 00:26:45,134 role you're in from a gen AI perspective? So we've said, okay, one of the 437 00:26:45,172 --> 00:26:48,958 core skills that we know we want to equip everyone with 438 00:26:49,044 --> 00:26:52,414 is exactly to your point on this topic of gen 439 00:26:52,452 --> 00:26:56,114 AI and then to what degree where, 440 00:26:56,232 --> 00:26:59,954 right? So where do you go deeper, et cetera. But I do think there 441 00:26:59,992 --> 00:27:03,426 has to be for us and for a lot of 442 00:27:03,448 --> 00:27:06,534 organizations, a really coordinated effort to make sure 443 00:27:06,652 --> 00:27:09,846 everyone has the fundamental skills on the 444 00:27:09,868 --> 00:27:13,718 topic or else it's going to get stuck in places in 445 00:27:13,724 --> 00:27:17,446 the organization. So we are definitely spending a lot 446 00:27:17,468 --> 00:27:20,978 of time on, okay, yeah, we've got the engine going now, right? What do we 447 00:27:21,004 --> 00:27:24,362 want to feed into the engine? Ironically, the first thing is gen 448 00:27:24,416 --> 00:27:28,138 AI, right. How do we get the right people there and find the 449 00:27:28,144 --> 00:27:31,606 people within our organization? And then obviously, if you're 450 00:27:31,638 --> 00:27:35,486 growing or you don't necessarily have the skills in your organization, then 451 00:27:35,508 --> 00:27:39,326 you've got to go and hire from outside so let's talk about talent acquisition for 452 00:27:39,348 --> 00:27:42,638 a moment. I know this podcast is mostly about talent development, but there are a 453 00:27:42,644 --> 00:27:46,386 lot of our listeners who are involved in talent acquisition in some way or some 454 00:27:46,408 --> 00:27:50,162 that manage both like you do, especially in smaller organizations. So 455 00:27:50,216 --> 00:27:53,938 how can skills intelligence enable recruiters to 456 00:27:54,024 --> 00:27:57,486 match candidates with job requirements more effectively, 457 00:27:57,678 --> 00:28:01,414 leading to making better hires? Essentially, I mean, I would 458 00:28:01,452 --> 00:28:04,402 imagine everyone sees the opportunity from an objectivity 459 00:28:04,466 --> 00:28:08,166 perspective, that's one, two 460 00:28:08,268 --> 00:28:11,958 is it opens up the pool. You sort of touched on this earlier. 461 00:28:12,054 --> 00:28:15,626 We were talking about not just looking for 462 00:28:15,728 --> 00:28:19,510 a line for line match to a job description 463 00:28:19,590 --> 00:28:23,438 against someone's resume, which I think is what we've been 464 00:28:23,604 --> 00:28:27,454 trying to do in the Ta function for many years and 465 00:28:27,492 --> 00:28:31,242 through a somewhat subjective lens, right? Because this is human beings 466 00:28:31,306 --> 00:28:35,066 that are trying to do that. So I think know 467 00:28:35,108 --> 00:28:38,462 a lot of organizations are pretty early on. Some are worried 468 00:28:38,526 --> 00:28:42,302 about kind of the compliance and ethics 469 00:28:42,366 --> 00:28:45,982 issues of it, which we all should be. But I think 470 00:28:46,136 --> 00:28:49,654 there's just some really basic things too that we can 471 00:28:49,692 --> 00:28:53,474 do to ensure that we're getting some of the manual labor 472 00:28:53,522 --> 00:28:56,994 out of everything from the actual initial creation 473 00:28:57,122 --> 00:29:00,742 of a job description to ensuring 474 00:29:00,806 --> 00:29:04,138 that actually what is listed as a 475 00:29:04,144 --> 00:29:07,786 requirement can truly be vetted as a 476 00:29:07,808 --> 00:29:11,550 requirement. And that we are looking at 477 00:29:11,700 --> 00:29:15,402 an individual relative to a set of skills as opposed 478 00:29:15,466 --> 00:29:19,102 to a collective body of experience that they have. 479 00:29:19,236 --> 00:29:22,558 And so ultimately, I think it's going to 480 00:29:22,644 --> 00:29:26,402 remove a lot of the biases in the process and 481 00:29:26,456 --> 00:29:30,180 it's going to open up a big pool of talent. So, for example, 482 00:29:30,710 --> 00:29:34,340 we have an initiative called Rise Up, which is basically 483 00:29:35,050 --> 00:29:38,614 there's a number of different components to Rise Up, but one of 484 00:29:38,732 --> 00:29:42,438 the things that we're looking to do within Rise Up 485 00:29:42,524 --> 00:29:45,480 is take individuals from 486 00:29:46,010 --> 00:29:48,470 less traditional paths 487 00:29:49,550 --> 00:29:52,906 and get them on a career path to be a 488 00:29:52,928 --> 00:29:56,506 technologist, which they may not have access to. And 489 00:29:56,528 --> 00:29:59,994 so to me, it's a really fascinating thing to think that 490 00:30:00,032 --> 00:30:03,774 corporations or even gen AI can help to address some of these 491 00:30:03,812 --> 00:30:07,166 social issues that get in the way of people having access to 492 00:30:07,188 --> 00:30:10,974 opportunities. Because ultimately, if you say, okay, here's someone who 493 00:30:11,012 --> 00:30:14,802 didn't have a traditional four year degree, right, didn't go to a school 494 00:30:14,856 --> 00:30:18,306 that we all recognize and know, but they did 495 00:30:18,408 --> 00:30:22,146 gain a set of skills through alternative methods. For 496 00:30:22,168 --> 00:30:25,762 us. It's the Rise Up program. And historically it's been really 497 00:30:25,816 --> 00:30:29,522 hard for leaders to then figure out, well, how do I translate 498 00:30:29,586 --> 00:30:33,110 this? And it feels risky, right? Because I can't really 499 00:30:33,180 --> 00:30:36,694 validate whether or not they've got the 500 00:30:36,732 --> 00:30:40,426 basics to do this job well. So it's taking the risk out of it 501 00:30:40,528 --> 00:30:44,054 for leaders and therefore opening up new pools of talent, 502 00:30:44,102 --> 00:30:47,658 which I think even before the market turn last year, 503 00:30:47,824 --> 00:30:51,530 organizations, I should say even after the market 504 00:30:51,600 --> 00:30:54,894 turn last year. Organizations still recognize there's not going to be 505 00:30:54,932 --> 00:30:58,206 enough skilled individuals on the 506 00:30:58,228 --> 00:31:01,822 planet to meet the needs of corporations if we don't figure 507 00:31:01,876 --> 00:31:04,960 out a way to get more people 508 00:31:05,590 --> 00:31:09,042 into the workforce. Right. There's so much in the news 509 00:31:09,096 --> 00:31:12,898 about AI taking jobs, and yet all these new jobs are 510 00:31:12,904 --> 00:31:16,626 being created all the time, and we don't have even enough skills and 511 00:31:16,648 --> 00:31:19,126 experience or people to fill a lot of the jobs that are going to be 512 00:31:19,148 --> 00:31:22,550 needed, especially if things start ramping back up in the economy. 513 00:31:24,810 --> 00:31:28,614 I always chuckle a little when I hear about some of the fear 514 00:31:28,662 --> 00:31:32,330 around that because I feel like since the beginning of 515 00:31:32,400 --> 00:31:34,860 time, there has been 516 00:31:35,950 --> 00:31:38,940 new skills that are needed to do whatever 517 00:31:39,470 --> 00:31:43,246 fill in the blank is required. So whether it 518 00:31:43,268 --> 00:31:46,110 be from way back in the agriculture, 519 00:31:47,570 --> 00:31:51,134 at every point there's new 520 00:31:51,172 --> 00:31:54,434 skills and of course, in recent decades, new 521 00:31:54,472 --> 00:31:58,018 technology that's introduced that makes 522 00:31:58,104 --> 00:32:01,634 some other skills outdated. And so it's not a 523 00:32:01,672 --> 00:32:04,738 new sort of concept that there's this coming into the 524 00:32:04,744 --> 00:32:08,118 marketplace and that people are going to need to 525 00:32:08,284 --> 00:32:12,050 people organizations are going to need to reskill upskill. 526 00:32:12,210 --> 00:32:15,782 I do think the irony is that Geni is going to help 527 00:32:15,836 --> 00:32:19,640 organizations do that a lot more effectively. So it's like, okay, 528 00:32:20,010 --> 00:32:23,706 before it would be like, well, now here's this scheme that has a 529 00:32:23,728 --> 00:32:27,514 set of outdated skills and we don't know what to 530 00:32:27,552 --> 00:32:31,002 do. Right? Well, it's like you're going to be ahead of that 531 00:32:31,136 --> 00:32:34,606 because you're going to see the trends using the analytics that you 532 00:32:34,628 --> 00:32:38,046 referenced and using AI to say, okay, here's what we've 533 00:32:38,068 --> 00:32:41,550 got, here's what we need, here's where we got to go. 534 00:32:41,700 --> 00:32:45,410 And so I actually think it can be used for good 535 00:32:45,480 --> 00:32:48,674 in so many ways. Oh, totally. And you brought up 536 00:32:48,712 --> 00:32:52,546 skills. I think that we are sort of entering a new 537 00:32:52,568 --> 00:32:56,382 era where the skills, because it can be more proven and identified, 538 00:32:56,446 --> 00:33:00,022 like you said, by AI, become more valuable. And 539 00:33:00,156 --> 00:33:03,906 we might be sort of at the end of a 50 to 70 year era 540 00:33:03,938 --> 00:33:07,686 where getting a college degree was sort of table stakes to get any type 541 00:33:07,708 --> 00:33:11,462 of professional role. People 542 00:33:11,516 --> 00:33:14,358 can debate the value of college degrees and what that's going to look like in 543 00:33:14,364 --> 00:33:18,166 the future. I'm sure they'll be around for a long time. But the 544 00:33:18,188 --> 00:33:21,866 fact is there's alternatives now. And I think more organizations 545 00:33:21,898 --> 00:33:24,186 are coming and saying like, oh, it'd be great if you had a college degree, 546 00:33:24,218 --> 00:33:27,678 but if you have these skills that's actually more valuable to us because 547 00:33:27,844 --> 00:33:31,038 at the end of the day, the degree doesn't really matter. It's what skills do 548 00:33:31,044 --> 00:33:34,018 you bring to the table that can help us, that can provide more value to 549 00:33:34,024 --> 00:33:37,460 the business? 100%. I remember 550 00:33:39,270 --> 00:33:42,450 we were talking a little bit about this. I'm a razorback. 551 00:33:42,950 --> 00:33:46,350 I graduated from the University of Arkansas wupe Suey 552 00:33:46,430 --> 00:33:50,194 with a degree in psychology. And I knew pretty quickly after 553 00:33:50,232 --> 00:33:53,366 I graduated or actually while I was still in school, I was like, I don't 554 00:33:53,388 --> 00:33:56,726 know that this is the path that I'm going to take. Not quite sure what 555 00:33:56,748 --> 00:33:59,946 path I'm going to take, but I remember so many people telling me, you've got 556 00:33:59,968 --> 00:34:03,802 to complete the degree, even if the major is 557 00:34:03,856 --> 00:34:07,434 not relevant to the direction you're taking. Because it's one of the few 558 00:34:07,472 --> 00:34:11,194 things that employers can use to gauge whether or not you have the ability 559 00:34:11,242 --> 00:34:14,878 to complete something like significant like this. And I was like, oh, 560 00:34:14,964 --> 00:34:18,734 that's the indicator that companies are using. But it 561 00:34:18,772 --> 00:34:20,400 was quite some time ago. 562 00:34:22,930 --> 00:34:26,258 But it's true, I think that was like without 563 00:34:26,344 --> 00:34:29,602 experience, you're naturally going to default to other 564 00:34:29,656 --> 00:34:33,186 indicators that help you understand whether or not someone has the 565 00:34:33,208 --> 00:34:36,562 skills and capabilities. And that's all going to change now. Again, 566 00:34:36,616 --> 00:34:40,210 it's subjectivity in the process. Yeah, 567 00:34:40,280 --> 00:34:43,954 I know we talked about I went to a rival, big state university 568 00:34:44,002 --> 00:34:46,950 and when I graduated, I don't know if I really had any skills other than 569 00:34:47,020 --> 00:34:50,714 being able to party five, six days a week. Well, I mean, 570 00:34:50,752 --> 00:34:54,522 I may have obtained those skills as well. Social 571 00:34:54,576 --> 00:34:58,426 skills are important. We're learning, right. More and more. Josh Burson calls them 572 00:34:58,448 --> 00:35:01,670 power skills, right. Like it's our people skills that are going to actually be the 573 00:35:01,680 --> 00:35:05,402 differentiator in the future. But getting back to hiring 574 00:35:05,466 --> 00:35:08,606 and skills and you talked about in the past 575 00:35:08,788 --> 00:35:12,526 identifying people who went to the name brand universities that we know and 576 00:35:12,548 --> 00:35:16,386 love. Obviously there are lots of people who have not had access or the 577 00:35:16,408 --> 00:35:19,506 ability or maybe the knowledge to get into some of those schools or to go 578 00:35:19,528 --> 00:35:23,214 to college. And yet they're now able to gain 579 00:35:23,262 --> 00:35:26,886 skills in different ways. So you say that AI also has the 580 00:35:26,908 --> 00:35:30,326 power to kind of level the playing field. Right. Andy eliminate some of 581 00:35:30,348 --> 00:35:34,086 the bias that's out there and increase diversity. Right? I 582 00:35:34,108 --> 00:35:37,878 mean, again, I'm a 583 00:35:37,884 --> 00:35:41,306 big de andy advocate. I had the 584 00:35:41,328 --> 00:35:44,550 ability and what's the word, the honor 585 00:35:44,630 --> 00:35:48,410 really to play a role at Disney for a number of years, 586 00:35:48,480 --> 00:35:52,326 helping to lead the corporate de I function. And you know, 587 00:35:52,368 --> 00:35:56,126 it was apparent to me pretty early on 588 00:35:56,308 --> 00:35:59,514 that again, sort of if corporations aren't 589 00:35:59,562 --> 00:36:02,926 helping to solve some of these social 590 00:36:03,028 --> 00:36:06,686 issues that get in the way, we're not going to make progress. 591 00:36:06,798 --> 00:36:10,414 We're just not as a society, as a global 592 00:36:10,462 --> 00:36:14,238 community, right. We've made a ton of progress. There's still a lot of biases 593 00:36:14,334 --> 00:36:17,746 out there. Right. And if we can use technology to 594 00:36:17,848 --> 00:36:21,574 eliminate those and really level playing, that's kind of the goal in the end, 595 00:36:21,612 --> 00:36:24,486 right. We want the best people and the best jobs. We want equal opportunities, right? 596 00:36:24,508 --> 00:36:28,326 That's what the E is all about. And create more diversity at all levels. So 597 00:36:28,348 --> 00:36:31,578 it sounds like there's tons of potential there for this. Yeah, 598 00:36:31,744 --> 00:36:35,578 data is the key. Let's just get back into 599 00:36:35,664 --> 00:36:39,018 development for a moment here. One of the goals I think for a lot of 600 00:36:39,024 --> 00:36:42,842 people in talent development is creating a better employee experience, improving 601 00:36:42,906 --> 00:36:46,606 productivity and engagement, and helping people grow in their 602 00:36:46,628 --> 00:36:49,726 careers so that they are engaged and want to stay around a lot longer. 603 00:36:49,908 --> 00:36:53,546 And AI is certainly the topic 604 00:36:53,578 --> 00:36:56,946 that is being brought up over and over again with people wondering, okay, how can 605 00:36:56,968 --> 00:37:00,322 I leverage this better? Can AI help us improve our 606 00:37:00,376 --> 00:37:03,426 productivity and engagement inside organizations as well? 607 00:37:03,528 --> 00:37:07,250 100%. This kind of goes back to what we were talking about in terms 608 00:37:07,320 --> 00:37:10,834 of the different prongs. Right? So 609 00:37:10,952 --> 00:37:14,594 employees, of course, we've talked about the employee experience. They can track their skills, 610 00:37:14,642 --> 00:37:18,374 they can express their aspirations, they can build personalized growth 611 00:37:18,422 --> 00:37:22,006 plans. And then AI again helps 612 00:37:22,038 --> 00:37:25,734 recommend the relevant trainings, mentors, mobility opportunities 613 00:37:25,862 --> 00:37:28,714 based on the skills they have andy what they need. But 614 00:37:28,752 --> 00:37:32,462 organizations, I think, can build a much more data 615 00:37:32,516 --> 00:37:36,090 driven talent management strategy that ensures 616 00:37:36,250 --> 00:37:39,818 that the investments we're making from a human resources 617 00:37:39,914 --> 00:37:43,250 perspective are actually helping us 618 00:37:43,320 --> 00:37:46,914 to have employees that now can 619 00:37:46,952 --> 00:37:50,734 demonstrate they have the skills that we need and the greatest impact 620 00:37:50,782 --> 00:37:54,306 on the business and closed skill gaps. But I think, 621 00:37:54,488 --> 00:37:57,830 again, managers with 622 00:37:57,900 --> 00:38:01,654 AI, you can really do a lot more in terms of optimizing your 623 00:38:01,692 --> 00:38:05,270 team performance, your team engagement, your team 624 00:38:05,340 --> 00:38:08,922 output. Again, we kind of touched on ta everything from hiring for 625 00:38:08,976 --> 00:38:11,500 relevant skills, but then also 626 00:38:13,550 --> 00:38:17,226 it enables you to see again, what 627 00:38:17,248 --> 00:38:20,862 do I have? What do I need? And you can also 628 00:38:20,916 --> 00:38:24,400 actually measure manager sort of 629 00:38:24,850 --> 00:38:28,638 effectiveness if you will too. Right. Are managers, you've got 630 00:38:28,724 --> 00:38:32,502 these tools that help support what we call quarterly 631 00:38:32,586 --> 00:38:36,274 growth conversations? Are they happening? Right. Which managers are 632 00:38:36,312 --> 00:38:40,066 actually spending the time doing the things that 633 00:38:40,088 --> 00:38:43,458 we know make an impact on an employee experience 634 00:38:43,624 --> 00:38:46,920 and ultimately an employee productivity because 635 00:38:47,370 --> 00:38:50,982 the two go hand in hand. So I think it is 636 00:38:51,036 --> 00:38:53,110 definitely managers 637 00:38:54,570 --> 00:38:56,630 and ultimately organizations. 638 00:38:58,190 --> 00:39:01,706 My team is close to 400 globally, right? 639 00:39:01,808 --> 00:39:04,860 So ultimately I can see 640 00:39:05,310 --> 00:39:09,146 using AI, like the aggregate sort of output of the 641 00:39:09,168 --> 00:39:12,394 manager behavior, the sentiment of 642 00:39:12,432 --> 00:39:16,282 employees and all the correlating sort of factors 643 00:39:16,346 --> 00:39:20,046 there. Yeah, that's interesting. The last thing I want to ask about is this idea 644 00:39:20,068 --> 00:39:23,438 of career development. We talked a little bit about talent mobility and putting people in 645 00:39:23,444 --> 00:39:27,266 the right positions. Career development is something that I think a lot 646 00:39:27,288 --> 00:39:31,134 about and work with organizations on, especially the mindset side of teaching 647 00:39:31,182 --> 00:39:34,754 employees to own their careers. I know that the number one thing that people want 648 00:39:34,792 --> 00:39:37,798 is to know how can I grow in my career here? Right? How am I 649 00:39:37,804 --> 00:39:41,078 going to grow if I work here, if I stay here? 650 00:39:41,244 --> 00:39:45,026 How are you using AI or how can people use AI 651 00:39:45,058 --> 00:39:48,514 to guide employees andy managers through career plans, 652 00:39:48,562 --> 00:39:52,406 development goals? You mentioned kind of measuring, are they having more of those career 653 00:39:52,438 --> 00:39:56,054 conversations? But we want to make sure that people are putting some type of goals 654 00:39:56,102 --> 00:39:59,866 or plans together and taking advantage of the resources that 655 00:39:59,888 --> 00:40:03,162 are available so they are able to continue to grow and develop in their careers. 656 00:40:03,306 --> 00:40:07,034 Yeah, I think we've touched 657 00:40:07,082 --> 00:40:10,686 on the AI in terms of underpinning all of 658 00:40:10,708 --> 00:40:13,890 that. To your point, it's what, 659 00:40:14,040 --> 00:40:17,714 today or yesterday, I should say, for 660 00:40:17,752 --> 00:40:21,490 us, you would have a campaign, right? 661 00:40:21,560 --> 00:40:25,194 So let's say we're going to push out the latest manager 662 00:40:25,262 --> 00:40:29,014 excellence training, right, to everyone that fits this 663 00:40:29,052 --> 00:40:32,726 persona. And so it's a very kind 664 00:40:32,748 --> 00:40:35,730 of manual effort to figure that out. Whereas 665 00:40:35,810 --> 00:40:39,402 tomorrow, with an AI sort of powered, it's all 666 00:40:39,456 --> 00:40:43,014 automated, really. So it's like you've 667 00:40:43,062 --> 00:40:46,906 captured what your aspirations are. So if the 668 00:40:46,928 --> 00:40:50,522 goal is to be moved laterally or into a different area 669 00:40:50,576 --> 00:40:53,742 or to move up, AI is serving all of that 670 00:40:53,796 --> 00:40:57,358 up. Now, I do think that there's an important 671 00:40:57,444 --> 00:41:01,278 overlay to all of that, which is something that we spend a lot of 672 00:41:01,284 --> 00:41:05,026 time on, because you can build it, right. But you still have to 673 00:41:05,048 --> 00:41:08,818 bring people to it and they still have to be inspired by it. 674 00:41:08,904 --> 00:41:12,226 And so I do think that it requires kind of a 675 00:41:12,248 --> 00:41:15,986 consumer grade marketing strategy on top of 676 00:41:16,008 --> 00:41:19,238 it all, to your point, to create awareness, but it is going to be a 677 00:41:19,244 --> 00:41:22,694 lot more automated. So if, Andy, you 678 00:41:22,732 --> 00:41:26,086 decide you want to be the SVP of Talent Acquisition and 679 00:41:26,108 --> 00:41:28,600 Development ServiceNow and 680 00:41:29,610 --> 00:41:33,414 you capture that as your Aspiration, then it's a lot more automated 681 00:41:33,462 --> 00:41:37,258 in terms of how it's served up to you. Yeah. 100%. I 682 00:41:37,264 --> 00:41:40,474 can see that as we continue to develop more of these 683 00:41:40,512 --> 00:41:43,366 tools, there's so many more things available. I know it can seem 684 00:41:43,398 --> 00:41:46,974 overwhelming to people. Sometimes they're like, oh, where do I start? 685 00:41:47,092 --> 00:41:50,206 But you got to start somewhere. Start with the data you have, start with the 686 00:41:50,228 --> 00:41:53,966 objectives, the goal, the problem you're trying to figure out. Ask your colleagues, talk 687 00:41:53,988 --> 00:41:57,506 to friends, listen to this follow up, look for other guides and 688 00:41:57,528 --> 00:42:01,358 resources. Our community, we're talking about this all the time in the talent 689 00:42:01,374 --> 00:42:04,642 development think tank community. What tools can we use to 690 00:42:04,776 --> 00:42:08,322 better development, provide development opportunities to our people, 691 00:42:08,456 --> 00:42:12,070 to develop our managers, to help people continue to grow 692 00:42:12,140 --> 00:42:15,798 so that they're moving into the roles, Andy, that we need, developing the 693 00:42:15,804 --> 00:42:19,558 skills we need to be more successful in the future of work? 100%. 694 00:42:19,644 --> 00:42:23,274 Well, Sarah, this has been really great. I appreciate you coming on. I have probably 695 00:42:23,392 --> 00:42:26,954 20 more questions, things we could talk about, especially with related to 696 00:42:26,992 --> 00:42:30,774 AI and talent mobility and the work that you're doing there at ServiceNow. 697 00:42:30,822 --> 00:42:34,606 But this has been a great start and I really appreciate you coming on and 698 00:42:34,628 --> 00:42:38,474 I look forward to talking more soon. Thank you for having me, Andy, truly. 699 00:42:38,522 --> 00:42:42,270 And we're deep in this journey right now. We're learning, 700 00:42:42,340 --> 00:42:46,046 we're capturing sort of our learnings and our journey. So 701 00:42:46,148 --> 00:42:49,602 if you want to reconnect in the coming months, we could share more 702 00:42:49,656 --> 00:42:53,042 about where we are because it's coming to life in real time. 703 00:42:53,176 --> 00:42:56,866 Yeah, for sure. Well, we've got our Bonus Q A, and I'd love to have 704 00:42:56,888 --> 00:43:00,726 you come speak in our community as well and get a discussion going about how 705 00:43:00,748 --> 00:43:04,246 we can better leverage these tools. So we'll talk more about that soon. 706 00:43:04,348 --> 00:43:06,920 Sounds good. Thank you, Andy. All right, take care. 707 00:43:10,570 --> 00:43:14,298 All right, that will do it for my interview with Sarah Tilly from ServiceNow. I 708 00:43:14,304 --> 00:43:17,882 hope you got value from that interview from that conversation. We certainly 709 00:43:17,936 --> 00:43:21,750 covered a lot of ground there with regards to using AI 710 00:43:21,910 --> 00:43:25,514 in talent development. And I want to remind you that in addition 711 00:43:25,562 --> 00:43:29,246 to all the great content you got here, I'm also hosting a 712 00:43:29,268 --> 00:43:32,874 webinar with my friend Josh Urmler about AI in talent development. 713 00:43:33,002 --> 00:43:36,062 And it is coming up next week on August 714 00:43:36,126 --> 00:43:39,826 29 at 01:00 p.m. Eastern Time. If you want to register for 715 00:43:39,848 --> 00:43:42,750 that for a link in the show notes or go to TDT 716 00:43:42,910 --> 00:43:45,966 Usai. That's TDTT 717 00:43:46,078 --> 00:43:49,926 usai. I'm also going to be inviting Sarah to join us in 718 00:43:49,948 --> 00:43:53,778 the talent Development Think tank community to speak about using AI in talent development. 719 00:43:53,874 --> 00:43:57,574 Josh will also be doing a follow up session in the community about 720 00:43:57,612 --> 00:44:01,206 using AI in talent development, so stay tuned for those. If you want to find 721 00:44:01,228 --> 00:44:05,078 out more information about the community that's at TDT us slash community. 722 00:44:05,244 --> 00:44:08,134 If you have any questions, reach out to me. I hope to talk to you 723 00:44:08,172 --> 00:44:11,486 soon and stay tuned because next episode, it is my Bonus Q Andy A with 724 00:44:11,508 --> 00:44:12,940 Sarah Tilly, and it is a good one.