Trust: The Missing AI Upgrade

Artificial intelligence investment is exploding, but adoption often stalls. In this episode of the AI Proving Ground Podcast, Great Place to Work CEO Michael Bush and WWT CTO Mike Taylor unpack the real reason why: trust. They reveal how culture, leadership and access — not just technology — determine whether AI pilots fail or flourish, and why people-first leadership may be the ultimate competitive advantage in the age of AI.

Support for this episode provided by: Tanium

More about this week's guests:

Michael C. Bush is CEO of Great Place To Work, the global research and analytics firm that produces the annual Fortune 100 Best Companies to Work For list, the World's Best Workplaces list, the 100 Best Workplaces for Women list, and dozens of other distinguished workplace rankings around the world. Driven by a love of business and an unwavering commitment to fair and equitable treatment, Michael joined Great Place To Work as CEO in 2015, bringing 30 years of experience leading and growing organizations. Michael is a former member of President Obama's White House Business Council and a founding board member of the private equity seed-fund, Fund Good Jobs, which invests in small inner-city businesses.

Michael's top pick: Cultivating Workplace Excellence with Fortune’s Alan Murray, Great Place to Work’s Michael Bush and WWT’s Jim Kavanaugh

Mike Taylor oversees WWT's Global Engineering and IT organization and Services segment to position WWT as a single-source provider to accelerate digital transformation. Mike aligns WWT's unparalleled technical capabilities with its collective business acumen to both advise and execute customers as they seek to become more agile and innovative. As business and technology become more complex, it is crucial organizations use technology investments to drive strategic initiatives. Mike is responsible for connecting business strategy into the IT organization, and simplifying the sales and services process to create a more seamless experience for both customers and partners.

Mike's top pick: Building for Success: A CTO's Guide to Generative AI

The AI Proving Ground Podcast leverages the deep AI technical and business expertise from within World Wide Technology's one-of-a-kind AI Proving Ground, which provides unrivaled access to the world's leading AI technologies. This unique lab environment accelerates your ability to learn about, test, train and implement AI solutions.

Learn more about WWT's AI Proving Ground.

The AI Proving Ground is a composable lab environment that features the latest high-performance infrastructure and reference architectures from the world's leading AI companies, such as NVIDIA, Cisco, Dell, F5, AMD, Intel and others.

Developed within our Advanced Technology Center (ATC), this one-of-a-kind lab environment empowers IT teams to evaluate and test AI infrastructure, software and solutions for efficacy, scalability and flexibility — all under one roof. The AI Proving Ground provides visibility into data flows across the entire development pipeline, enabling more informed decision-making while safeguarding production environments.

Chapters

• 0:00 The AI Adoption Paradox
• 2:19 Bubble, Hype, and Reality Checks
• 4:13 Culture, Trust, and Conflict That Builds
• 6:40 What The Data Says About Trust
• 9:55 From Suspicion to Curiosity
• 12:20 Building Adam AI: A Use Case
• 15:21 High-Trust Teams Under Pressure
• 18:07 Monday 7am: Executive Sponsorship
• 21:01 Will AI Break Employee Bonds?
• 25:05 Tackling Fear With Dialogue
• 28:03 The Future: Agents, Signals, Skills
• 31:07 Training, Driver’s Licenses, Prompts
• 34:15 Measuring What Matters, Faster
• 37:18 Takeaways and Closing

Transcript

SPEAKER_03: 0:00

Across the enterprise, investment in AI is soaring. But adoption often stalls, which is pushing ROI down the line and making it harder to realize. On today's episode, we'll talk with Great Place to Work CEO Michael Bush and WWT's chief technology officer, Mike Taylor, about that void between AI's promise and its payoff, and the role culture and leadership have in bridging that gap. Mike and Michael answer questions like what leadership behaviors push AI from proof of concept to production? How do you move a workforce from suspicion to curiosity without glossing over the job anxieties that many people feel? And once you see progress, what kind of training makes those changes stick? This episode is packed full of practical signals you can look for to gauge your own organization's success with artificial intelligence. And by the end, you'll have a sharper playbook for how to sponsor AI efforts, communicate the why, measure progress, and raise the bar for leaders who must now be both human-centric and technically fluent, turning AI from a story you tell into a system you run. From Worldwide Technology, this is the AI Proving Ground Podcast, everything AI, all in one place. Let's jump in. Happy to be here today, Brian. I've seen you talk a number of times, sometimes in person, sometimes in video. You always get me pumped up, so you got a high bar to live up to. All right. Looking forward to it. And Mike Taylor, equally, you get me pumped up as well. So I'm excited to have you on as well. Welcome.

SPEAKER_02: 1:41

Uh happy to be here with Michael and uh yeah, look forward to this topic and conversation today.

SPEAKER_03: 1:45

Absolutely. I want to start with kind of what's kind of an obvious statement right now taking place in the industry. It feels like we're in the middle of a paradox right now. Investment in AI from the biggest of the big companies on on down the list, growing rapidly. Consumer adoption of tools like ChatGPT, Gemini, or whatever it might be, skyrocketing. But at the same time, organizations are struggling to really drive meaningful adoption of AI in their businesses. And even further, it's so hard to get pilots out of that phase and into production. Michael, I'm going to start with you. What do you think that signals? You know, we talk a lot on this podcast about data strategy, cyber, use case prioritization. And those are reasons why some of these pilots fail. But from a leadership perspective, I'm curious what you think. What does that signal to the market from a leadership perspective?

SPEAKER_01: 2:35

I think with uh every transformation throughout history, when there's a new idea, there's a bubble that's created, which eventually bursts. But then the thing takes off. It actually happens. The bubble doesn't mean it's not going to happen. It means people get too super excited. A lot of money moves, there's a lot of hype without a lot of tangible ROI type thinking, but it's necessary. And that's where we are now. So uh the bubble's getting bigger and bigger. Money's moving in a way that actually doesn't make sense. Um, but one thing we all one thing we all know is on the other side, uh, AI is going to change the world that we live in. So we're in that phase now. Uh also because we're all uh in a capitalist environment in terms of running companies, um, we are projecting that we are perhaps delivering more than we actually are, because that's important. That's what gets the bubble going, that's what gets investment going, which all companies need to break through and have the innovation. So we're at that point now. And uh I'm fortunate in the work that we do to actually look inside companies and get a feel for what's actually happening. So I'd say we're a little ahead now in terms of hype being above uh the actual work. Uh, but people are beginning to think about um, well, maybe I'm not getting the ROI because I have no idea what that means right now, but we better start doing something because sooner or later, you know, people are gonna say, kind of, where are the goods? And uh there's some great examples, world worldwide technology being one of them, uh, of companies that are actually already dealing with reality and making sure that it's getting applied at work.

SPEAKER_03: 4:12

Yeah. Mike, I'm curious, you know, from what we've done here at WWT, what what leadership traits do you think push AI projects over the finish line, or even the reverse, what leadership traits maybe you know help push back a little bit?

SPEAKER_02: 4:26

Yeah, prevent that sometimes. Um I I would say just doubling down on what Michael covered there, anytime the way we view the market, anytime there is change, anytime there's disruption, uh, there is opportunity out there. And uh I think the companies, the organizations, the teams that are most prepared to capitalize on that are are the ones who have invested in culture, they've invested in health, they've they've got trust. Um, we talk about, you know, conflict is good, conflict is necessary, and organizations that can can bubble these ideas up, bring them together into a cohesive or even a connected strategy are are the ones that are succeeding right now. And make no mistake, whether it's um uh you know the the current AI trends that are going on, if it was, you know, remote work and all the things that we had to face there, you know, years ago, um, leaders who who lead by example, who get involved, who spend the time to learn how these things are going to be applicable to their organizations, those are the ones that we see moving out front. And I'd say even with some time spent with Michael and his team yesterday, you know, you're a data analytics company, uh, you know, in terms of the core properties that you seek out and their ability to move and adapt and how not just they're they're collecting the data, but how are we how are we looking at this? How are we using machines to interpret uh you know, and at least it worldwide through your survey, we get somewhere around 1,300 pages of of text-based feedback from our employees. How are we using new, unique and and differentiated methods to collect that, determine what's actionable and and go make a difference with it? Um, but the same, you know, I hate to to to to bury the headline a little bit, but a lot of what we're seeing in the success, it's doing the same stuff the right way that you have been for a while.

SPEAKER_03: 6:15

Yeah. Michael, you or Mike, you mentioned great place to work, kind of at its core, a data and analytics company. And and Michael, you mentioned, you know, you're kind of constantly on tour talking to, you know, the the tons of companies that that you interact with. What are you seeing in some of that data? Not that you have to have specific data points, but anecdotally, what are you seeing from the data as it relates to AI adoption and and what's working and what's not working?

SPEAKER_01: 6:40

Yeah, well, one of the things we're seeing in the data, we've surveyed about three million people now uh over the last two and a half years, specifically around AI. So uh one of our our lead data scientists, uh Marcus Erb, realized, you know, I'm sure glad he did, that we better start measuring. And so we did almost three years ago, we came up with a with a question set, and then we went to great companies, companies we knew that were great. You know, these are companies that we recognized uh as being the best in the world uh to measure what's going on with their people. And what we what we measured was enthusiasm, uh, whether they had access and adoption, were they actually uh using tools and did they think it was having impact on their work? And what we found out is in high trust companies, uh, without trust, there's nothing. Uh if you want to talk about how do you have failure in terms of um human experience, you implement AI in a low trust environment. The fear level is super high. People do not have hope. They're not using the tools, most of them don't have access to the tools. So that's one part of the world, which I would say unfortunately is the largest part of the world. Um, and then you can take great companies where there's a high level of trust. And so while everybody's wondering, worried about their job, you know, I've been worried about my job for my whole for my whole career. So this is nothing new. Um, that's just a normal human fear, but but whether or not this is gonna replace me, whether or not this is gonna lead to net less income and growth opportunities for my family, those basic human concerns. When you have a high trust environment, that's at a lower level. And and we we measure trust. That's the business that we're in. And so when you've got a high level of trust where over eight out of 10 people say, this is a great place to work, which is kind of our bar uh for that statement, worldwide being way above that bar, one of the one of the best in the world, then then um you've got 87% of your people saying, We're excited about this, we're excited about it, and wanting to try to use tools and getting access to tools, um, you know, whether it be open AI, whether it be co-pilot, anthropic, etc., people making those choices and people being supported and encouraged to apply it in their job, not just for planning their kids' birthday party. Let's see if we can actually put this to work and feeling safe that that when they do that, there's not anything negative that's gonna occur for for them with that experimentation. Matter of fact, the opposite is gonna be what happens. When you're in a high trust place, you can do that. Um, unfortunately, as you and we did a global survey country by by country, um, and uh it one of the things that shocked me is there's more access to the internet in Africa and China than in the US from an access point of view, because in those places everybody with a mobile device has access to AI, multiple cheap AI, low-priced AI. So, so um uh that that was an interesting finding. And then the other one is this issue about trust and and the experience that people are having, and and from what we all know, uh that depends on who you work for. Yeah, totally who you work for. If you if you work for a leader who you doesn't who you don't trust and you don't think trusts you, and they say use these tools, you're like, I'm not so sure. And so so that's the barrier, you know, and uh the opportunity. But in terms of AI, uh our our view of AI is that uh it should be abundance for all. And and and to us, what that means is that everybody does better when everybody does better. It's not just some people, it's everybody does better when everybody does better. And we believe that that if you care about people, um, you want that to be true. And uh and you you want uh not only cost reduction, you want growth. You know, you're just excited about massive expansion of your market as you are about cost reduction. And right now I think we're a little rotated towards just the cost reduction and the ROI part instead of of uh you know just uh thinking about doubling and trickle tripling the size of your market.

SPEAKER_02: 11:04

Yeah. Yeah, that that's a really good point. And we we talked a bit about this yesterday too. I I think the moving people from a a state of suspicion to curiosity in in this space is gonna be really important. And and I do think many of the headlines that that are out there, because I think this is what gets clicks and this is this is what people can can draw upon, even even in in in you know media news outlets, is you know, what is the impact to the to the job environment? How is this gonna change? And we'll and we'll get to some of this in in the discussion, but I think the point that was just raised by Michael there that has really created more curiosity within within our customers and and within worldwide has been this idea of how do these tools help us break through limitations that we have otherwise had in serving our customers. And and rather than it being about uh reduction in job force or changing the landscape of the of the employment base, it's how are we using these tools to reimagine services and capabilities that we want to offer to people? And and internally, I would share just a use case we struggled with was we have all this great intellectual property around uh technology and technology comparisons through the advanced technology, the proving ground that you've covered on the podcast here. What was really hard was to sort of democratize that information out to someone where the the complexity and the nuances of those questions and answers is is is the the permutations. I don't even know where they would stop. They're they're endless. And so machines being able to interpret language that opened a door for us, essentially. We said, okay, our mission has been how do we share this IP with with the market, with our customers. And now we have a product we've developed atom AI that can interact with a human being and say, oh, that that is kind of what I wanted, but I really was looking for something more over here. And now we're able to bring that forward. That that is reimagining a set of services that we wanted to bring to the market for a very long time, but had run into technical challenges that prevented us from being able to do it. And I don't know if we were a little lucky or a little good, maybe a little bit of both, that we started there. But I think that example is something our our our company and the employees we have here have been able to rally around and say, when we talk about new levels of service or new ways to serve and better serve our customers, here's an example we can point to. These are the things that we're talking about. Now, how do we go find that in in all areas of the company and and and and increase our value? And that generates more opportunity for people within our business, not just in the near term, but over the long haul.

SPEAKER_03: 13:50

Mike stick with Adam or WWZ's AI journey. What type of uh what type of human or cultural um signals did we utilize to help drive that forward? Like, I mean, I'm sure you're gonna kind of get into our our culture and you know, our IML, our integrated management leadership program. What what really helped us push that forward, knowing that adoption is such a struggle for many?

SPEAKER_02: 14:15

Yeah. I the the first piece I would point to is in a high trust environment, you you can say the wrong things and people still know what you mean. Uh and and you know, some would argue I've made a career of that, by the way. But uh, you know, in this case, it was about having a real intention with our teams to say, how can we imagine use cases that matter and and how do we bring teams together to take it on? And I would tell you from Adam AI to the RFPA, our RFP assistant, you know, that we built together uh with our teams, um, you know, there were moments there where we're like, are we gonna make it? Are we gonna be able to figure this out? And you know, some of that were things that we needed to organize internally. Uh, some of this was the evolution of you know, GPT technology from the the transformer technology from you know two five to three and now you know up to five that we're using in in conjunction with some of Microsoft's platforms there. But all of those things together, we had difficult conversations on are we going down the right path? Should we keep doing this? Uh and I remember a meeting very specifically with our CEO, uh, some other executive leaders, and we were looking at our technical teams and we're like, are you guys gonna be able to figure this out? And we had a very blunt and direct conversation. And and I remember the answer today uh from one of our data scientists was give me two weeks. I need two weeks. And we said, You you have two weeks. And we got off that call, and I was like, I don't know, I don't know which way this is gonna fall. And you know, sure enough, they they came back uh it was probably in less than a week. So we think we got it, we think we we think we can do it. So um trust extended throughout there uh in order to see it through and make it happen, and um, you know, really proud of of that team and and and what they've been able to do and continue to do.

SPEAKER_03: 16:04

Yeah. Michael, thinking about what Mike just said right there, what are the lessons learned that others can take from from that story and apply within their own own organization to help drive AI?

SPEAKER_01: 16:16

Well, I I think uh what Mike's talking about is working in a company where there's a very high level of trust. Yeah. Both people trusting their teammates, um, people trusting people they don't know in the company, people trusting their people manager and people managing uh trusting top management that they may not interact with as much. Um so we measure that. So so we know that environment. That environment is very different from um most work environments. And and and so just using the data, again, using this metric of you know, seven to eight out of ten people feeling like they trust the company, feel like the the company um uh cares for them compared to the average workplace, which is five out of ten people. Big difference between those two. Um and so when you've got that situation, you get to uh say the wrong things. You get to say things and maybe make mistakes, and and people don't don't attack you for it because they know what you're trying to do and that you care about them, you care about the company and the and the community as well. Well, when you've got that high trust environment, so for anybody listening, it's like you have to assess your workplace. And um, and and if you're not at a place where seven out of ten people are having a great experience and feeling cared for and want to commit themselves fully to the company, update your LinkedIn profile and go someplace else. Oh, okay, um, because you want to be it. That's that's that that work is so important, such a big part of our life. That's where you want to be. If you're at one of those places and you ask the question we ask, um uh, do you believe that artificial intelligence will create new growth opportunities for the company? It's almost nine out of ten people say yes at a high trust workplace compared to five out of ten people at an average workplace. I believe artificial intelligence will have a positive impact on my career. Eight point eight out of ten people say yes compared to five point three out of ten people. Management clearly communicates our plans for using artificial intelligence within our business, including saying we don't really know right now, we're trying to figure it out. Nine out of ten people compared to five, five out of ten people. My company encourages me to use artificial intelligence to do my work. 9.2 out of 10 people compared to five. And the final one, my company provides artificial intelligence tools that help me do my job better. Nine out of ten people compared to five out of ten people. Yeah, so two different experiences going on around the world in terms of working people, and so that's the opportunity. If you're in a place where there's low trust and kind of that five out of ten, you can't implement, you could barely implement Excel. Okay, some people use Excel and some will not. You just it it doesn't happen. And this is the difference between good and great. You can do business, but in terms of of you know uh the kind of growth and sustained growth um that you want, having customers with high CSAT scores, it's just not gonna happen in that environment. And so th this is the opportunity, um, and and this is why we talk about um at Great Place to Work, uh people first AI. We we talk about it because we don't see how you do this well without having that great experience. But I know you know not every uh company uh b believes in that, but but I think you know we were talking earlier, and and so worldwide is a place that's pushing this. Worldwide is pushing this, and and when I say push, it's not always comfortable to be pushed. Yeah, okay, but but if we're if worldwide pushes this and pushes the people where it's a little bit uncomfortable, it's gonna be great for worldwide because it's gonna enable worldwide to lead and support customers and to let customers though, because worldwide's in a position where they can talk about AI and the implementation of it based on what they're doing, not theoretical stuff about you know, generally what could happen and how great it is. They can talk about it. And I know for a fact here at Worldwide, on a departmental basis, senior leaders have goals. They have like two things they've got to be doing, and they're held accountable every Monday at seven o'clock to report on what they're doing. So I think they probably have a terrible Sunday, okay, and preparing for that. But this is the reality of the situation. How many companies are doing that?

SPEAKER_03: 20:49

Yeah.

SPEAKER_01: 20:50

How many companies at the top are doing the normal things they do? Earnings per share, you know, CSAT analysis, free cash flow analysis, uh, new logos, retention, upselling, uh, expansion, budgets, all the normal stuff you do. And then you add an hour to that to do something you've never done before in your history, which is to talk about how you're going to implement a technology across across the company. It's a short list. It's a short list. A lot of passovers at a lot of companies, when this topic comes up, senior execs leave. They delegate it. Okay. There's a whole, there's an AI team, but it's not the senior execs themselves. That's happening here. I'm sure it's not the only place, but I don't know another place doing it with this kind of rigor that's been doing it. Right. Oh, oh, you know, I actually made that commitment. And so um, again, when you know your company's doing that, you have more trust and faith with the in in what's happening and why, because you're like, it must be important. I know Jim Kavanaugh is in these discussions every every Monday. He's not delegating it to someone else. It makes me trust and have more faith that this is important, and yes, I should commit myself to it. And um, and any leader, you know, I heard this from Mike and other uh others yesterday in the time that we spent here. Any leader who's not doing this on their own knows they're not being a leader right now. They they know they're not really being a worldwide technology leader, and they better get it going or or they're gonna be called a manager, you know, rather than a leader. So um, you know, it's inspirational uh uh to see. I I I'm inspired because I believe this is how we make the world better with AI. The other way, I think all the dark things come true if if you're not really putting people first and and and and and leading this in a way that that they feel comfortable and inspired that things are going to get better for them and their families. Yeah.

SPEAKER_00: 22:52

This episode is supported by Tanium. Tanium provides real-time endpoint management and security to protect enterprise assets. Gain control and visibility with Tanium's Unified Endpoint platform.

SPEAKER_03: 23:05

Well, Michael, you're talking about the executive uh leadership team, which meets every every Monday morning. And Mike, you can kind of go into that a little bit. Uh, but frame up your answer in terms of what does that mean from an executive sponsorship perspective, understanding that executive sponsorship is one of the key traits to pushing AI pilots into productivity.

SPEAKER_02: 23:24

Yeah, it is. I think this is uh also just a sort of a continued flight path or trajectory, if you will, of just the importance of connecting technology to you know, to your business and the and the and the various business offerings that you have, whether that's on the go-to-market side in terms of the products you bring forward or you know, how you improve, how you serve your own employees. We talked about a few examples with our our uh RHR team yesterday as well. You know, but what when I look at this, it it the the number, and this is like the back to basic stuff as I think about it, the number one thing my teams, I believe, pay attention to in terms of what what I'm doing is where am I spending my time? What am I spending my time on? Who am I interacting with? And and and those things are the strongest signals from my perspective. Um, maybe even more so regardless of what I say is what do I do and where do I spend that time? And so, you know, in in in a you know, somewhere in the front chapters of you know, a a book on business management leadership is just where do you spend your time? What are the topics that are important to you? Who are you interacting with? And I think that's a page that you know we have taken very literally through a number of different changes at worldwide and and bringing that topic into into our Monday meeting where it's not just about the technology, but it's the technology, it's the business operators and the and and the sales teams and and going through ideas, progress, and things that we're blocking to get to get these these use cases beyond pilot into full production. The part that's been really interesting that I don't think I I certainly did not um uh did not anticipate, but have seen is the the lateral or the transferability from the internal use cases that we're doing to our customers and what they're trying to do, as Michael said kind of earlier. We we know it because we're doing it, and we're not just doing it internally, but we're doing it across 20 or 30 different customers in terms of these use cases. But once you have one or two, there is a flywheel effect, uh, both in terms of change management momentum, people who are seeing things and oh, I heard this team's doing that. How do we, you know, how do we get on board? How do we how do we take that on? But that flywheel effect of of momentum within the employees, but also once you get the data right and you get these these things collected and pulled together, you may serve seven or eight different internal use cases from the same blocking and tackling you did in one set of data or one one uh one grouping of data. And that that for us has led to speed. It's helped keep that initial momentum going. And as we all know, momentum is a powerful thing, whether it's working with you or against you. And and right now we're we're privileged to be in a position where it's it's it's going well and we're trying to share that more with the market.

SPEAKER_03: 26:07

Yeah. Michael, I want to go back to trust. I was reading uh a recent Wall Street Journal article that positioned a question. It actually might have been in one of their newsletters. Um, but the question was will AI break the bonds between big companies and their employees? And then they went on, they were talking about the Walmart CEO and some of the things that he's done in terms of um addressing the market and their employees. It had to do with like training and things like that. Do you think that question is is overblown or is that a very real risk that the bonds between the companies and their employees are at risk here if you don't get um AI right?

SPEAKER_01: 26:43

Uh I think it's it it is uh I love the fact that people are writing about that. And um, I wish more people were thinking about that. Um I I would say it it's like um in when uh the pandemic occurred, and uh companies would call us and say, Um, look, we have a whole a low level of trust and we need to build it quickly because we're about to go remote. And I'm like, you better uh do you believe in prayer or light and incense? Oh, okay, because that's the only way now. It's too late. Too late. Yeah, it's too late. You can't do it now, okay? But companies that had already been doing it, they went remote, they figured it all out, did something, you know. So that's the thing. High level of uncertainty, no roadmap, no books to refer to. How does a company succeed in that environment? It's trust. It's trust. When you have a high level of trust, you can absolutely do anything because you have a group of people who believe you can absolutely do anything. So I believe that is the issue. I I think that that you know, Doug is an amazing CEO uh at Walmart there on the 100 best list and uh a company that uh has a great leader who's focused on the people, you know, and so one of the things that he said uh very recently is that, you know, I don't really see our employee numbers going down. You know, to to me, by him communicating that in a time when public markets want you to say I'm gonna cut people, he's got a growth mindset. He's got a growth mindset. You know, he's believing that the the these new technologies will come in and uh you know the headcount will stay about the same, but revenues are gonna go up. To me, that's the growth mindset. Now that inspires me about AI rather than the opposite, you know, CEOs who are like uh leading with the we're gonna be able to cut 30% of our staff. Um that's short-sighted. That's probably gonna help you this quarter, but cutting your way to growth, um, I want to see that. Okay, cutting cutting your way to sustainable growth. So um, you know, that that's where the the trust spark comes in. And um, you know, if you've got a low trust, bad leader today, that person's gonna be horrible with AI. That person's gonna be horrible with AI because that person uh doesn't really care about people and their experience. They also don't care about what's in the model. You know, they they don't want to check the model, you know. And I remember, you know, because I've been doing business a long time. I remember VisaCalc. I remember Lotus 1, 2, 3, these products that at first the math wasn't right. I remember those things, you know, but but um was in an environment where if you were using those tools and the math wasn't right, nobody was gonna chop your head off. Okay, they they still enabled you to to work through it, um, which which you need that kind of trust and faith um for for AI as well. So um, and I believe that there are two types of leaders in the world right now. There there's leaders who are looking at using AI to replace people, and uh these I come from Silicon Valley where people are writing articles that they think are interesting, like the first billion dollar company with one. employee, I don't think that's interesting. Okay, because I just I don't see the what's good about that. Um I'm I'm more about what's good for people, you know, what what grows communities, what leads to safe communities, you know, companies that care about schools, companies that care about water and air and things like that, uh, because that's a great place to work uh for for all. And those companies only exist that I just described when there's a high level of trust um with with the employees. So um we believe trust is everything and and and we believe this is a technology that has the highest level of fear attached to it that I've seen in my career. People didn't have fear about the internet. People didn't have fear about Excel. You know, people didn't have fear about trains, another bubble that collapsed electricity, another bubble that collapsed. So but this one people do. You know you know people have a fear that this one is somehow going to try and automate them and somehow going to replace them. They have that fear depending on who they're working for.

SPEAKER_03: 31:07

Yeah.

SPEAKER_01: 31:08

You know um some people believe the those movies depend depending on who they're working for but uh when you're in a place where people care about each other um people care about each other's families people care about each other's aspirations people um want uh people to to leave work at 4 30 to go watch their son golf okay an environment a company like that um you you kind of know um I don't think they're gonna use this thing against me I don't think they're gonna weaponize this thing I I think this place uh is actually one of those places where they're actually trying to make the make the world better and high trust companies tend to do that yeah uh you can look at it in terms of the impact they have on the community the level of volunteerism in in the company retention you know I was I was here you know countless people have been 20 years 26 years 27 years you know where I come from Silicon Valley it's like oh I've been here a long time four years okay it's a whole different thing I'm not knocking the valley I love the valley but I'm just saying there are different uh things in a high trust company Walmart people have been working there a long time and and you hear that um freight companies great companies they've they're there for a long time because they make a commitment to their families the second largest commitment maybe you know maybe they're cherish here depending on what they believe in you know then their families then it's the company you know so so it it it it's it's really important and obviously you know we all we know in this room today how special that is um when you and you feel lucky to work for a company like this and you want to stay there a long time it's one of our survey questions do you want to stay here a long time you know and I think it's like 9.2 out of 10 people at Worldwide Technology say I want to work here a long time you can't force people to say that that's a survey question. When people are taking our survey they pause before they answer it you can watch it because they're thinking are they going to commit their future to the place? It makes them stop and think before they respond. And when you can get a person to stop and think and go I want to be here a long time you know you you you now you've got an environment where actually you know any anything can happen uh rather than another environment that's trying to rift their way to greatness.

SPEAKER_03: 33:27

Right well next time uh I take that survey I will be sure to do a nanosecond yes I want to be there a long time there you go yeah there you yeah Mike you know certainly WWT scores uh very well on the Great Place to work survey which is uh a source of pride for us but Michael brings up something important which is fear there is a fear about this technology and because we have a high trust environment here at WWT we're probably more prone to jumping in with AI but I'm sure there are still pockets of employees that have that fear factor. How do how do you and by extension the executive team think about tackling that fear so that we can make everybody comfortable to move forward?

SPEAKER_02: 34:11

We talk about it. I I think that the the first thing we do is we we allow people a platform to to share those ideas whether it's town halls we're hosting, it's you know the meetings we're having week in and week out we do uh listening tours where our executive leadership will will participate uh six times a month one of us is you know uh on a call with 20 to 30 employees and those topics here recently are around innovation, disruption, AI, workforce engagement um where inevitably and we go through these in that infamous 7 a.m meeting as well we spend you know five or 10 minutes kind of recapping what those are regardless of the topic there is there is some uh component of AI or the impact of the opportunity for AI to impact those things and and one of the interesting pieces has been again you know glass half full half empty I'm I'm I'm more half full on this stuff than than anything and um you know we're thinking about and have started implementing agents that that help augment our management leadership curriculum. So someone who's new to the organization where they go through facilitated training on our our culture, our values, the concepts that we use around employee performance and and our core values um but creating an agent uh out there where our our employees can ask you know maybe questions they're afraid to ask uh you know their boss or even you know their their informal mentor around how these tools are used or having uh uh role playing and coaching conversations with with these tools. Those are where our imagination goes around and and our execution frankly go around how these tools can uplift, evolve and grow employee engagement in the midst of, you know, in some cases fear, uncertainty and doubt on exactly where this lands. But um we're we're thoughtful about those. And some of those ideas I mentioned those came through those those listening tours and and different sessions and engagements we had. What if we did this it's like it's a good idea um you know let's let let's let's activate that and uh you know again we've got a playbook where we're able to do that fairly quickly.

SPEAKER_03: 36:20

Yeah. No I think having that kind of open discussion helps turn people I think we used the the phrase in a prior episode phobo fear of becoming obsolete turning that phobo into FOMO fear of missing out and then you know helping drive adoption of AI that way. I know we're coming up on the uh the the bottom of this episode I I want to kind of shift to the future a little bit. What do we think the future of great workplaces, Michael uh looks like as it relates to a growing number of companies becoming quote unquote AI first or AI led. What does it mean to still be a great place to work for all in the AI age?

SPEAKER_01: 36:56

Yeah I I think it still comes down to trust. I still we'll still be measuring that the way we're measuring it will change but it'll still be trust um we'll we'll still be trying to understand how you feel about the people you work for and and the person you work for, the people that you work with and the community uh that that you and your colleagues uh live in uh regardless of where you work so that part of it won't change I think what will change is I think we'll have agents um basically creating the questions depending on things that are going on all around you so it won't just be a survey as as as it is today it'll be uh looking at all all of your team's chatter um looking at all of your emails looking at um your what you're accessing the agents you're accessing the information you're accessing and looking at all of that to get a uh a sentiment you know kind of a measurement of whether this person is inspired or not uh whether this person is curious or not whether this person is learning or not you know one of the things that came out of our most recent study is that um we think that in this era um the skills you have today are gonna be obsolete in two years so you're gonna have to it used to be you could hold on to skills you know 15 to 20 years now it's gonna be down to two so you have to be a continuous learning leader um you know in order to grow and thrive and and have value so I think I that that that that's it. I I think that that we'll be surveying the experience you're having do you trust your agents um do your agents trust you do agents trust agents um all these kinds of things it it it just kind of multiplies but that's the world that we'll be in but we're doing all those things to get I think an actual more accurate uh measurement on your experience and whether you're having a good one and then from that suggesting to leaders what they need to do. You know one of the things that's clear here is employees in a company where some people have access to copilot and some people don't if you don't you've you're kind of there's a message there. So we're like do something about that you know do something about that this access you know is is really important. Companies where people are being encouraged um even forced to use agents in their actual work um people take that as a sign of respect and care. Even if they resist it they they they take it as a sign of respect is and care compared to to companies that don't. So um I I I think the you know we have a 60 question survey today pretty sure in three years we won't have that um we're we're gonna have a sh a much shorter set uh we'll be pulsing more often we'll be looking at access we'll be trying to measure through those things productivity uh I think we'll be linking up with data systems related to performance so that leaders are able to know uh the linkage between this person their experience trust level access usage performance productivity ROI so it it'll be a very quick line between trust and economics yeah uh to help leaders uh be inspired and I and I think uh Mike and I spent time talking about this yesterday that uh this actually is a point that that that uh that Mike made that we at Great Place to work have written the book on great leadership you know literally but we're gonna have to raise that bar because it's hard to be a great people leader. We know that in addition to that you're gonna have to be technologically stronger. You're gonna have to be more able at prompt engineering for example using the language uh uh of the day to be great you're gonna have to be great at both and at the same if you're really strong technically and you don't have these behaviors you're you're you're you're not that great today. So the bar's gonna get raised for everybody to no longer say well this is just the way I am I'm really strong technically and everyone knows I'm not good with people. Um we're gonna call you a manager then or a great IC but we are not gonna call you a leader because you are not a leader because a leader builds trust and and gets 150% out of people because they want to give it um so I I think we'll be rewriting that chapter on what it means to be a great leader.

SPEAKER_03: 41:34

Well Mike uh Michael mentions access being an important factor here but even beyond access training making sure that the people that have access can actually utilize these tools. How important is training and and what do we think about upskilling and training and that whole kind of arena yeah it's a that that definitely on the training side is a contact sport piece here.

SPEAKER_02: 41:53

You know you we we this is not something that we've taken a passive approach to like you know hey this on-demand out there just go kind of check in on it when you need to um we we issued an AI driver's license kind of beginning of all of this that shared really with people a general concepts of what AI and generative AI in particular were were useful for, but also some guidelines around you know when to use it, when not, what company data what platforms and and and and the governance side of things too which is very important. The where training really sticks is in and around use cases that people are going to interact with every day or a handful of times a week you know at different at different stretches. What what we were intentional about was general training on the concepts what we are intentional and intense on is as we're rolling these out with specific use cases and tools, how do we highlight how people are going to use that and then they're able to reinforce it on some general basis. This stuff is moving so fast the uh I don't think we've ever been in a scenario where we're we're updating our training as frequently as we are given how things are changing and evolving uh but but critical uh to again overcome maybe some of the uncertainty on how to use the tools or how to best use them. The other skill set that's been critically important is is training on prompt engineering. Michael brought this up earlier in the discussion uh you know I was with some of our teams in New York last week and uh the the sophistication of the prompts that they're using for data reconciliation other use cases is off the charts brilliant you know um how do we take the best of what some of those prompts are and make sure that that engineering and those those are getting proliferated out to the broader organizations another really important approach that we're taking to things there. So um you know consistent with the rollout it it's moving very fast. We have to be intentional about it but make it in time it with something that's going to matter to the people that you're addressing it with so it's reinforced on a consistent basis.

SPEAKER_03: 43:57

Yeah love it. Make it resonate make it stick make it applicable to the day to day well Mike Michael's talking a lot about how great place to work plans on assessing and measuring that great place to work atmosphere as you look into the future what are you going to look at as it pertains to worldwide on you know how are we going to maintain being a great place to work with AI? Like what kind of signals or hallmarks would you look for?

SPEAKER_02: 44:21

Yeah you know our our um our focus over the long term has been, you know, how do you balance being a profitable growth company that's also a great place to work for all? And and and I don't I don't see that those sort of centers of gravity across those three things. I don't see that changing. What what I do see though is is the way people are going to get their jobs done and and the speed at which we're able to bring new and innovative services to market is is going to operate at a a rate and pace of change that is going to feel uncomfortable at times. It's going to be unfamiliar at least maybe uncomfortable as a stretch uh but I I'm sure we'll have some of that in there too. So I go back to how do we continue to do some of the basic things and I say basic and that not not they're easy to say they're they're very difficult to regimen and do but these are fairly basic concepts that require intense attention to detail and commitment from leadership to go in and do. But but I look at my my enthusiasm from this comes from a point of uh an example I used with my team yesterday. All those out there listening you know you you you too as well do you remember a time when you were on a meeting and somebody was like hey uh do you mind if I record this meeting? Like five or six years ago that was like an uncomfortable you're like uh well shoot what why are you doing you know what immediately is fear right you that that was the instinct everybody had sure with it. You fast forward to today in terms of what just AI has done in a very simple use case of summarization and our ability to go back and reference those things and I I'm on the call I'm like why we got to record it. We need to record it. We need to record this and so that to me is an example where we start off from a place of fear because we don't understand. Maybe intent is suspicious value is is unknown kind of in terms of where we are and you see how everybody even external meetings I'm having with customers and partners is like hey do you mind if we no not at all let's record it. You know it's it's it's good for all of us kind of thing. And so that little example of kind of momentum and mindset shift is something that I see now happening in 20 different pockets of the organization where initially these things, these agents were met with suspicion. Yeah. You know, well we have an order status agent and well I I I give a lot of order status to our customers. It's like well what what if instead of doing order status we thought about strategic plans to grow and and add more value with that customer. As soon as those things hit the ground engaged and motivated people they take off and I think the next you know three and a half five years it it's going to be a lot more of that than it is maybe what we've had in terms of the the fear uncertainty and doubt uh over the last three and a half years.

SPEAKER_03: 47:06

Yeah. Well to the both of you I know we're at the butt the bottom of this episode thank you so much for for taking the time um I believe Michael you may have even uh switched uh a flight on our behalf so that is very greatly appreciated and thank you for the the partnership so to the two of you thank you again that thank you thank you very much yeah okay big thanks to Mike and Michael for taking time out of their busy schedules to join us here in studio from that conversation three key lessons to consider first trust is the foundation of AI adoption without it even the best technology struggles to take root in high trust cultures people experiment more learn faster and turn AI into an advantage second leadership time is the clearest signal of commitment when executives make AI part of their weekly rhythm not just a side project it cascades through the organization and transforms ideas into outcomes. And third training turns access into impact tools alone don't create value. Teaching people how to use them safely and creatively does. So make sure you're not just handing out the technology but also investing in the confidence and capability to use it as well. The bottom line the future of enterprise AI isn't likely to be decided by algorithms. It'll be by leaders who can align people around them. Those who do will turn the AI era from a moment of fear into a moment of progress. If you like this episode of the AI Proving Ground podcast please consider giving us a rating or a review. And if you're not already don't forget to subscribe on your favorite podcast platform. And you can always catch additional episodes or related content to this episode on WWT.com. This episode was co produced by Nas Baker and Kara Kuhn. Our audio and video engineer is John Knoblock. My name is Brian Felt we'll see you next time