205. Say What Sucks: Catalyzing Organizational Change with AI

[00:00:00] Matt Abrahams: When it comes to AI, catharsis catalyzes change. My name is Matt Abrahams and I teach strategic communication at Stanford Graduate School of Business. Welcome to this special live episode of Think fast Talk Smart, the podcast recorded at South by Southwest. Many of us know about AI and some of us even use it. But how do you bring AI to your organization and make it have a positive, productive impact? This is what I have been curious about for a long time. So when my friend and two time former guest, Jeremy Utley asked me to facilitate a panel to discuss his AI implementation work with the MBA's, Portland Trail Blazers, I jumped at the chance to speak with Jeremy, Christa and David. And I have to say it was a slam dunk for AI best practices and learnings we all can implement. So without further ado, let's listen in to our conversation on the South by Southwest stage.

[00:01:07] Well, good afternoon. My name is Matt Abrahams. I teach strategic communication at Stanford's Graduate School of Business. I host a podcast called Think Fast Talk Smart. It's all about communication skills. We're very excited today to talk about the particular application of AI within a business, uh, this business is in the world of professional sports, the NBA team the Trail Blazers. And I am honored to be on stage with these wonderful guests who have actually employed and deployed AI, and we're here to share their experiences and best practices with all of you. So with that, I thought we'd just start with quick introductions. I'll start with Jeremy, farthest away from me. Go ahead and introduce yourself briefly and share how you're connected to the team. 

[00:01:48] Jeremy Utley: Hey everyone. I'm Jeremy Utley. I am an adjunct professor at Stanford. Been there since 2009 or so, teaching mostly design thinking innovation, creativity at entrepreneurship courses. And then my world, much like many of you was rocked a couple years ago when ChatGPT came out. Unlike most of you probably, I had just written a book about creativity and a month later this tool that's amazing for creativity came out and I look in the index of my own book, the AI is not even in it. So I strapped myself into the front row of the classroom as a student, and I spent the last couple years trying to get as close as I can to people like David and Christa who are doing this stuff in the real world and learning from them as much as I can and then sharing as publicly as I can. And so it's really fun to be here with all of you. And I thank Matt and Christa and David for allowing me to join the conversation.

[00:02:37] Matt Abrahams: Thank you, David, how about you? 

[00:02:39] David Long: Yeah, I'm the VP of Digital Innovation with the Trail Blazers and the Rose Quarter. We're, uh, dual business for concert events and basketball. My teams run digital products, app, web and arena, digital products as well, and then digital marketing. And then recently we are taking on the strategy and implementing the strategy around Gen AI for our company.

[00:02:56] Matt Abrahams: Thank you. Christa? 

[00:02:57] Christa Stout: I'm Christa Stout. I oversee strategy and innovation for the Trail Blazers. I've been there about 11 years and get to work with David and Jeremy on our AI strategy and implementation.

[00:03:08] Matt Abrahams: Excellent. Thank you. So many of us know how basketball is played and we see what your team does, but a lot of us might not understand the business behind basketball. Christa, could you spend a few minutes talking about the business side of what you do and then Jeremy, I'd love to have you share how the Trail Blazers came to explore AI and, and get this whole project started. So we'll start with you. 

[00:03:29] Christa Stout: Yeah, for sure. So our business is set up into three areas. The first area is the one that people probably think of when they think of the Trail Blazers, which is our basketball operations. So that's players, health and performance coaches, et cetera. It's one element of the business. Another element is actually our venue operations, so the people that put on the concerts and events and all that. And then we have our business operations, which for us is about three hundred people. And that is run in the same way that probably any organization you've ever worked at is run. HR, finance, sales, marketing, et cetera.

[00:03:59] So for today, we thought we'd focus on that part of the business operations because hopefully it's most relevant to you all as well in your AI journeys. And my boss, who's our president of business operations, in August of 2023, we took the time to go to this AI training and he came back and he was like, Christa, we gotta figure out how to implement AI across our organization. Like it's the future. We have to figure it out. And at the time David and I had been, because we're in charge of figuring out emerging tech, we had been talking to Jeremy about a whole other thing and we pivoted and we were like, so Jeremy, can you help us figure out how to implement and create a strategy for AI instead? He was like, yeah, let's do it.

[00:04:39] Matt Abrahams: So David, AI came about as a result of your boss essentially saying this is an important thing to do. What were some of the burning questions that you guys had that brought you to Jeremy? 

[00:04:51] David Long: It's an emerging tech. It was something we were excited about, but there was no professionals on staff that understood like how to take this and run with it necessarily. 'Cause it's brand new. And machine learning obviously is something that's been around for a little while. But this from a Generative AI side and being an accessible technology was new to us. So who's gonna take that and run with it? We looked internally, we found people who could turn ideas into action, but we needed someone to be the barrier breaker for us.

[00:05:16] And the way I refer to that is someone who says, who could show that it's accessible, that it's something that's fun, it's something really impactful. Remove some of the fear from our staff around something new and then just tear it away brick by brick and the wall that people might have put up around, I can't do this. It's too challenging and I'm scared of it. Like all these sort of things. And so how can we remove those? Whether that's within one-on-one sessions, a group learning sessions, sharing how you use AI personally was a big one for us. So that's the thing that kind of jumpstarted everything. 

[00:05:47] Matt Abrahams: I wanna come back to the change management piece of this because it's definitely challenging and I'd love to hear what you all did. But Jeremy, what excited you about this part of the relationship that you had with the team? 

[00:05:57] Jeremy Utley: These guys are the ball game for me because we had already been collaborating, as Christa mentioned, exploring different kind of technologies or businesses or we were doing all sorts of stuff. 'Cause we had kinda had a kindred spirit in terms of our willingness to experiment, try new things, and I came to appreciate and admire the way they were approaching experimentation in the business. As Matt, you and I actually talked about this on another episode of the podcast and we talked about that research there, but I had been privileged to be a part of this research program where a partner and I were basically studying how does Generative AI impact creativity? And we found some kind of counterintuitive stuff.

[00:06:32] But I would say armed with those observations and insights about how do normal people get the most leverage outta this technology. But I had, there were a lot of ideas I had. And when they came to me saying, hey, is there something here with AI? To me, I saw an incredible kind of almost sandbox and opportunity to collaborate with folks who I could test some of my ideas with. So because I already knew them and I knew they were the kind of people I wanted to work with, and because I had a bunch of ideas that I had studied in the lab, so to speak, it felt like the perfect opportunity to test some of those hypotheses.

[00:07:05] Matt Abrahams: Excellent. And David, I'm curious, how did you identify the problems first to apply AI to, and how did you prioritize those? 

[00:07:13] David Long: Yeah, I think after we had done some learning sessions with Jeremy and try to get the baseline up with Gen AI knowledge for our staff in general, we started to reach out to individual departments, well all departments actually, invite them to a lunch and launch is what we coined these type of practices.

[00:07:28] Matt Abrahams: Lunch and launch. 

[00:07:29] David Long: Lunch and launch.

[00:07:29] Matt Abrahams: Like it. Yeah.

[00:07:30] David Long: And we would get as many people from the department as we could to get into a room with us. And the whole concept was to share with them, let's talk about your systems and within your systems, what pain points do you have? Let's identify those pain points and let's, let's not start with one and say, this is the one we have to make it work. We want ten pain points, we want twenty pain points. 'Cause who knows, like the way AI works, we can solve for one and then potentially have a list of a ton more we can tackle next. Let's find that first one. And so we'd go through and we let people talk cathartically about their job and what bothered them and what could be done better. They could spend more time doing something else.

[00:08:02] And then we would take that, we would assign a co-pilot from that department to assist us throughout the process with the strategy in mind that keep these people as close to the build as possible. 'Cause they're closer to the problems than we'll ever be. So with them in tow and in helping us out, we would build, utilizing AI, to either build a software, build a Slack integration, build simple GPT, that sort of stuff, and then pitch it back to them, and then get the response. And then from there we would then a level of measurements. We can see how it's performing under a couple filters of is this feasible and sustainable long term? Does it impact business efficiency, revenue, or fan engagement? Are they gonna adopt it? And what checkpoints can we put in place so that there is adoption? So lunch and launches have been super powerful. We plan to do two builds per department for every department.

[00:08:49] Jeremy Utley: Can I say one thing about lunch and launch? There's a clear role of branding. And Christa as a marketer, she understands that. I can't overestimate the importance of branding, and I've got an AI focused podcast where I talk to AI leaders in different organizations. I think about JJ Zhuang , who's the head of AI at Instacart. Their internal effort they call the Carrot AI team. Because the carrot is their mascot, okay? I talked to Brice Challamel, the head of AI of Moderna. They call their internal team the GCAT, which are the core components of DNA, but the Generative AI champions team. But I think there's a role of even thinking about the effort as branding it. It gives it a sense of credibility. Oh, you've heard of the lunch and launch and you, you haven't been to a lunch and launch? There's something to that that I think when you talk about change management, thinking about branding stuff is actually a meaningful part of it. 

[00:09:37] Matt Abrahams: And it sounds to me that not only did you take the time to brand it, but you started with people identifying their pain points. So all of a sudden you're not coming in and saying, we're gonna use this new thing to fix things. You had them share what their concerns are, where their challenges are, and then had them thinking about how AI can help. And what's very clear in the literature on influence and persuasion is that when you get people to buy into the problem early, they're much more likely to adopt and follow through. So I think that's beautiful that you did that. In addition, it sounds like you also came up with very clear criteria or what success would look like, so you'd build some things and then you had some clear criteria, which I think is a good bit of advice for everyone. Did you do anything in particular to help prioritize which things you focused on first? 

[00:10:22] David Long: We managed the project from a top level, right? We were running all these different lunch and launches. So we saw that what was coming in and then we could use the same filters without everyone involved and say, this one's gonna really impact our revenue. This one's really gonna improve customer experience. And then communicating that back to stakeholders. And we had a copilot along with us too, so we can utilize them to spread that message within their group. Like it looks like the timeline for your build is in two weeks. Hope you're all excited. So like, just kind of managing that, the expectations around this. 'Cause everyone was excited, but from an overall top down, what's most impactful for the business, that was something that we would manage. 

[00:10:55] Matt Abrahams: I love that as somebody who teaches strategic communication, that you were including communication throughout the process. That's really important to bring people along and to keep it going long after you've created that particular solution. I'm hoping each of you can give us a concrete example of something you did that is impacting the business. Christa, do you mind starting with something that you saw really impact the business? 

[00:11:17] Christa Stout: Yeah, for sure. So the builds that David's talking about, we have about thirty-five of those that we've done across the company, and my favorite one currently is called David Detractor and his counterpart Kelly Kindness. So I assume that you all, like us, send surveys to your stakeholders, to your customers, to get qualitative and quantitative feedback. We were doing a really good job getting and visualizing the quantitative feedback so that we could learn from it and implement it. But the qualitative feedback was much more complicated. So we dug into it during one of the lunch and launches and learned that a couple different people were spending combined almost forty hours a week.

[00:11:54] So almost an entire full-time employee's worth of time just digging into the qualitative responses from our post-event surveys. We have like millions of responses over the course of the year, not all of them have qualitative responses. But people go into the system, read it, decide if they needed to send it to someone else or not, decide if they should respond, get approval to do a make good, if they had a bad experience, et cetera. It was just like a lot of mundane work. And so David, I guess you, did you name this after yourself, David Detractor David?

[00:12:21] David Long: It was the first one, so I think it was the easiest one for me.

[00:12:23] Christa Stout: David built an alliterative tool, David Detractor, that ingested all of the post-event verbatims, filtered out the ones that we didn't need to respond to. When people were like, boo. You're like, okay, I'm not responding to that. But if people have a specific thing that we need to respond to, that would actually go to a specific Slack channel where people that were relevant to that Slack channel, and I'll give an example in a second, could read it, put a specific emoji on it that then creates a draft in their outlook outbox to send to that person. So before took forty hours of people's time, now takes seconds and two clicks. So my favorite example of this recently is actually this person who came to a game and really wanted a vegan hotdog, but the hotdog bundle didn't include vegan hotdog. So she has this detractor feedback, it surfaces automatically to our head of F and B who reads it and is amazing.

[00:13:13] And she's like, hey, we should include the vegan hotdog in the hotdog bundle. So she makes a change in the operations of the business. Hits one click, responds to the person, gives her an F and B credit to come back and to get a free hotdog. And this person now hears back from us right away, right? So it works really well on the detractor side, as you can see, but it also works on the promoter side where we can surface really any positive experience someone has at a game. We surface actually across the whole company. Which is really nice because if you work somewhere and you have no idea how the experience is, it's really rewarding to see these and read about these positive examples that people have across the company.

[00:13:51] And on top of that, they're often like the warmest leads we could possibly have. Like they're hand raisers. Someone literally said the other day, I had the best time at the game. I wanna come every week. And so we're like, hey, sales team, you wanna call her? She seems interested. So to close on this example, it drives revenue 'cause it services warm leads. It improves our customer experience 'cause people hear back from us. And it improves efficiency, so we basically cut out one FTE's worth of mundane tasks as part of this process. 

[00:14:20] Matt Abrahams: It's a great example of how it was able to help you. F and B, food and beverage. 

[00:14:25] Christa Stout: Sorry. Yes.

[00:14:26] Matt Abrahams: Just making sure everybody's following along. David, please, what's one of the things that you're proud of or impressed by?

[00:14:30] David Long: One other addition to the Kelly Kindness piece. One, name your bots. That's also a part of our branding strategy. People can refer to them easily. It's great.

[00:14:37] Jeremy Utley: It's a pro, it's a pro tip. Name your bots and give them a human personality. 

[00:14:41] David Long: Correct. I think a lot of talk around Gen AI is one of those concerns around disconnecting human to human connection because of the use of these tools. This is a perfect example of how it's actually increased human to human connection. I think on Kelly Kindness in particular, we're acknowledging folks who had really good experiences trying to solidify like a core memory, a core moment for them, and build fandom. We'll admit there's areas where that was happening and very small scale, but now the scale for that is like immense because of this tool, and so I really like to call that one out in particular.

[00:15:11] Matt Abrahams: I recently was interviewing somebody else and they were talking about how they have built into their system whenever an employee calls in sick, they have a bot that automatically will send them chicken soup for their house, and it's a way of showing kindness and showing that they care. And that somebody's monitoring that you're not at work that day. So it does a whole bunch of things. So this ability to drive connection, I think is important. Is there another tool that you are pleased about? 

[00:15:36] David Long: Yeah. Another named one Billy Brand. So Billy Brand is trained on our complete content style guide, our brand guideline book. Some history about the Portland Trail Blazers, anything else that our brand team, PR team deems appropriate to be within there. And the main pain point we're trying to solve here is try to avoid is revisions. And I think that's one thing that this thing was trying to solve for is, if you're having copy, if you're having creative, if you're having anything that's supposed to be public facing, let's have a tool that we can load it up, it can audit all that stuff for any brand things that are not aligned, give that feedback, give suggestions on how to fix it. And so we're trying to cut revisions from six, seven down to one, two, three. Can we get it down so we're not spending time doing that stuff, moving these campaigns forward and moving the best campaigns forward. So Billy Brand has been really impactful.

[00:16:21] Jeremy Utley: Just, just to make sure I understand the kind of economic impact. You're saying a typical, say somebody in marketing or insert department here, they're getting feedback on how to align more with the brand voice, six, maybe six or seven times in some cases. And this tool's taking it down to two or three times.

[00:16:39] David Long: Yeah. 

[00:16:40] Jeremy Utley: That's cool. 

[00:16:41] Christa Stout: We also been upwards of ten or fifteen times. 

[00:16:43] Jeremy Utley: Wow. 

[00:16:44] Christa Stout: Six or seven is 

[00:16:44] Jeremy Utley: It's generous, conservative.

[00:16:46] David Long: Yeah, the best, for adoption purposes, it's still, this is one of the first ones I built, so I actually built it without someone helping me with it who was closest to the pain point. So it actually went through a couple different systems. One, it was like, it previously used to be within Slack, but people were like, I don't want to use it in Slack 'cause then everyone can see that I don't know how to do this or that. I was like, great point. So it's now a web-based software that we're rolling out to folks and I had one member of my team who complained that he ran outta tokens the other day and I was like, that's the best problem I could ask for, so. 

[00:17:16] Matt Abrahams: And I'm sure it's one hundred percent brand compliant, that website.

[00:17:18] David Long: Absolutely.

[00:17:19] Matt Abrahams: Excellent. Very good. Jeremy, what's one of the tools that you're excited about? 

[00:17:23] Jeremy Utley: I, I'll give a non Trail Blazers example, if that's okay, just to broaden the aperture a little bit. But I've had the privilege of working with a bunch of, this is gonna sound crazy, but a bunch of park rangers in the National Park Service. Which is super cool. They reached out somehow. I don't even know how. Hey, all of our backcountry rangers and facilities folks wanna learn how to use this tool. Can you help? I was like, totally. And we did some kind of basic foundational training, and one of the things that we focus on, similar to the conversation about pain points that Matt's drawing out of David here is what sucks about your job? What takes way more time than it should?

[00:17:58] And a really great kinda stem for finding opportunities is to finish the sentence, it sucks that dot dot dot. And we had people just think about that, what sucks. And one of the folks on, in this group as a group of about sixty folks, he said, it sucks every time I've gotta replace the carpet in the lodge. He worked at Yellowstone or Yosemite, something like that. Every time I gotta replace the carpet tiles, I've gotta fill out 10 pages of federal funding requests that include OSHA requirements and ANSI standards and historical heritage site removal preservation. He's, I'm like a back country ranger, man. I don't know the answer to this stuff.

[00:18:38] So he built in forty-five minutes a tool that could reference all of the relevant databases of information, including expense information, all that stuff, and would take a crack of first pass at drafting the document for him. And it took him, he said, whenever, he said the last time he had to replace a carpet tile, it took three days to fill out the paperwork. This thing took fifteen minutes. It took him forty-five minutes to build it, so call it an hour in total. But three days minus an hour is not bad. But here's the really cool thing. When you codify these workflows and simple kinda shareable tools, the individual who builds it gets the benefit, but then anybody else for whom it's relevant also gets the benefit.

[00:19:18] So in his case, name's Adam. I try to tag him on LinkedIn to shout him out. Homeboy doesn't even have a LinkedIn account. Alright, so it's like this is someone who literally has no presence on the web, no tech experience, and someone shared his tool. There are four hundred and fifty parks across the US where there's a role like his, the National Park Service is estimating that tool is gonna save the National Park Service seven thousand days of human labor this year. Just his tool.

[00:19:46] Christa Stout: Wild.

[00:19:47] Matt Abrahams: That's amazing.

[00:19:47] Jeremy Utley: But the shareability of it, right? The fact that Billy Brand is shareable, it would be useful maybe just to you, right? But now it's useful to anybody who's trying to create brand aligned communication. 

[00:19:59] Christa Stout: Which is everybody. 

[00:20:00] Jeremy Utley: Which is everybody, right? Yeah.

[00:20:02] Matt Abrahams: So I'm hearing a couple things to take away from this. First and foremost, that these tools can build connection, not reduce connection. Two, it's really important to think about where you place the tools. And how you involve people in the process. Three, the shareability of these things is really important, and so I love the specific examples, but the lessons that we learn, I think are really important. AI for non-technical people can be intimidating, maybe not for one Park Ranger, but for many people it can be. Christa, how did you help make AI accessible to your less technical folks? 

[00:20:35] Christa Stout: Yeah, I think you said it as part of your recap. It was, for us, it was figuring out how to connect with people and bring people into the process. So when my boss Dwayne said, hey, you gotta figure out how to like have everyone at our company using AI eighteen months ago, I was like, well, I don't know how to do that. So the first thing I did was on a full team call, I just asked if anyone that was using AI wanted to come talk to me or be part of a conversation about how they're using it, what they liked about it, what they don't like about it. Let's just talk and then go from there. And so it's like tapping into people who were like, we had thirty-five people who were already using AI eighteen months ago, who were then excited to share what they were using it for. And whose job is not to create strategy for new tech across a business, but they got to be a part of that and got to help shape it.

[00:21:24] Matt Abrahams: I'm curious, Jeremy, what have you seen beyond the Trail Blazers that helps organizations bring AI beyond just this as an IT initiative, but how do you bring it to everybody in the organization? 

[00:21:34] Jeremy Utley: I don't think we have to look very far beyond the Trail Blazers. I think they're like a great case study of creating space for folks, creating venues and mechanism, venues for sharing and for celebrating mechanisms, for learning incentives where we can get into all that stuff as well, right? But there's a bunch of pieces there. I think one simple thing that has really helped a lot of folks I talk to is when they say, I don't know how it's relevant to my job. The kinda meta hack, which feels like a Yodaism, but is not, is you can use AI to use AI. The basic idea is if you're not sure how AI can impact your work, you can actually pull up Chat or Claude or Gemini, whatever. I, I'm not model agnostic, but I'm not hyping a model here, but you can pull up any of 'em and say, hey, I have no idea how to use AI in my work.

[00:22:24] Would you act like a insert LLM here, Chat expert or Claude expert or Gemini expert or Grok expert, act like a Grok expert and interview me about my job so that you could recommend three to five obvious and maybe totally non-obvious ways I could use AI. And you know what? It'll totally do that. The biggest thing is actually getting your imagination sparked. And most failure to use is actually a failure of imagination and part of the value of mechanisms and forums like lunch and launch and like gathering people together, is it helps broadcast and showcase a bunch of things that people go, I would've never thought to do that. And basically what you want do is create these forums where you kinda give these forehead slap, I can't believe I've never thought to do that, right? And if you can provide enough of those moments and then celebrate how people are trying stuff, it's just kind of a snowball effect.

[00:23:13] Christa Stout: I'd just say, just to build on that, but one of the things that Jeremy unlocked for us that also helped with the change management was tapping into personally relevant AI examples. And so rather than starting with how can AI help me do my job better, which is great and helpful, we started with prompts that, that really tapped into personal issues that people had. So not work appropriate personal issues. So for example, think of a decision that you have to make in your life. It's a hard decision. And then Jeremy had a whole specific prompt that we just like copy and paste it into ChatGPT where we described the decision we had to make and some of the challenges, and asked ChatGPT to interview us to get more context. And then to work through that challenge with us. So I did it about my daughter starting kindergarten. Schools and whatever, and it was so helpful, right? Like the kind of advice that I wouldn't, I just never would've thought that an AI tool could help me with that then sparked a million more ideas around how it could benefit me at work.

[00:24:07] Jeremy Utley: That was actually inspired by a life experience, right? We ended up doing a series of emails or Slack something, right, where we basically said, here's a use case. Here's a prompt you can copy paste, and here's a video of a professional nerd in California doing the thing, right? And the only reason we even did that, by the way, is 'cause I had this true story about my, in my personal life. I'm riding with my grandma in the car one day. She lives in Oklahoma, she's mid nineties. I love her. I love you, granny. If you're listening to this and we're driving the car, she's like, hey, what is this chat thing that you're working on? And think about, how do you answer that question? Your ninety-five year old grandma asks you, what is Gen AI.

[00:24:38] You know, and I'm like, what's an emotional question you'd ask Faye Ann, who's her neighbor, that she'd ask Faye Ann about. And she goes, I thought this was technology. I go, just bear with me just for a second. She said, we don't even know how to think about assisted living. And I said, let's invite my friend ChatGPT to the conversation. And I'm driving, she's in the passenger seat. I just said, hey, my grandma just asked me about assisted living. I don't even know what framework to reference. I don't, I have literally no idea how to think about this. Before you give us any advice, would you ask her three or four questions so that you can customize your advice to her?

[00:25:08] And said, sure. Have there been any changes to her mobility recently? You know, I hand her my phone and she's like, this is amazing. And I said, the tech's pretty cool, right? She goes, not the tech. I've never thought about assisted living like this. Two days later, I get the, my favorite text message ever from granny. Jeremy, we're out of cream, of mushroom soup for the green bean casserole. Do you think your chat thing could help? To Christa's point, the reason she thought of the work application was because she had this personal experience and that made me realize, and then I just, all these random things in my life, we happen to have this opportunity. I said, hey, instead of starting with work, let's start personal. Let's give the first prompts personal so that people feel like they have this kind of imagination opening experience where work effectiveness or productivity isn't hanging in the balance. 

[00:25:53] Matt Abrahams: That story is amazing for so many reasons. One that your ninety-five year old grandmother is texting. I find that fascinating. And second, this notion of making it personal first to get people connected. And this idea of bringing people together to share at Stanford, where Jeremy and I both teach, they do this thing called Appy Hours. So people come together to share the different apps that they've built so that you can then learn to leverage it and just the name Appy Hour and they do serve drinks. It's a fun experience to share building more on that creativity. I wanna pick back up on that notion of allowing for time for this. How did you at the Trail Blazers actually give permission to people to take the time? Because I'm sure people are saying, I already have a full-time job. I don't have the time to do this work. David, did you do anything in particular to give people permission? 

[00:26:40] David Long: I think to couple along with what you all are just saying, I think it does start individually and looking at personal uses cases to, with an end goal of like empowerment. Can this tool empower me? Because if you reach that level, then you stop thinking about replacement. You stop thinking about things that are negative connotations with Gen AI and then you can be a proud displayer of what you're able to come up with. This is what I did. Lemme share it with my staff, whether that's personal or something work related. They see it and then instead of saying, hey, are you using AI?

[00:27:09] So they're immediately put on the defensive. You say like, here's what I did. Have you tried this? Have you tried using AI for this? Or something like that. Just trying to rephrase it around empowerment and trying to get an end result has been super helpful, and just making the time is difficult. But in the end, once you start it, you realize that there are benefits of using it, that it cuts down on some of the manual labor that you have to do and allows you to focus on more important things.

[00:27:32] I refer to it as a utility. It's gonna be a next utility for us. Implementing electricity, okay? Companies got rid of gas lamps. It's one of the most obvious things to do right away, but the people who really take it to the next level is like, how can they use electricity to improve their production lines, improve revenue, improve all those different things. So I think you have to do it 'cause it's a utility. It's not, it's not a new flash in the pan. 

[00:27:54] Christa Stout: Yeah. And we would also, like, we had a Slack channel where we would just encourage people to share like, hey, I just took a picture of my lunch and asked it how much protein is in it, and guess what? It knew exactly how much protein and what I was eating and blah, blah, blah. And so we just were like constantly encouraging people to share how they're using it so that it is demystified and encouraged. And so the result of that is that David has someone that works on his team who just like went off without even asking, built her own software that replaces an existing software that we spend a lot of money on today. And I think it's because we, like she knew top down that Dwayne, our president and others supported its part of our business planning process, et cetera. But also it's just so encouraged across the organization from that initial AI committee, from David's lunch and launches like it's encouraged and celebrated. And when you celebrate something, people tend to wanna do it. 

[00:28:47] Matt Abrahams: The literature on motivation is very clear that if you put people on the defensive, they're not going to be motivated to do something. And it sounds like you've worked very hard to reduce that defensiveness and give people an opportunity and to celebrate, as you said, to help them, and that's really an important step. Can we talk a little bit about the change management to actually get people across the organization to use these tools? It's one thing to build them. Is it simply that people see the benefits, so therefore they use them? I can imagine some people are really comfortable in what they're currently doing and the current way they're doing it. Have you done anything to help with the change management to keep the momentum going? 

[00:29:22] David Long: I think individual groups adopt faster than others, and I think the best thing is just to come back to the lunch and launches. Within those groups, there's people who have not used AI yet. There's people who have, but it's a shared space where we can talk about a similar topic and talk about solving problems and it's specialized to what their main focus is. So I would say that those are incredibly powerful. One, for we are there to build something impactful, but for the shared space of communication and things like that. That's major motivator for change management. 

[00:29:49] Christa Stout: And to go back to Jeremy's sandbox point, the David Detractor Kelly Kindness example that I shared earlier. So when David first built it and launched it, it's not like people just started using it right away. People, a lot, sometimes a lot of people didn't use it at all. So then we had another meeting and a conversation. We're like, hey, what is keeping you from using this? What would make it easier for you to use what, you know? And so like I, you iterated that product for a couple months before, and now it's just like everyone's using it and it's everywhere, but it took months of iteration and learning and feedback and communication to get to that point. 

[00:30:21] Jeremy Utley: Were there any key revisions or key iterations that you feel like unlocked people's ability to use it? Like what was keeping someone from using it? I'm just dying to know. 

[00:30:29] David Long: It was me. I think one, one part of it was that I was not solving for the user's problem, so I needed to stop and overproduce something that I envisioned would be helpful. And that's, this was before a lot of these lunch and launches a big component of what we now implement, but getting with them and saying, does this actually solve your problem? In what ways? Why? And what does it allow you to do? What impact do you think this will have? So that, that's the main thing. If you're solving for it by yourself, you're gonna have revisions, you're gonna overdevelop, and you're gonna probably have less adoption.

[00:31:00] Jeremy Utley: Matt, just thinking about your question of what drives adoption is kinda what you're getting at. To me, as I'm listening, I go back to the very beginning, which is everything's rooted in employee pain points. Of course, people want to use something that's actually making their life better, but I think importantly, critically, David and Christa did the hard work of figuring out how their lives need to be improved. So they didn't start with a broad mandate of, let's just use Gen AI in general, right? I think the usage metrics are largely irrelevant there. What they did is they said, what are the problems? What really stinks in your job? Let's build a solution there. And then it just creates suction, it creates pull. This makes it easier. This makes it better. No brainer, right?

[00:31:41] Matt Abrahams: Absolutely. 

[00:31:42] Christa Stout: And like I love the, it sucks, that prompt. It's a really good framing. It turns out people really enjoy talking about what they hate about their jobs. And so we had, we set up hour sessions and then we would always have to cut people off at the fifty minute mark and be like, okay, now we're going to switch to solutions. You used the word earlier, it's cathartic for people to be like, oh, and if only. And for us to get that insight across the company of like the systems, like the key systems across our company and how they do and don't work effectively. And then the problem solve for those also gives us a lot of insight, which my hypothesis is that ultimately it will help us be able to figure out where and how AI is going to significantly transform our business. Like right now, this is all incremental innovation across a lot of different work streams, but by getting this insight across a whole company, it is already opening our eyes into ways we can like really potentially transform the business more broadly. 

[00:32:33] Matt Abrahams: Anybody who knows anything about me knows I love alliteration, so catharsis catalyzes change. I like that. For those in the audience looking to expand AI in their organizations, whether they're technical or not, I'd love to hear from each of you what's one concrete action they could take next week to start making progress with AI? Why don't we start, Christa with you. We'll just go down the line this way, if that's okay. What's one thing they could do? 

[00:32:58] Christa Stout: I mean, it's self-serving 'cause this is what we did, but I think just recognizing that you don't have all the answers and don't need to have all the answers when it comes to AI and how to implement it. Like you have to step and trust that the path will follow. And also admit that you don't know everything. 'Cause literally nobody in the world knows everything about AI. So the idea that you would be expected to is a little crazy. So I think just admitting vulnerability, starting with curiosity and understanding like what's already happening at your organization so you can tap into the latent motivation and create momentum from there.

[00:33:33] Matt Abrahams: Excellent. So start with vulnerability, follow with curiosity. Very good. David, what's one thing people could do starting next week? 

[00:33:40] David Long: I think at the leadership level, critically about who within your company or under your team who exhibits like behavior of taking ideas and turning them into action. I think that's a person that you should have a one-on-one with and present AI as an opportunity for them. 'Cause that's a huge unlock if you have someone who can move things forward that way, 'cause this is a powerful tool in the right hands of someone like that. As an individual, like I mentioned earlier, do a complete audit of some of your systems. Whiteboard out. Here's one for example. Like every month I have to balance my credit card and so I need to know all the codes to send all these different charges to across marketing, across our corporate partners, all that sort of stuff.

[00:34:16] I know it takes four different sheets. I know I have to reference control F, all these different sheets to find these different codes. It takes me two hours. Talking about cathartic, like this is one that I absolutely do not like. And so within that I was able to mark just with little carrots maybe I could use something that understands all of our codes. Maybe I could do something that can be accessible within Slack and answer it right away. So that's something that's, that's taking it to the next step. But to, to your answer your question, it's just like audit something and see what's possible and then go from there. 

[00:34:45] Matt Abrahams: So the audit point is well taken, but you bring up something that we haven't really talked about, although you mentioned it, is buy-in from more senior leaders is really helpful. And taking the time to make sure they're on board can help. And in your case, to really drive the event. Jeremy, what's one thing these folks could do next week to make a difference? 

[00:35:03] Jeremy Utley: We talked about earlier, but I think have AI interview you about either your life or your work to identify opportunities. Tell AI it's an AI expert. Which, by the way, a role is a critical part. If you've been playing with AI at all, you know this, you gotta give it a role. If you're talking about a parenting challenge, hey, you're a child life psychologist with a specialty in childhood development in teenage girls. I have four daughters, so I've used that prompt a lot, right? But the point is, you're an AI expert. You're here to give me a consultation of how I can use AI better in my blank. Would you ask me five questions one at a time, because I'm a human and struggle to answer more than one question at a time, please? Something that simple.

[00:35:44] The other thing I would say about leaders, by the way, leadership buy-in is not some nebulous, abstract thing. If you're a leader and you want to give buy-in, do something yourself and tell the team what you've done. Because to say, hey, y'all have permission to go do it, is totally insufficient and it's far too passive. And the best leaders I have observed, they are actively showcasing what they're doing on Zoom calls. Let me share my screen for five minutes. I wanna show you guys what I've been doing. That goes so much farther than, no, really, you're free to try it on your own time, no problem. 

[00:36:16] Matt Abrahams: And what's even more important is to, as a leader, to share your struggles and challenges and failures, because that gives permission for others to do that. Because it's one thing to say, go do it, and here's what I'm doing. If people feel there's has to be perfect, just like yours was, that can be challenging. Before we wrap up every episode of my podcast, I ask some typical questions. Due to time, I'm just gonna ask one question. We'll do it very quickly. The final question I always ask is, what are the first three ingredients that go into a effective communication recipe? And since there are three of you, and I'm asking for three ingredients, just very quickly, name an ingredient and then we'll wrap up. Christa, what's one important ingredient that for successful communication?

[00:36:54] Christa Stout: Oh, since it's his birthday, I am gonna say something that Jeremy does really well, which is turn complicated objects into very clear messages, and communicate them very well.

[00:37:05] Matt Abrahams: Make 'em accessible. 

[00:37:06] David Long: Constructive problem solving. If you have a problem and you want to present it to your leader or your staff present it, but now you have this tool, AI potentially, where you can come with lots of solutions and you can flood a problem. And so I think anytime you can come to a leader and say, hey, I have this problem, but here's some things I want you to consider about how I want to go about solving it, that's a completely different type of conversation.

[00:37:27] Matt Abrahams: Lead with solutions. Very good.

[00:37:29] Jeremy Utley: Conviction. If you don't believe it, don't say it.

[00:37:32] Matt Abrahams: Three very valuable bits of advice and important ingredients. And lots of interesting steps and recipes today to help all of you be successful in deploying AI. Thank you very much for your time. I hope you're taking something of value away.

[00:37:48] Thank you for joining us for this special South by Southwest live version of Think Fast Talk Smart, the podcast. To learn more about AI and communication, please listen to episode 77 where I interview ChatGPT and episode 134 with Jeremy Utley and Kian Gohar. This episode was produced by Ryan Campos and me, Matt Abrahams. Our music is from Floyd Wonder. With special thanks to Podium Podcast Company. Please find us on YouTube and wherever you get your podcasts. Be sure to subscribe and rate us. Also follow us on LinkedIn and Instagram. And check out FasterSmarter.io for deep dive videos, English language learning content, and our newsletter. Please consider our premium offering for extended Deep Thinks episodes, Ask Matt Anythings and much more at FasterSmarter.io/premium.