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3 Things to Do Before Rolling Out AI in Your Organization · Leading in Change

• Kellie Bourque: Hi, I'm Devin. And I'm Adrian. And today we are here to talk about leading your organization in the age of AI. So last time we were here, we were talking about leading your team in the age of AI. Before that, we talked about managing your career in the age of AI. So this is part three of this three-part series. By the end of this series, you should know how to effectively navigate this new AI environment. So with that. You know, Devin, I'm curious. ⁓ what headlines around AI adoption have caught your eye lately? Let's use that as our icebreaker. ⁓ wow. I think you sent me actually a a New York Times story that was really I can't remember the headline, but it was absolutely focused on ⁓ the organizational level, like you know, what is happening there and how Integration really is the challenge. All anybody talks about is AI, but the disconnect between what that means and for you for an organization and then what it looks like to actually get on that path. So Yeah. I mean, I think in that same vein, this isn't the one that I was going to share, but I was listening to the HBR ideacast yesterday. And one of the stats was something like 70% of transformation efforts fail. And technology implementation is a transformation effort. Framing the problem that we're here to talk about today, ⁓ a common response from leadership is like, we need to just implement it. Like we need to get it out there. You know, I'm working with one company that in the middle of Q4 last year. sent his entire leadership team to an AI certificate program at Tulane, you know, insisted that they figure it out and drive it down in the organization. You know how's that going for ⁓ Right. Well, they still don't have the magic AI bullet, right? sorted out. So I'm curious, you know, what are you seeing happening with organizations and and where are they getting it wrong? Well I think you just pointed out something really important, which is I think They hear AI, they're like, ⁓ AI, we should be doing something. And their solution is, you know, let's get Adrian to come talk about AI for an hour at one of our meetings. And that's not or, you know, there's this, there's this free class or there's this program, this five session program here. But I think it still leaves the gap of, you know. Maybe people know about more tools and they know a few more things that it can do, but I think it still comes down to a lot of just talk about we need AI, we need an AI strategy. But the reality is very few people are using it and the people who are using it are mainly using it to help their emails be better. Yeah. So it's a very limited, there's a big gap. And part of that gap is that. I don't think we re most people really know what they're talking about when they're are saying we need AI. I don't really know if they have a good feel for that, of what they really mean by that. I don't think they know what they mean by that. I think they just know that they feel like that they should be saying AI. That's right. I think that's right. You know, even companies that are implementing it quickly and have rolled it out are now rolling back a lot of those efforts because they rushed headlong into it. And then didn't really think about what the implications, what the process, what all of it would look like. You know, one of one example that I was recently reading about was Klarna. They were in that early, you know, 2004 rush to cut head count and roll out AI implementation across the board. And, you know, in doing so, they learned that AI compounds issues, compounds problems. So you're moving faster. But if you're replicating bad process or you, you know, you are don't have the staff with cut heads and you don't have the people to handle all those edge cases, it's gonna create real problems and friction in the business. And ultimately what they ended up having to do is hire back almost all those people. In fact, there's a stat that 54% of AI-driven headcount loss has been rolled back ⁓ since since this has started. So I think like people need to slow their roll. You know, either on the implementation side, you know, really pause and think about what's our strategy, like you said, or, you know, What's our what are we trying to fix with this? Or what are we trying to grow with this? Yeah, I think you and I actually talked about that a little bit this morning. It's like we say AI, but no one's stepping back and really thinking about ⁓ what tr problem are we trying to solve, just like you said, or how does this fit into how does this fit into opportunities or our strategy or our business plan or where we're heading in the future? And, you know, most things exist for one of two reasons, right? It's either to solve a problem or to move us forward really, really effectively a and fast and ⁓ And I think that piece is skipped. It's it's like and it is often, right? Like when we think of so if we think about just technology change, right? Like we're gonna put in a new CRM or E ERP, and we see that. We've talked about that actually maybe in one of our our last meetings or or discussions about these big transformations, and then they're spending, they're hiring consultants, they've got They've carved out teams to work on this and be it be focused on it. And they get to the point and they were like, my gosh, like we've just spent years and money and consulting time and we've ⁓ not done other things. And now we're either pausing or we're having to completely relook at what did we s think we were doing and go back. And so ⁓ some ways, the trap, right, is that AI is potentially just a sexier, faster. version of that. Yeah. Right. And so where I see a lot of teams get it wrong is they aren't doing that. You know, I think last time we did talk about the slingshot pause of you've got to pull back to fling forward. And so what do you do in that pause? I think it is, like you said, taking stock and saying, what's the value creation opportunity for us? You know, what do we want, how do we want to grow as a company if we have this time savings. You know, if we are able to eliminate some of the minutia through AI, what would that allow us to do with that time back? You know, how are we we're what if our processes are are of high friction? How do we reduce friction instead of replicate bad process and then accelerate all those issues or compound all those issues by using AI, which is I what I see happening. Yeah. Just making things worse. Just making things worse faster. I think that's exactly right. Teams need to slow down, they need to pause, they need to think intentionally, and they need to ⁓ start to plan what this looks like. One of the things that ⁓ I I read recently as a good tactic for this slow down and pause phase before you start moving forward in implementation, whatever that looks like, when you think your leadership team is aligned. Have everyone in the room write down, okay, what are we doing? Why are we doing it? Who's gonna be doing it? What's the end goal? And see how many people are actually in alignment as a leadership team in that work. Yeah, that and that that misalignment or that not being aligned is super common. And and why does it happen, right? It happens because, you know, ⁓ other things that we work with with organizations all the time, which is there's a lack of trust. ⁓ people don't feel like they can be honest about their thoughts or or ideas or feelings about something. And so those those conversations either don't happen, but if they do h even if they do happen, I think there's a lot of times that those aren't super honest conversations. And then because there's often a a push to like, well we have to do something, they could just move forward. And they move forward with that that alignment. And then what you talked about, which which is where things start breaking down and ⁓ is that it shows up. It shows up that everybody's not aligned. And then it starts causing some some challenges. and then you've got to then you've got to stop and pull back. ⁓ ⁓ goes to ⁓ something I I was thinking about earlier and I shared with you. ⁓ that was when you're doing any kind of ⁓ new thing ⁓ you're trying to ⁓ that new thing and make it work for you and you ⁓ it it takes time. It it's not like we decide and snap our fingers. And so in order for to get aligned, to include people, to have it be a shared throughout the organization effort, well, what does that need? Well, you either spend time on the front end setting that up and that feels slow. And so everybody wants to move fast. But that feels slow. It's kind of like the pullback, right? Like, hmm. And then so you move fast and then you do spend time, but you spend it on the back end with frustration, pissed off people, ⁓ you know, wasted time and money. And so you kind of have a choice, right? With with any kind of change or implementation or movement forward. Do you want to you're gonna spend time? Would you like to spend that time proactively on the front end? Or reactively on the back end. And a lot of times back end time is takes more time and is more expensive for a lot of different reasons. So I think when you think about AI, you've got to think about that. You've got to think about alignment strategy. You've got to think about readiness of of the team, ⁓ why you're doing it. And then frustratingly for a lot of people, you've got to invest that time up front. One of the things that you said triggered a thought, you know, in that early alignment, I think it also needs to make sure you have more people than the leadership team at the table, especially when something as transformational as AI is what's being discussed. You know, I see a lot of leaders coming in and viewing AI primarily as a tool for cost savings. And they don't want to bring other people into the conversation because they think nobody wants to make cuts, nobody's gonna take this as serious as me, you know, heads I can't wait to cut head count, you know, is how a lot of people think about it. And instead, there's some orgs that are doing this really well where they say, one, like I said, what's that opportunity for value creation? But what are our non-negotiables as a team? ⁓ working with one organization that said, you know, they feel confident they could replace their project management a lot of it with AI. Well, They said in non-negotiable is we're not gonna let go of anybody as a result of that. So how do we repurpose and redirect those people towards more meaningful work? Right. And I think you shared with me a really great example from IKEA, ⁓ which I loved. I know. So IKEA has ⁓ rolled out Billy, which was a a chat bot for customer service. And it was able to handle, I think it was something like 74% of all customer service calls. So they were looking at the potential to lay off 8,500 people. And rather than lay those people off who had all this institutional knowledge and knew the, you know, catalog frontwards and backwards, knew all the like Billy bookcase mods that people did on TikTok or whatever, they said, you know, what could we re how could we reskill repurpose these people? So they said, look, we've wanted to get into the design industry. What if we reskilled these people to become AI-powered design consultants? So, you know, all those cool tools where you can like drop a chair into your living room. They taught these customer service agents how to use it and unlocked 1.4 billion in new revenue last year from design services alone. So I mean, think about the headcount savings, creating 500 people versus this huge value creation over a billion dollars by rethinking how to retain that institutional knowledge. And then drive the business forward. Yeah. So when you share that with people, because I do think that, you know, one of the big things is like, ⁓ think of all the things we can do once we get this in place and we won't need all these people. So when you share that example, what are people what what are how do people react to it or how are organizations reacting to it? I think it's like an aha. Like people aren't thinking about it that way. You know, I think people are really shocked that there is that kind of opportunity out there because we don't pause, right, as organizations and s and think about How could we repurpose people's time? You know, I think institutional knowledge is the value that people bring in these situations a lot. So I'm curious, is there anything in the past that makes you think about this? About, you know, losing institutional knowledge? I think about this a lot, like this is happening across the board in a lot of manufacturing, you know. So what can organizations do to retain that and capitalize on it? Yeah. And I you know, before I kind of go down that road, I go back to kind of this this old line which is, you know, you can't cut your way to success. And I think the initial thing around AI is the idea that, well, we'll have this quick win and and we'll cut people, which is also the consultant model, right? Like big consultant comes in, you know, we're gonna re w yeah, yeah. Yeah, we're We you know, we could save you tons of money. Well, yes, we can. We're gonna cut a bunch of people, and then that ends up being ⁓ a problem. And I think it's very similar. I don't think you can cut your way to success. And I I think that that mental shift of what what could we do if we could free people up to do things that we have not had time to do? And I think we talked about that last time with teams. You know you and I talked about like even our AI and how we've used it and maybe how we've become a bit more efficient and been able to turn things around ⁓ more quickly for clients and and it's allowed us to in some ways focus on a few things that we kept having to put on the back burner because we were so busy doing right like grinding on on on things. So ⁓ Yeah, I'm curious how like how do you help teams have that conversation? ⁓ what about about the you can't cut your way away to success. Around ⁓ how how do you get out of that mindset and towards a value creation mindset and towards appreciating the talent on your team and thinking differently about how they could reskill or repurpose or or reuse that time. Yeah. Well I guess that's the classic scarcity versus abundance, you know, idea of ⁓ and and and I think this gets in the way in a lot of things when we, you know, talk further about How AI gets incorporated into organiz organizations, because I think there's a bit of a scarcity mindset there too. But what do you mean by that? Well, I guess what I'm thinking about is when we talk about how does AI get actually embedded and used in organizations, there's the lack of sharing that I'm using AI, right? Like, is it okay? Is there some policy against it that maybe I shouldn't say anything? If I let people know I'm using AI, will they think that? I'm not doing my job or I'm cheating, right? And then that gets so that gets hidden. And and that's a little bit of an old the old school mentality of like, well, I'm not gonna tell anybody what I do and how I do my job because then they won't need me anymore. So it's it's some version of that. ⁓ so I think, you know, how do you have those conversations with teams and organizations? I mean, it is definitely a reframe and a reset. And what I expect is as we start working with more more organizations around getting them to step back or including the AI conversation as part of their s part of their strategy, I think that's the opportunity to have to reframe and have people thinking forward and not just about what can we cut? Yeah. Right. Like this is a huge opportunity to cut, right? And and to be leaner. And we know right now and now, you know, I'll pivot to to the the succession or the you know, the the the cut conversation and You know, I would say that that's probably true. You know, it's true for financials. You just can't cut. It's true of people, I think, also. So thinking about accession or institutional knowledge or what might be lost, often it's invisible until something goes wrong because that deep knowledge is what saves you when things don't go as planned. And when you have to rely on you know, experience actually. So there's if anybody's watching ⁓ the pit, ⁓ and you remember the episode where they get ⁓ they get they get hacked and they have they have none of their like stuff is working, And they basically look at all these people and there are people there that are like, we're just going old school, right? And that institutional knowledge is what allows them to get through that twenty-four hours. But the the all the people that have only experienced ⁓ the high tech version are like, huh? What? Like, you know, and they're just basically going back and they end up calling somebody like a retired charge nurse. And they get her in there and she just gets in there and just starts kicking ass, right? Making names and like, do this, do that. ⁓ so it's it's it's a little bit of an example of that. But when you you know, you don't just lose when you lose experienced people, you don't just lose their task, you lose their judgment and their relationships, knowing just who to call or just what button to press, their memory of things and the way they worked or the way they didn't work. So that's what AI can't give you is context. And it also can't give you those relationships. And that that what it's what we call ta right, it's tacit knowledge. It's what's in your gut and your head because you've seen it and you've done it and you've also worked through the ⁓ the blow ups and the problems and those things. And so that's essentially what lose of that is worth you can't just go to the new. There's there's there's what happens between the new and the and what you're moving from. And people are the connective tissue of that. I don't know that you can move forward without completely and and completely erase the past. Yeah, I agree. I wanna I have like have my have a couple thoughts on the different things. Yeah. You know, one of the things you said was around going back to scarcity mindset. And I think that in that, you know, when people say, Okay, where do I start? We say, Okay, let's start with leadership planning and readiness. And I think a lot of people view this as a Technology problem, right? This AI implementation is a what's the right tool to solve this problem? When really I I think it is a people problem. It's a leadership problem. This failed adoption that, you know, or this this f you know, roll rapid rollout and then pull back or this stuck in the mud and not getting anywhere. At the end of the day, it's a failure to address those things you're talking about, right? A failure to talk about the loss. What's this going to mean for ⁓ you know, me and my job that's gonna change? I see some of the most pushback on AI implementation from IT teams. And it's because I think they're really afraid of irrelevance because those are the those are the jobs that were targeted first. And the, you know, people who thought they were gonna have a stable, solid career as a software developer are now being, you know, ⁓ pulled back in a way that they their value is being pulled back in a way that they didn't anticipate ever. And so I think acknowledging that, you know, i is like step number one. ⁓ and and that's what I mean by s like what are the non negotiables then? You know? So ⁓ d are we committed as a team towards openness and visibility and in encouraging that openness and visibility? Are we, you know, and sharing how you're using AI and what you're using it on? How are we creating the safety around that? Well, and it I think it does get less scary when you talk about it. What how so well I mean, I think when you surface things, then you can address them. And so, you know, in a in a high change world, right, ⁓ brittleness and an and anxiousness or or brittleness of systems and and anxiousness of people are some of the things that are are part of that. And there is a lot of anxiety. And look, the most human thing in the world the most human thing in the world is to is to think when something new happens or a change happens, what do I have to gain or lose by what is happening right now? And so that is, you know, welcome to the human condition, right? That's that's that's part of it. And we wouldn't be human if we didn't have those thoughts and and there's nobody no one cannot tell you that they don't start there on some level. and the people who are successful though are able to move quickly to what we call kind of owner mindset, which is the looking at what's possible, what could be, what might I learn, right? How what good can come from from this? And ⁓ there's another thought I have about what if you get stuck, if you get stuck in the mode of ⁓ my God, why is this happening? Why is this affecting me? This is horrible. Who made these decisions? I'm I'm just gonna not participate. And you there's no there's no real there's no real dividend or plus side for that for the individual. Things are moving ahead. And so if you get stuck and you can't move. forward, which I think everybody's capable of, maybe just at different times and the different ⁓ you know, ⁓ ways of doing that, that's ⁓ just no value in getting stuck. It doesn't it doesn't increase individual value, it doesn't increase team value, and it doesn't increase organizational value. So then it's like, well, I could spend a lot of energy being in this place. Or ⁓ I could spend this energy, you know helping drive the change. And I think that goes back to our first meet, right? It was like, how do you manage a career in a time of AI? And you know, how do I do this? And so then we going back and look, you know, organizations are just a bunch of individuals right at the end of the day. So so you know, when we think about our our ⁓ you know, our resilience model. Well perspective, right? Like mindset is the first thing. And so the collective leadership and organizational mindset drives this or or or keeps it from moving forward. And then I think when we talk about s you know, well, how important is strategy and what problem is this going to solve or how's this going help us drive our mission and our vision, well then you go right to purpose. Like like those two things, right? Like having The bright the perspective and mindset and then in order to start looking at well what does this actually mean for us and where are we going and how does AI fit into this? Mm-hmm. Right? Yeah. And then of course, yeah. So so I think it you know, it it it all lines up, right, and and and makes sense, right? But we still are human and and that's what is the the saying, ⁓ change happens at the speed of trust. So if you lose to people you can't get the people behind you, y it you won't get where you're going. That's right. So I hear you've got to start with mindset and and creating psychological safety and and getting people in the right head space for this change, right? Getting their perspective solid. I think that a lot of organizations that struggle with AI adoption are not addressing that. Right. So I think that is absolutely number one. And then what I see is there's are a lot of structural I think artifacts of a different time, you know, a lot of old school business models around kind of h hierarchical leadership and siloed information sharing and ⁓ you know, some practices that are really again get compounded with AI. You might be getting away with it right now, even if it's pretty hard in a high change environment to operate that way. But AI is just gonna shine like a glaring flashlight on all of those issues. And so one of the things that I'm seeing organizations struggle with is that openness and information sharing and a place where the people closest to the work can drive the solutions. I think that's ⁓ sounds maybe easy to say, obvious even to someone, but ⁓ how few organizations do that, right? So many decisions are still top down. And so you know, giving people, like you said, that clear true north, that clear purpose, where are we going as an organization, but then a more ground up approach to okay, how are we gonna get there? I think is the way you've got to move forward. And you've you're a part of this. Going back to the very first thing that you s were talking about in like database migrations or or big s system implementations like ERP implementations and CRMs. mo early momentum and early buy-in and maintaining momentum and maintaining buy-in across the board is is critical. And that's old I mean, that's that's not Well was about to s yeah, I was about to say, you know, sort of and ask you, 'cause a lot of your, you know, what you bring to this and what you bring to these conversations, ⁓ because you think you very much embrace these of AI and you're out there talking to a lot of our clients and People are really excited about this topic. And, you know, you get to go in in an hour trying to like impart some of this stuff. But but I think ⁓ some of the practicality too of what you bring to this conversation, I'd like to know more about it is is the some of the big implementations you've done over time. They weren't AI, but they are others. And I think the lessons come from that. Like a like we said, it's just a sexy, faster, you know, version of those kinds of changes. So You know, one of the things that I I I remember I led a a big database. We called it a revitalization, because we were gonna transfer to a new system, came in and looked at it, and I was part of the team that did this, and it was like we're not even using this system to its full potential. We hadn't ever upgraded it from the original implementation almost 20 years later. So there there were a ton of new features. And so rather than move to a new system, we needed just use the system we had well. And so one of the first things that we did. was say, okay, we sat down with the fundraisers and said, what are the things you love about your job? What are the things that really bring you joy? And what could and where do you have friction in that? What keeps you from getting to do that more? So many of them said, I love to be up and out with the donors. I love to be understanding what people's passion is for philanthropy, but I am out far less than I should be because I cannot get data out of the system. I don't have visibility into who I should be focusing on. ⁓ I struggle to know how to prioritize my time most effectively on my donors, right? Am I t are these the right people I should be talking to? And so what we very quickly realized is, and then the other point of friction was coordination with others, right? Anxious to reach out because they were afraid is somebody else talking to them. There was no visibility in the system around coordination. And so what we realized we immediately need to do is one, rip the system wide open and say, Everybody's got ventilation and there's activity. And that was a tremendous culture shock, right? Because it's going to reveal who's who's got activity and who doesn't. Everybody's got an excuse. Well, I just don't put it in the system. Well, now you're gonna be incentivized to put it in the system so that way we can have greater coordination. You say this is something that matters to you, you say this is preventing you from being successful, this is what it's gonna take. The flip side of that is we're gonna make sure that you're incentivized for it. You're we're gonna make sure that it's part of your metrics that if you're keeping data in the system and you're being a good steward of the system, you're going to be rewarded for that. And then the other thing we did was we've got to proactively push information to help fundraisers make better decisions. So so often these technology implementations are not oriented towards making the people doing the work more successful. You know, it's so top-down driven and it's like, I want this specific report for myself, you know, or it's this one leader has ⁓ undue weight in the situation. So a system will be oriented towards one team but not provide broad service across the board. And so taking the time to really understand what's gonna set each team up for success and if I could get the friction out what's causing friction. If I got the friction out of the way, what would I do more of? What would that allow us to again create v value, you know, in terms of more money raised or whatever, new products developed, whatever. ⁓ all that So, right? It's gotta be almost grassroots effort. If you it can't these things cannot be top down and be effective. Well, I think that's a great example and I kinda love that because then you're actually giving them what they say that they want. And I think we have a ⁓ you know, just that idea that if I'm not frustratingly trying to use this system or not be able to get what I want, it's holding me back from doing the things I really enjoy do doing. being out with potential donors and doing that actually is what you're trying to happen anyway, because that's where the money comes from. And I think about even for us, right, is I think we're happiest in in our work when we're out there facilitating or meeting with the client. And and so the things that the little things like my debrief notes afterwards, being able to spend 15 minutes on that and delivering something usable to the client so they can use the next morning for a follow-up way better than me spending an hour trying to type notes and organize them in a way that they can use them. And so those, you know, I do think people can get more on board with change if the the message is not or or the unsaid message is not, ⁓ we're we're doing this so we can be more efficient. And being more efficient means that we w you know, we'll have less people. What we really want is right, and there's this whole thing is like efficient is not always effective. Yeah. Right. So so but how really can we be more effective? And guess what? If you use if you work if we work on this together, you get to do more of the things that you like. And you might get to do some things that you would be great at or that you would like because you're gonna have more time. And then that's gonna create value. That's right. I I think that is like when I think about the scarcity mindset versus like the abundance mindset. The scarcity mindset is often, okay, we gotta be more efficient. We gotta squeeze more out of our people. And so people look at that and say, why would I work harder for an organization that as soon as I free up my time, they're just gonna put more on my plate. Right. So you've got to find a way to Leverage the t this technology to make people's quality of life better, make working at your company better, make people do more of the things that they love, use their brain and it to their highest best use, as opposed to now you've got to process twice as many expense reports. You know what I mean? It's like get the minutia the plate and think about it from that perspective. What's the highest best use of my people's knowledge and talent? It drives our mission and vision, right? Because if you really say like, what are we here to do? Right. And we said, you know, well, what are we here to do with with at Success Labs using us an example, right? Well, we wanna help create better leaders, better teams and better organizations. Well well, is is me spending a lot of time typing up and organizing notes, driving better leaders, better teams and better organizations? No. Right, like that particular task. So then it's like, okay, well, you get to spend more time actually doing that. And and that's I think The reframe, right? Like we're talking through like the reframe and you've gotta you've got to frame it up for people in a way that they can get to that owner mindset and not get stuck about loss. This is you two things you said, just p ping something in my brain that I really liked. You know, one, you brought it back to purpose. What are we really here to do? And I think as long as you can continue To drive this change back to what's our true north? What's our vision? What's our purpose? Why are we here? And we lose that absolutely. The other thing that I heard you talk about is incentive. Why should people do this? Why should they care? One of my favorite examples of a company getting this really right is NVIDIA. And they ⁓ did something really, really interesting. So, you know, in leveraging AI. it a lot of companies see the opportunity to get rid of their developers, right? You don't need as many developers if you've got one guy who can produce a way more code using AI. Instead of thinking about it that way, they said, okay, we're gonna take our best engineers and we're gonna give them access to AI to really increase their output. We want 10X output from all of our best engineers. But ⁓ you know and they gave them huge ⁓ token budgets to do this. So Token budget is like how much compute do you have? So if you've ever hit that wall that says like you're out of usage, they basically said you guys have ⁓ you know, an in a giant piggy bank of tokens, use as much as you can, but you have to come and share back with your team what's working and what's not. It was it created this culture of show us what you're doing, show us what you're building, show others how you've used AI to become better. How did you create this 10x output? replicate that across the team. And the people who continue to do that well continue to be incentivized. And so it comes back again to make it fun, create incentives to share, create incentives to empower and develop others. And in doing that, you know, and give people their time back, right? If this engineer is creating 10X output, don't insist that they be at their desk nine to five, right? If they're getting the work done, let them spend their time the way they want to spend their time, especially if they're going back and pouring into your organization by training, developing, sharing. Yeah. Or creating new things, right? Like the that you or new I new ideas or next the next thing because we're not over here doing these very rote often ⁓ kinds of things. Yeah. And I think, you know, rote, you know, that rote things are easy to turn over, right? Like how do you Save yourself for the things that only you can do. And that's relationships and it's thinking and still I think it I still believe it's thinking, it's create creativity and it's people and it's ⁓ you know, ideas. Yeah. And so I agree. I agree with that. ⁓ okay, so we talked about, you know, we've got to do that leadership planning and readiness. Like we gotta get minds right, we gotta be ⁓ you know, aligned as a leadership team. on why we're doing this, what are the the problem we trying to solve or the ⁓ business you know ⁓ know where we're heading as a business, like get clarity on that. And we talked about, you know, what are the structural changes that need to happen? And there likely needs to be greater organizational openness and breaking down of silos and, you know, incentives in the right places. ⁓ Right. Inclusiveness of of you know people participating in the yeah in the process of getting there. Yeah. And then you know, the the third one I'll name is practitioner-led adoption. So I talked about this a little bit with it needing to be a grassroots effort, you know, the people closest to the work deciding how that work gets done. I I there was a really cool example. People keep coming to me asking me about AI tools for recruitment. Because hiring is so challenging right now. People have perfectly tailored resumes to these job descriptions. And submitting an application now, there's no barrier to entry. There's no, it doesn't take any time. So thousands of applications for a single job. So recruiters are overwhelmed, right? Everybody's asking this question. I found a really cool example of a company that did this where they brought in an AI recruiter that did screening instead of just Taking all screening off the plate of the recruiters, they had the recruiters work alongside this tool for a month and they said, help us figure out the best way to use this technology. And what the recruiters came back and said is we want to target this at some specific high risk candidates or highly technical types of candidates. So jobs that are really hard to fill. And so we need to be really on top of the specific type of candidate. People that we think are high risk in the pipeline. So somebody who's likely got a lot of career mobility, somebody who's really attractive, somebody they think might be applying for multiple positions and so likely to fall out of the pipeline. They had like a series of criteria, right? And they said, if we can target these people and have this preliminary conversation with the scre with this screening tool, get those in our queue for Monday. Let it do that over the weekend. It was able to churn through getting some basic information. from these candidates. So Monday, the recruiters came in with a warm list of leads that were pre-screened by AI, their most valuable targets. And then they were able, you know, oftentimes by the end of the week, to have people placed into positions to increase their speed to place, it increased their success rate. They were finding better quality candidates because they were able to deliver those early screening questions. And ⁓ it allowed them to ⁓ have a lot more high quality conversations with the candidates. So some of that ⁓ logistical screening is what they put in AI. That way they can have more talk to us about the type of culture you're looking into. Talk to us about what motivates you in the work. They could really understand the culture fit, the skill fit for those individuals moving into the organization. So to me that's such a great example of the people closest to the work should decide how these tools get implemented. Yeah. And help make ⁓ work for you. Yeah. Like they were able to make that work because they understood and could isolate the things that really made a difference. Right. It still takes that human, right, like understanding to really target the AI to get what you want from it and and have it make work for you. So that then you can do the human piece that really is necessary to get the right candidates in this case. Yeah, that's right. Do you have any other Good examples like that. Anything else come to mind? No, I I I think just reiterating that that shift from just efficiency, thinking of AI from an efficiency and what can we cut standpoint to thinking of AI as a really ⁓ useful tool that helps us deliver on our mission and our vision ⁓ well, right? And better. A tool for value creation. Tool for value creation. I love that. For recognizing our vision faster, better. Yeah. Yeah. And and being a and and freeing up our people to do what only they can do and what they do best. It moving things out of their way that keep them from doing those things. I mean, to me that's the the best best use. And that's I think the reframe and also the how do you move forward. that is beyond just like, ⁓ AI. Let's we we have a we have a training day coming up, you know? Go get somebody to talk to us about AI for an hour. That'll do it. Right. That's that's not really and I think honestly, I think the biggest action around AI is that. It's I mean that's I've been I I think I have three or four trainings this week and five or six last week. And I'm and it's not a bad thing, right? I think it's good It's a good intro, but it's not the deep work. It's not the deep work. It's not gonna make you, it's not gonna transform your organization. Yeah. What it hopefully does is open the up the, yeah, the the conversation for, ⁓ where do we go from here? That's right. So I think that's a good segue, Devin. What are, you know, the three things in the next 30 days, let's say organizations are are ready to do this. What are three things you think they should do? well, I think. One thing you can do is you can download our AI wet readiness self-assessment. That would be one thing. And I think ⁓ the other couple of things might be like really understanding. I think this is a question you ask when you do your your talks, which is like who's using AI and do you even know who's using AI? Like, where is it sitting in your organization right now? ⁓ It's so interesting. I'll I'll I'll ask people to raise their hand and I'll say, How many of your people, how many of you have organizations with people that are using AI? ⁓ and ⁓ you know, or how how many of you all have an organization AI strategy and almost nobody raises their hand and they'll say, Well, how many of you all are experimenting with AI yourselves? Everybody raises their hand. And and I think the dots haven't connected that your people are experimenting with it. They're using it. It's just not in a concerted, coordinated way. Anyway, keep going. Yeah, no, I was just gonna say I think that's it. It's like really understanding where everybody's at and can tell you a lot about like where you're even at along this like r readiness ⁓ thing. It's like if if everybody's scared. Or if and in some cases there's been a real like, let's squash this, like putting in a in some kind of ⁓ policy that squashes the whole, you know, intention early on. So then people get worried and people all the time look at me and say, Well, we can't really use it at work. And they're like, Yeah, I'm I'm kinda like doing stuff at home around it. ⁓ and I think just that that whole pulling back, right? That that slowing down to speed up, like I think people we're we're not Starting in the right place, right? Like, yeah, it's great to have somebody come and talk, but that should just be a cue, like, okay, let's step back. When we're doing I str I would tell everybody if you're doing thinking about your strategic planning, which you're probably starting to think about if you're on a traditional year, right? And couple we're about to end of ⁓ Q two, ⁓ And Q t three, you're starting to think about what does next year look like. But I think having really ⁓ thoughtful ⁓ strategy ⁓ discussions around AI. And again, going back to something we've said a couple of times is like, what do we is there a problem we're trying to solve? And also how does this play into where we're trying to go to to ⁓ achieve our mission and our goals. So I would say self-assessment, I would say understand where your your your people sit on AI or where your organization sits on AI and be str and and and and now is the time to start thinking strategically about AI. I think those are exactly right. What would you or what would you change? One thing I might add is like just tactically, practically, the one gap a lot of organizations have is well-defined data and documented processes. And and you cannot leverage the power of AI without having your data all in one place, knowing where your data is, and then having your processes documented. So I'm sit working with a team right now that's wanting to do an implementation. being asked to hand over all their process. Well, okay, hand us your processes. They don't have anything. So now they want me to come in and help them write processes. And I'm like, this is, you know, there's groundwork that needs to be done. So people and processes, right? Like ⁓ I think that's gonna that's that's a readiness, a huge readiness It's on our readiness assessment is, you know, do do you know where your data is? You know, do you have your processes documented? This is some of that early just check boxes that you've got to check to get ready. Yeah, if if I mean, you know, I think w if I if I think through this conversation today, I would say like, you you are not ready if your dating processes are are aren't organized, you're you have no idea where your people sit right on that. And if you aren't thinking about strategically why you're even having the AI conversation. So you know, people process strategy, like those are the things, the takeaways organizationally, I think. And and I agree, like I think the self-assessment can really surface some ⁓ organizational assessment can really surface some things and help you understand where you're at and maybe what some of the first steps might be to go down that road. Yeah. I love it. Okay. So that was part three of our leading through AI series. We started with you and managing your career. We went to managing your teams and now, you know, leading really through ⁓ as an organization. So I think the through line for us has been the AI is accelerating everything. ⁓ and you know, the change is rapid, but the basic principles are s the same. The principles of transformation and change are the same. You gotta focus on your people, your processes, your strategy, like Devin just said. you've got to invest in your people, you know, and you've got to spend time with them. And ⁓ that's gonna be the best way that you can move forward. AI is just the sexy fast version of the old stuff. That's exactly right. ⁓ so thank you all for joining us. Please sign up for our newsletter, follow us on social, and join us next time.