NB 62 - Navigating AI in Business: Integration, Leadership Challenges, and Future Perspectives

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Speaker C: Artificial intelligence is reinventing business as we speak. You can either get up to speed or get left behind. The choice is yours. And really, really, it's a no brainer. Join Cognitive Path founders Jeff Livingston and Greg Verdino as they chat with AI experts about the latest ideas, trends and technologies that are creating the future of business today. This is no Brainer.

Speaker D: Hey everybody. Welcome to the no Brainer podcast. I'm here with Greg Verdino. We are actually recording this on the eve of July 4th. How are you, Greg?

Speaker E: I'm doing well, Jeff. How's it going over there?

Speaker D: Uh, you know, same old, same old. Fireworks are coming, I guess, one way or another. I'm not going. I'm too old and cranky and I don't like all the security, so.

Speaker E: Yeah, that's rough. That's rough.

Speaker D: Yeah. What about you? What are you doing?

Speaker E: Not a whole lot. Um, because I can't get enough fireworks, I guess. Pun intended. Uh, we're having my mother over tomorrow just for little casual thing so that she didn't feel like she was sitting home alone. But, uh, other than that, I just laying low.

Speaker D: All right, well, make sure not to let any at home. And, uh, you know, because there's always that bad story every year of some NFL player that blew off two of his fingers. It is literally dynamite. Right? All right, well, before we introduce our fantastic guest who's got to be rolling his eyes by now, uh, let's roll the usual introduction if we could, Greg.

Speaker E: Yeah, absolutely. So, of course, as everyone who listens frequently knows, but for the rest of you, wherever you are listening or watching, be sure to subscribe, rate us, review us if your platform allows for it for example, YouTube. Please be, uh, you know, please feel that you can go ahead and drop us some comments if you would like to get into our inboxes. If you go to no brainerpodcast.com, uh, you'll be able to email us there. Please suggest show topic, show guest. Uh, we do occasionally, as Jeff likes to say, have a mailbag episode. So if you do have questions you'd like us to address, topics you'd like to hear about, people you'd like to hear from, let us know. And with that, let's get to the person you're gonna hear from today. Jeffrey, who do we have?

Speaker D: We have Michael Whitaker, but everybody calls him Whitney. And Whit is a senior vice president at ICF Consulting. He handles strategy. He's a bit of what I would call a fixer in the old traditional sense. You know, for all of us guys from the east Coast. Yeah, he's a fixer. He's got the Mr. Wolf mobile. Um, I want the Mr. Wolf mobile. By the way. That's a good Pulp Fiction reference. But Whit is also the author of an interesting substack on AI. I know he's helping ICF adapt with AI, but he writes one for parents who are looking to understand, uh, how to incorporate this into their media diet. And with that, Whit, welcome to the no brainer.

Speaker F: Thanks Jeff. Thanks, Greg. Really happy to be here. And on the substack, really it's uh, it's kind of for working parents and who want to shape how AI is going to impact our work, our kids and ourselves. That, that triad that I think so many are struggling with, then it's really just meant to be a honest conversation of what's going on and some, um, uh, to help people that are busy and don't really know maybe how to engage or feeling like the world is racing past quite fast and they, uh, don't want to get left behind in it and they want a gentle way to engage and be part of the conversation. And so that's the intent with it. Free substack. And would love to have anybody listening here that's interested in the topic join that conversation.

Speaker D: And we'll be sure to post a link, uh, in the show notes afterwards for sure. But, but to ask you quickly, you know, what compelled you to start this? I mean, obviously, um, in your work at icf, uh, you're doing some of this. But you know, what made you really feel like this was needed right now?

Speaker F: So I think there's you. When you think about purpose and where you can drive impact. There's this concept of what are you curious about, what are you passionate about? And where does that intersect with something that has a big impact on society at large? And how can you bring those two things together so that you can really drive your own curiosity and engage deeply, but also while helping other people. And what kept coming back to me was this worry that we were going to lose generations to the AI transition the way we lost them to the social media transition, that as this technology entered more and more parts of our lives faster and faster, that we were going to have unintended consequences, that we were going to have significant portions of our population that didn't come along with the ride, that, that got, that missed, missed early stages, felt too far behind, didn't know how to engage. And then all of a sudden the impacts were going to be large and almost uncontrollable. And what I wanted to do and the reason I started the substack is I want more, more particularly working parents to engage because I think now is the time to really shape the conversation about how this is going to impact our work, our careers, but also our kids. And I've got a 14 year old going into freshman year of high school, I've got an 11 year old going into sixth grade and middle school. So I'm acutely attuned to what is this going to do to education, what is this going to do to their future careers, but then also ourselves. You know, this like, what do I feel like is most important to hold onto as a human as AI becomes kind of outsourced intelligence and cheaply available? And as I started to explore that space, I kind of kept coming back to creativity, mastery and grit. How do we keep that human ability to create novel things, to do lateral thinking, to drive that spark of, of early in a process, that ideation, but also as intelligence becomes more and more available, what's our, what's our human, um, motivation to go deep and to master a topic if you can ask a question on it at any moment. And but I think mastery is really innately human and so we don't want to lose that motivation to master topics and to be able to then put the judgment and discernment on what's coming from the AI because we really deeply understand a topic and then grit. Like I want my kids to still iteratively problem solve. I want them to struggle. You know, if you, if you think about flow science and like how humans reach their states of optimal performance for periods of time, the struggle phase is critical. To that like you have to struggle with a topic before you can then flow into it and feel that release and that, that extra performance boost of really getting over the hump and tackling it. And if we, if we abort the struggle phase, I think there's going to be huge ramifications. And so it was that kind of mixing of topics that really got me interested. And I'm a working parrot and I feel like there's a lot of other working parents that are probably facing this. Myself, my work and my kid triad that are all somewhat overwhelming on their own and just wanted to have a venue to have a conversation with them and to start to explore these topics together with some others in the space.

Speaker D: Yeah, it makes a lot of sense. One of the things that strikes me about this approach and just generally from our conversations you have this kind of a groundswell view of how things change, which we love because both Greg and I came out of a social media era. Uh, well, I can't speak for him, but I love it. And that's our old friend Charlene Lee who wrote that book. One of the things about the groundswell is it assumes that leadership is not adapting. Leadership is not changing fast enough and it creates a crisis which causes the groundswell, which is people rising up to demand change or to demand, uh, evolutions, if you would. And it seems like in our conversations, in your writing, we've really talked about how leadership is not adapting well to AI and that there really is a need for middle, uh, management to lead that conversation and to perhaps for parents to lead schools into that conversation. Am I off on that? What are your thoughts?

Speaker F: No, I think you said that really well and it's an uncomfortable topic, but let's be honest about it, right? Like the, the people that are leading most of our largest institutions, the ones that are in the everyday lives of our kids, that are often our employers, that are the politicians that are driving a lot of the big societal choices, the people leading those are the generations that are least engaged with AI. Statistically they're using AI the least on a day to day basis with their jobs. They are trying to keep their organizations still operating under the current paradigm in which AI is starting to have a role but has not yet fundamentally changed things. So they have a responsibility to keep the train on the tracks and to deal with the day to day fire drills. Their personal jobs are least affected by it because they're right now because they're senior decision makers, they're doing large scale planning, they're doing more of the strategy work which AI has a role in and can be a partner with. But it isn't something that's going to be automated in the near future that they're really feeling that pressure. And so they can largely still do their jobs the way they have done their jobs for the last 10 or 20 years. And they're in their positions for a reason. They're smart, they're, they've got discernment, they're prudent. But they're not engaging with the technology on a day to day basis to the degree that their workforces are, to the degree that the students are, the degree that that next generation is. And this is a space that is evolving so fast that if you are not engaging with it on a nearly day to day basis both in terms of reading and personal use, your mental model is going to be three to six months old constantly. Like it is almost impossible to keep that updated. And then so you're making decisions based on whether it's cost, information, capability, information. The last buzz article that you read somewhere that's only a half truth and not really what's going on.

Speaker D: Like are you saying that AI Buzz articles are a little bit.

Speaker F: And what I'm saying is it's the old way that executives would typically keep track of these kind of trends doesn't work for AI.

Speaker D: Mhm.

Speaker F: And that's not like just executives and companies. It could be leaders in schools and whatnot. And it like you could, you could deal with blockchain or you could deal with big data and say hey, this is going to impact my area but I don't need to understand it myself in order to lead an organization that takes advantage of this. Ah. And I don't think that holds for AI and I think it's causing a real problem in the pace of adaptation for organizations which then puts the emphasis on that next layer to say hey, this actually I have more urgency and I'm engaging more in this and I feel like I need to take some responsibility for this change and agency and shaping it and not wait for my leaders to tell me what to do and how to adapt to this because they'll be, they won't do it fast enough.

Speaker D: Verdino, what do you think?

Speaker E: Yeah, I mean I think that's absolutely right. I think, you know, kind of what, what I'm thinking about though is, you know, I. Is the answer to push AI down into the organization or is it to somehow embed a new mental model at the leadership level? Because the problem you're describing, I think is maybe 10x or 100x now, but it's the same problem that, I mean, I've been dealing with. I'm sure you have two wit and Jeff, of course, over the past decade or more around digital transformation, where a CEO hires a cdo, outsources all of the strategy it relates to digital, as if the CEO just became the chief analog officer. Um, you know, the organization doesn't adapt quick enough to the changes that have already happened. Uh, they're 10, 20 years behind their customers. Um, and then, you know, Covid happens, the supply chain breaks. Now all of a sudden it's rush, rush, rush, rush, rush. Right. Um, what new mental models and then even methodologies do senior leaders need to adopt in order to kind of get with the game? Because sure, they might be in their 60s, but they're not gone yet.

Speaker D: Right.

Speaker E: And they do have that perspective and that broader experience. How do we not lose that? At the same time, we kind of gain what we need to move organizations

Speaker D: forward as a t. To tap on to that too. Maybe I could like, even bridge us a little because you. We had, as usual, folks, we've been going back and forth a little bit before we got on here. Um, and wait, you had mentioned something about the training programs not being adequate. And it seems like tacking on to what Greg was saying, you know, and part of the problem is that corporate training fails. Right. And the way it's set up, you know, we've all been through those horrible PowerPoint slides. At the end of the year, here's your cybersecurity training. And you know, that's not going to cut it with AI. I mean, you really need to make this a, uh, habitual execution every day.

Speaker E: And, and on top of that, no CEO that I know is sitting in on the lunch and learns. Right. They think the other people in the organization.

Speaker F: So, so many good questions in your two statements.

Speaker D: Can I add five more?

Speaker E: Last 57, please.

Speaker D: Is this the best coffee I've ever had, But God, I can't get a word in with these guys.

Speaker E: And that concludes today's episode.

Speaker F: Thank you.

Speaker E: Goodbye.

Speaker D: Nice talking to you, Whit.

Speaker F: So, yeah, let's step through those a little bit. Um, so we'll start. And I think it's both. And in terms of middle and top, right? Like, you can't ignore the leadership model. Um, I'll start briefly with the middle and then go to the top. So I think where I've seen the most sustainable change come in organizations around big things like this starts in the middle and moves out from there. It starts with the people that are every day doing the work with clients that are facing the challenges in more throughput productivity expectations. And they start working in a different way. And as they start working in a different way, their peers see them getting benefits and they want those same benefits. And then they are then m motivated to adopt the new ways of working. And so those early adopters spread to others in the org at the middle level, not because leadership tells them they have to, but because there's a very tangible realization of value. And one of the articles I wrote recently was around this tipping point at work that I think is not yet reached, but is coming. And it uh, may be it's reached a little bit in the developer space and a little bit in school, but it's right now it is harder in most organizations to use AI to get your work done than it, than there is like pressure to use AI to keep up. And so what do I mean by that? Like if you think about uphill downhill, it feels right now using AI in most orgs like you're pushing a rock uphill. The company has approved tools that are probably not as good as the commercial tools. You've got all kinds of requirements you've got to jump through to make sure that you're protecting data and doing things in line with clients. And you know, understandable, right? These are public companies or even the private ones, you're, you're trying to control risk. But at some point it is going to tip to I have to use AI to keep up with my colleagues. I can't move as fast as my peers if I'm not using AI. And that momentum, once it flips, that momentum really builds. And that's where the change is driven and sustains within an organization. But it is five in most organizations that has not happened yet. It has happened a little bit in developer space as you get these really good copilot coding tools that can help developers go faster. And the interview I did with my daughter on the blog where she talked about in school feeling like they have to use AI, uh, to keep up with their peers and the perfect production of the peers. It's starting to happen with students but by and large knowledge workers are not feeling that yet. So leader, you know, so then we get to the leaders in the mindset and where Greg went. So one I think leaders need to set the tone that this AI uses an expectation, not a bolt on or something that's nice to have and that starts with them. Their teams need to see them Using AI. It could be as simple as I used AI to do this assignment and here's or like this piece of work or this thought piece and sharing that with their team. It can be. I think every knowledge worker that uses a computer should have an AI related goal that is set in the near term, two weeks, four weeks. It could be learning based, it could be setting aside time to start to build their skills. Not a year long goal but something that's tangibly in their goals related to the building of AI skills. And that starts with the CEO and the C suite and down through their direct reports. And if they don't have that, if you don't start to bring AI into the day to day conversation like give your direct report an assignment and say use AI for this. Right. And then let's come back and look at how you, how this went and so that it, it doesn't feel like you're unsure if your manager is okay with you using AI, but we can have an honest conversation about oh you did that 10 times faster. Was it good? What did you have to do afterwards? Is this something repeatable? Is what was that experience like? Where did you run into barriers in our institution with having the right tools? That's where I think leaders can really play it. Partly this personal. I um, need to have my own skills and I need to engage myself. But it's also this message down to the org that it's okay to openly talk about AI use. It is not cheating and we're going to figure this out together. But it's fundamentally a core way of how we're going to do our work and that's very different than even a product offering around AI. Those are separate. Like that may come up too. This is like about the core way that work gets done on a day to day basis and the this how leaders are setting up their organization for a different kind of conversation around it.

Speaker D: Sure. It's like a basketball team, right. The star shows up first, the star leaves last. Right. When somebody's doing that, the rest of the team follows suit.

Speaker E: Yeah. And we um, we've done a couple of upskilling programs with smaller professional services organizations um, where that kind of approach, that permission to experiment was really core. Um, in one case in particular, um, it's sort of a small health care consultancy. They um, had access to no tools. There was sort of almost a pushback of we are not going to compromise our work by using AI. And we almost had a 180 pivot them towards no, no, no, you're going to experiment with it and you're going to be honest about where it helps, where it doesn't help, where it benefits both the worker and the work, and where it just flat out doesn't work for you. And you're going to make some smart decisions about how to integrate it into the way you do business. And that's going to start at the founder level, in that case all the way on down to the receptionist.

Speaker F: Um, and I want to go back briefly to Jeff's point about the corporate learning programs because they suck. They're still okay for things like compliance, right? Like we need to show that everybody went through a basic training around data safety, privacy, like, you know, timesheet, M, you know, timesheet processes, all those kind of things. With AI being an exponential technology, by the time a corporate program is developed to build a skill in the AI system, it is going to be obsolete. Right? Like it just cannot move at the pace that the technology is moving. And so ultimately the learning around AI within, uh, an organization, the expectation needs to be set that it's on the employee. Now the company can create time, they can create access to programs, they can give you funding to go use tools from the outside and they can help, they could set goals so that it becomes part of your expectation that you're learning. But ultimately it needs to be this self driven, experiential process of using the tool to do your work and understanding where it does and doesn't work well and then sharing with peers and accelerating that learning by. You know, I had a great experience with a, uh, colleague the other week who saw a prompt that I had used to prepare for a meeting with a CEO, said like, hey, I like that. I've got an account plan that I need to come up with. I think I can do it differently than I have in the past. Can we get on the phone for 45 minutes and can I just like open up my tool and I'm going to go through this and you kind of coach me on how would you have done it, what, what prompt would you use? I'm going to do it, but I want to hear like how you think about it and how you would use these modern tools. And it was a wonderful 45 minutes. And then he comes out of that with a different approach and now he can go iterate on it. And I think that kind of peer to peer, real time in the moment tied to actual work product learning is the way that organizations are going to advance with AI not waiting for the corporate learning program to tell Them what they need to know.

Speaker D: Yeah, it's got to be a daily practice. It's funny because I'm launching a training, uh, program and the whole goal of it is to literally treat it like you're training for a marathon type of, or a running event where literally every day you're doing something to, to learn something and then bring it into the workplace. And it was funny. Somebody emailed me as this appropriate for CEOs? And I said, no, it's not. This, this class is largely designed for somebody that's either running a department, maybe a, uh, senior manager, that kind of thing. Said, however, it would be pretty easy to tailor it for executives. And the reason why I thought it would be interesting for executives to do it is they have a different set of tasks. Right? But those tasks can be wrote as well. So, for example, somebody that's a director that's making a report to justify the acquisition of, let's say, an IT system.

Speaker F: Right?

Speaker D: Okay. That's a significant proposal. Usually, there's usually several meetings that are involved with it. There are objections. You have to do vendor calls. You have to also see how it, uh, would work within the organization, Budgeting, change management, the whole nine yards. Right? So, so you're doing a lot of work and you're creating a lot of internal content for that. On the other side, if you're an executive, you're receiving that. So why would you use AI to vet that content? You know what I mean? Because I know with executives, one of the biggest barriers is time. I don't have time to read this. I don't have time to answer all these emails. I don't have time to resolve this. And AI is actually something that addresses rote tasks, like reading email, like reviewing, uh, proposals, like reviewing reports, and allows you to summarize them, get down to them quickly. One of my favorite tasks with AI and LLMs is to critique documents. Here's this proposal. Is it strong or weak? Why? And what's the veracity of your response? Is it good or bad? Are you confident in it? Like, have you ever asked an AI if it's confident in something? It's really funny, the responses you get back. You know, it's like, well, it's about 70%, right?

Speaker E: Yeah.

Speaker F: I love the document review. I actually have AI on some topics that I'm looking into around human AI collaboration. Deliver me, uh, an academic paper every morning along with some comments on it, so that it's doing the search for me and putting forward a new piece of information that I could Dig into. Sometimes I'll read the paper myself because it's interesting or short and sometimes they're 30 page papers. So I feed it back into AI and I say what does this add to the state of knowledge in the human AI space? Help me understand the key points, help me understand the places I might want to dig deeper. And it's not to give me the full answer going forward, but it's to help me fine tune where I want to dig in deeper within a larger piece of knowledge or whether I want to spend my time on that or move on to something else. And it becomes a really fast workflow to triage and to figure out where my most precious asset attention is given at any, at any particular time. And you know, I've been trying with hm, my executive team. One of the things I've done is come up, I have a newsletter that uses a three, two, one format right where it's. What are three reads that are of interest in this general field? What are two actions you could take to build your skills this week? And what's one thought that you should ponder or that we should collectively ponder as a leadership team around AI and figure out what we want to do with and try to keep the read to uh, it's going to show up largely on one screen in an email. It's five minutes. But even that with executives can be tough at times because they're triaging an inbox. And so I took the, you know, the original articles are linked. So I took the original articles and fed those into AI along with my newsletter and I asked AI to turn it into a five minute transcript of somebody reading it. And I didn't use the, I did not use Notebook LLMs podcast just because I think it can be a little bit kitschy at times in terms of like the pauses and the back and forth for an executive audience it can feel like it meanders a bit and I wanted something that was more like a professional briefing that would not waste their time.

Speaker D: So you use ChatGPT either then?

Speaker F: Um, no, I, I use, I actually use Gemini for this one and I, I, I went into Gemini and had it come up with the five minute transcript and, and then I had it do use the audio overview and the, the Gemini or uh, Google AI studio to do a five minute voiceover of it. And I, when I sent the newsletter to the executives I attached the audio along with the newsletter and you know, the feedback I got from one of them was like the audio was great because it helped me understand where I wanted to dig in further. Which, which article do I want to go read out of all these? I could listen to it when I'm on the go. And so it's, it's like thinking about those multimodal ways of communicating with those teams as well.

Speaker D: And it looks like we lost Greg. I think AI kicked him out. I don't know.

Speaker F: Greg, we hope you come back.

Speaker D: Yeah, we hope to see you soon, Greg. Um, so let's get back into this kind of like, uh, it's this general executive mode. And obviously your newsletter is pretty cool. And what's the response been to that? You know, obviously it's a little bit challenging, right, Sometimes because these guys are also busy. So like, how can we get in front of these executives and make them really open their eyes

Speaker F: to some degree? I think you just have to start using AI and having IT show up in front of them in their workflows. And so like I'll give you an example, we had our strategy day not that long ago. I'm sure other organizations do similar things. There's a variety of presentations and discussions which there were some people in person, some remote. So it was on teams, it was recorded, there was a transcript, there were slide decks in advance. There were even some AI generated notes from the meeting. I fed all that back into AI. So I put all the presentations, I put all the notes, I put all the transcripts. And what I asked AI was what are we not talking about that we should be? I said, you know our company, you know the industry, you have knowledge, you can go out and do research on what's happening in the federal government or the utility space or these other places that we play? What are the questions that we didn't ask that we should be asking that we're dancing around? What surprised you about our conversations? And ultimately I asked it to be provocative and I said, come up with a bank of questions that we should be asking in follow up conversations that will be uncomfortable but are important to the future of the firm to ask. And then I was able to take those questions and send them to the executives and openly say that I used AI to come up with these things. I'm not hiding it, but there were some very pointed questions that would not would be difficult to come up in a conversation from another human in those executive things because of whether it shows up as territorial or adversarial or just. People are nice and they don't want to ask the pointed question. AI doesn't care as long as you give it the instruction to not be sycophantic and just puff everybody up. But you say, I want you to be adversarial and provocative. It's actually quite good at that. And so those kind of things I think of just, like anytime you can find a way to insert it into the workflow and bring it openly into the conversation and just start to show how it can actually be used differently, I think that's really the way to get it in front of the executives, not in the academic, hey, here's theoretically what you can do, but here's what I did with it and here's why I think it could bring value. Then at some point, their curiosity. These are leaders. Like, they need to do the work. They want to be more. They don't want to waste their time. At some point, that curiosity overtakes cognitive resistance. And they say, oh, okay, like, it probably worth my time to dig in here.

Speaker D: Yeah. Why is it we have that cognitive resistance, do you think? I mean, obviously everybody's talking about it. There's. I was just reading. I saw. I. I made the mistake of going to CNN's website, uh, yesterday, and CNN had this article about, this is crazy, this is so funny. But this, this is AI in a nutshell, right? Um, husband says a chatgpt has brought him a spiritual experience. Wife says chatgpt is ruining their marriage.

Speaker F: Yeah.

Speaker D: What does chatgpt have to do with that? I mean, like, couldn't he have easily done that with TikTok or, I don't know, uh, Call of Duty 5. I mean, I think we've all seen these stories through the years where people get distracted because they don't want to be present.

Speaker F: I think there's a few reasons for the cognitive resistance. One is the buzzwords are really powerful, but the nuance is not often talked about. So you could talk about agentic AI, you could talk about AI, you could talk about ChatGPT, you could talk all.

Speaker D: What is it, genic AI now, right? It's like everything, right?

Speaker F: It's everything. It's everything. It's everything and anything, right? And if you look at, like, some of the work out of Stanford, around the human agency scale, you know, if you're getting into these human AI processes, there's some that are going to be largely automated, there's some that are going to be nearly an equal partnership. There's some that will have almost no value unless the human is in the loop nearly consistently. And there are these different levels of engagement. And this whole field of human AI collaboration is going to be a future management Discipline that, that is very nascent right now, but is going to be super important. The, you know, we've talked about this a little bit, Jeff, like choke point hunting, right? Like AI is going to run into real world constraints on progress, whether that's a senior human decision maker that hasn't engaged that or is too busy to understand the information or human content review or a lengthy regulatory process around a, ah, new discovery. And so, you know, I think what happens is the executives don't have the same exposure to the technology because they're busy. Like they're running the, they're running their organizations. And those organizations still have non AI demands to meet talent, budgets, planning, everything, right? So they can't put their full time into it. A lot of these people are in their positions because they are experts and they are most comfortable when they feel like experts. So they could be, you know, experts in business, experts in the domain, expert in finance. And they've really grown that expertise over time and they don't feel like experts in AI. And because they don't feel like experts in AI, the nuance of the conversation gets quashed. It's easier to and uh, safer to parrot the hype or to stay quiet than it is to like push back and really say like, hey, here's what I don't believe yet, or you know, hey, I hear all that buzz and I don't think it's coming for a year or two, so we're just not going to act on that. It's much easier to kind of go along with it and not engage and to feel safer. And particularly in the public square, it becomes very scary for leadership to engage, particularly, um, in somewhat controversial ways around AI or against the hype. They'll get punished by investors. There's going to be a general backlash of you're naive or you're too slow. And they may have very good reasons to say, in my space in this industry, the change will be slower than the hype is suggesting. Not that I'm denying it's going to come, but I don't think it's going to come as fast. And I have a responsibility to keep things on track until it comes. And so we're going to balance and be more measured in our approach. But that nuanced discussion is really hard to have if you don't feel like you're confident in the technology, have a current mental model and are engaging with it. And that lack of confidence then leads to a pullback in the conversation, which I think manifests in a Cognitive resistance to the change and kind of hinders some of the organization's approaches to this devil's advocate.

Speaker D: Do you, and this is for both of you guys, don't you think that there's a reasonable, I mean, we all believe that AI, uh, is coming and it's just obvious that it's being incorporated. But do you think that cognitive resistance, at least from an executive level, is there a, uh, healthy skepticism about AI given the failures to date?

Speaker F: I think there is a healthy skepticism. What I think is missing right now is an articulation of the details of the skepticism. So I think a lot of the executives feel in their gut like it's hyped, it's too fat. Hey, this is blockchain 2.0. This is big data or other things where maybe there's a behind the scenes change, but it's slower, it's not as impactful. Some of these other technologies, but they can't quite articulate what it is that is that hesitation and surface that in a non buzzy, non hype, nuanced way that allows an executive team to uh, really align on like, where do we have a similar viewpoint and we feel like we're confident enough to take action and where do we still have hesitations and feel like we need to hedge understandably and responsibly to be a prudent steward of the resources of this organization and to make sure that it keeps functioning and keeps meeting the needs of our clients even during this AI transition? And I think that nuance is, I think the cognitive resistance is healthy and I think it's okay. I think the nuance of the discussion and you don't know where you disagree until you get to the details. And I think too many of these discussions float at the. Everybody's going to nod their head at the headline as opposed to the more detailed argument and that those detailed arguments, executives can have that around finance because they've done finance forever. They can have it around risk because they got to their position by managing risk. They can't have it. Both of them can't have it yet on AI. And I think that's the challenge. But Greg, I'd be interested to hear what you think as well.

Speaker E: I mean, I think that's definitely a lot of it. I think, you know, often it seems we're kind of sort of swinging, like the pendulum swings in a way. Right. And either it's executives getting so swept up in the hype that they're doing too much too quickly. And we've seen that model Fail before, like I think even back to the digital transformation days when GE went all in on Internet of things and then their entire digital transformation strategy crumbled, practically destroyed the company.

Speaker D: Uh, Metaverse.

Speaker E: Right, the metaverse. That's another factor too. And that's where the skepticism comes in. It's like there's this sense of we've been here, we've seen this, we've done this before and all it was was a massive weight. Metaverse, web3blockchain, NFTs, whatever. Right. Um, then you've got the other side of it, which is kind of, you know, Toffler's future shock come to roost. Right. Where there's just so much overwhelm. And that goes back to your idea about how maybe your mental model is three or six months old. I mean it wasn't so long ago where having a mental model that was three or six months old put you ahead of the pack. Uh, now it puts you woefully behind. And when, uh, you know, even if you're playing with tools, whether you're an executive or somebody deeper in the organization, you know, when there is so much coming at you so quickly you can't possibly keep up with the press, let alone the actual hands on experimentation, that a lot of people just freeze. Right. Future shock, right. How do you bring people into that middle where you have a healthy skepticism, where you are willing to think critically and strategically about where this technology really delivers benefit to the company, to its customers, ultimately to the world. How do we mitigate some of the risks that might be greatest? And I don't mean exobots are going to terminate humanity, but the real stuff, the bias, the misinformation, the, you know, all of the near term risk, technological unemployment and all that kind of stuff, right? How do you come to that middle in a way that really makes sense for an organization?

Speaker D: And also, I mean, maybe to answer the question, I'm going to, I'm going to steal your thunder, Mike. I'm going to steal your thunder. Wit. I'm sorry. I think some of it too is that we continue to have the personal productivity versus enterprise.

Speaker E: I think that's a big issue too.

Speaker D: Right. It's great on a personal productivity level, once you learn how to manage it correctly and not let it basically become your voice. Right. Like as soon as you do that, you're basically asking for trouble. But if you, if you actually incorporate it as a true kind of, uh, assistant to knock out kind of hard tasks and repetitive tasks and really turbocharger work process, then it gets to be pretty excellent. But when we start looking at these more complicated, sophisticated enterprise applications outside of traditional ML, we continue to see massive fall downs on the generative side when we start talking about enterprise wide applications such as customer service, such as AgentForce, which still touts a whopping 58% veracity when it's deployed, which they think is great, it's not right, you need it to be at least 90%. So these types of failures is really kind of ah, are really kind of the touch point I think where skepticism is legit versus hey, we've seen this now for a few years. There is a place for it in the workplace.

Speaker F: So I think there's a, uh, few things that I'll touch on on that one is from a leader perspective, I think you just at least need to recognize what biases are probably at play. And those biases are there for a reason because they're heuristics to help you make decisions and they've served you well in the past and so you're not necessarily throwing them out. You at least need to ask the questions to challenge whether my natural bias for how to handle this is the appropriate way to handle it. And do I need to recalibrate as the technology evolves over time. There's the pattern bias, right? We've seen this before with other technologies. We're going to run the same playbook. There's the risk containment bias which is I'm more worried about making a mistake than I am about the risk of inaction. And does that still hold here? And then the uh, linear budgeting bias, right? Can our linear budgeting plus annual planning process, you know, does that work with an exponential technology and can we actually get where we need to go with using that same playbook? And maybe you can for a while, right? If we're really seeing AI struggle to beyond personal productivity to have these enterprise applications this slower, we're going to go measured, we're going to be careful with the approach that may be okay so long as you are also planning for when this technology will get better and what that may ultimately do. And you're doing that in parallel. So you're looking at like a box one innovation of how do we incrementally do better what we're doing now. But you're also looking at a box three, what's our future state and you know, box two, what do we need to let go of in order to get to that future state and having more of that holistic conversation. So I think I Think that's important. And I think the other thing that's really hard and understandably hard for executives and leadership teams right now is an investment decision you make in AI technology is likely to be obsolete in the coming months, right? Like you could choose to build your own tool and then one of the commercial off the shelf platforms may roll it into their base platform in two months. And everything you did to build that tool is now obsolete and out of date. Right? So it becomes really hard to pull the trigger on meaningful investments because of the pace of change of the technology. And so you have to balance, like, how do we not do. How do we not do nothing that leaves us too far behind and not learning and evolving with. How do we not go all, all in or over, invest in something that is no longer going to have value as the technology evolves in the next few months?

Speaker E: Super hard.

Speaker D: You just made the pitch for adapting through SaaS platforms, right? Because I mean, the more you do on your own, the more likely you are to be obsolete. So you may as well just roll with your existing platform vendors, assuming they're adapting well, and just take their application iterations lesser than if you were to do it on your own. However, most, most enterprises aren't billion dollar organizations. Most of them are small and medium businesses and they can't afford to do that.

Speaker A: Right?

Speaker F: Right.

Speaker D: Yeah.

Speaker E: I wonder, you know, to, to build on that. And Jeff and I talk about this kind of thing, you know, fairly often is, you know, there's this whole sense of there are those who are going to adopt and adapt to AI and those who won't, right? There's that, all that rhetoric around, that divide. Um, but when you look at SaaS platforms and the extent to which they're integrating AI into everything and not just SaaS platforms, I mean, we're integrating AI into, you know, television services and refrigerators and toilet seats right? Now, some of that is stupid.

Speaker D: Um, and I had a conversation today, well, after my coffee with ChatGPT in

Speaker E: the bathroom, literally is a Kohler toilet seat that has a chatbot built in.

Speaker D: I don't know if we find that, but nonetheless, I have one idea. He might be in office right now.

Speaker E: Putting the toilet seat aside, seems to me that for an organization who might, I'm not gonna say who's waiting it out, but ultimately everybody will be using AI in a way that it's kind of ambient where you want to be. You won't be thinking or even realizing that you're using AI. It's just embedded into your experiences. I love that. And does that represent even a viable strategy for some, let's say even mid sized businesses who can't make massive investment, you know, kind of to really get on top of how are our current tech stack vendors integrating AI features and functionality, how do we use that as our gateway drug into becoming a more AI forward organization? And eventually, you know, we kind of rise with the tide as we become better and better at using these AI tools.

Speaker F: So I think what's embedded in your assumption there is that the individuals within the organization are taking a personal responsibility to learn the AI technology.

Speaker E: Um, that is absolutely embedded in there.

Speaker D: Right.

Speaker E: And we've seen that's not always the case.

Speaker F: Which I think then becomes a viable strategy of yes, we're going to leverage the tools we're already investing in our core stack and the mandate on our organization is going to be to become use AI more as your first reach for when you're doing your work and embedded into the core way that work is getting done as opposed to an add on a side project, a curiosity. And I think that's a mindset shift. Right. Like for years people's first reach is it's word, uh, it's Excel, it's a Google search. And for m more and more people the first reach is becoming hey, I'm gonna go, I'm gonna go to the chatbot, I'm gonna go develop a prompt, I'm gonna run a deep research query, I'm gonna go change this into an audio and instead of like going through the whole process myself and figuring out the details, I'm gonna figure out how can the AI help me do that? Even things like I'm in a car and I'm talking to the voice mode and the AI to look to prepare for my trip to and learn some Spanish and I'm just like, hey, I could turn on the radio and listen to a song or I could take this as a microlearning opportunity around something that's super targeted to what I'm doing and get a moment there. And you still want to protect human only time and have these, these think times and not have AI go in everywhere. But at what point does the AI tool or the AI enabled process become your first reach for how to get things done as opposed to the way, the more analog way perhaps you've done it in your past. And I think that that's critical more so than what's the delivery mechanism of the AI? That's more of a mindset shift.

Speaker E: Yeah, um, um, I kind of want to pivot back, I think to something. It was something that kind of went in my head before I had a tech issue, dropped out and then came back. Um, so I didn't get to. So I'm going to kind of circle us back a little bit.

Speaker D: We know that ChatGPT booted you.

Speaker E: We were, um, we were talking, you were talking about. And we fundamentally, I think all agree on this, that to a large extent it's on the individual to make the time, take the time, have personal responsibility around upskilling around these tools and incorporating them into our workflows. Um, absolutely 100%. Now, at the same time, uh, you know, I wonder what leadership's responsibility is in a scenario like that. And I'm thinking about the spate of recent CEO announcements. Right. Which of course have all been made out in public. As if everything that happens inside an organization is meant to be public knowledge. Right. All the CEO letters and blog posts and whatnot, where there seems to be this very distinct carrot and stick, right. Where CEOs are saying, we want you to embrace AI, we're maybe even going to incentivize that. Or we're going to start to goal you on that as you described. And we expect you to go to AI first. Oh, but by the way, a lot of you are going to lose your jobs anyway because we're not going to have the need for as many human beings in the organization. Right. It's the Amazon announcement, it's the Klarna stuff, it's IBM and you know, Salesforce or whomever saying 50% of our code is now written by bots, that kind of stuff. Um, and I feel like there's a tension in that, that doesn't incentivize people to engage with AI in a positive and proactive way. It makes it fear based, it makes it reactive, it makes it disengaging in a lot of ways that I think ultimately is harmful. I guess my question really is, what's your perspective around that? Because it seems like that carrot and stick is really not the right way for leaders to bring their organizations along in the journey.

Speaker F: I think there's a few elements of it. One, I think leadership communication to bring AI use out of the shadows is critical. Whether leaders know it or not, people are using AI.

Speaker D: Sure.

Speaker F: Like particularly their earlier workforce. And I think the more that you elevate that conversation and make it okay to talk about AI use, how you used it, what you learned, what that brought to the process is critical to reaching the tipping point in the organization where that productivity gain and the uh, adoption accelerates and it has to be less top down driven and fear driven. Right. I think on the fear side in a lot of these organizations the change will be slower than the hype. Right? Like, and that is in part because of these choke points that like whether it's how data flows across systems, whether it's how decisions actually get made in organization, how work it does, whether it's reticence on the client side to stuff that work. I mean you could go do an environmental regulatory analysis and you could use AI all day to write the chapters to respond to comments, to accelerate the document creation process. And if you run into an 90 day stakeholder engagement process where you get to go host workshops out in the community, the process, you know, there's still a choke point there, still fast, it's still going to be just as slow. And I think there's like this knowledge of how do I, how do I actually navigate the real world to get things done using AI to inform that process and let that, like how do I let the speed of AI go through these choke points at the right speed? Combining balancing risk and kind of flow and calibrating those. I actually think that's a skill that humans are going to need to impart for a really long time. And I think those employees that embrace the tools with their domain knowledge and start to understand that flow, there will continue to be roles for how do we actually navigate this interface? It's going to be interaction design, right? Like how do we design the flows of information, how do we navigate these choke points? And I think there's a long Runway for people to have value in that process, but only if they're engaging. If they just disengage and say I don't want to engage with this because I feel like it's going to take me out of a job eventually, then you don't have the knowledge needed to transition to that next piece of value. Which is more about how do you help AI deliver actual real world value as opposed to the theoretical value from an intelligent system.

Speaker D: And I think what you're speaking to as well is this belief that AI, uh, is fairy dust. It's a panacea to resolve your problems. But the reality is you like every technology, it's really a mirror. It just shows you your problems. In fact, it breaks into life a lot faster, rapidly.

Speaker F: Identify the slowest point in your process.

Speaker E: Right. I don't know if it's an irony or it's a reality. That's all it is. Really is a reality is that so many organizations have so many breakage point. Um, it's still very human. People process technology data that the AI just, you know, they think AI is going to be a solution. It ends up becoming the next challenge. Right.

Speaker D: The data disasters are just shocking. You know, everybody wants to go 0 to 60 and they can't go 5.

Speaker E: Right? Yeah. And that's all the way up to some of the largest organizations in the world. Right. You almost expect it with an organization that's smaller, cash strapped, resource strapped, maybe is running on retrograde technology or whatever. Uh, but then you get into a top five consumer packaged goods brand and they can't integrate customer versus prospect databases in a way that's meaningful.

Speaker D: Yeah. We're running out of time, so, uh, I'm going to throw it at you. Any last moments of brilliance for our listenership? Always have you back too, right?

Speaker F: I always like to share a book that I enjoy reading or things that others might go into, I think. The Friction Project, how smart leaders make the right things easy and the wrong things, things hard is a really important concept in this day and age. It's not about trying to drive your organization to be frictionless and let AI take over and let it flow throughout the organization unfettered, unchecked. But it is about understanding where your choke points are and calibrating those to this is an invaluable one. Or, uh, this is one that doesn't have value that we should be removing. This is one that, uh, appropriately provides governance and risk control. Or this is one that we had pretty tight because the technology was nascent and now it's getting better and we're getting more confident and now we can open it up a little bit. And I just think that's going to be, uh, an increasingly important leader responsibility. And that concept in that book was really helpful in thinking through that.

Speaker D: Very cool. All right, we'll put a link to the book in the show notes. We'll put a link to your LinkedIn in the show notes as well, and most importantly, your substack. And so with that, Mr. Verdino, will you take us out?

Speaker E: I sure will. Wit, thank you very much for joining us. Again, in the show notes. You can find all of that@nobrainerpodcast.com just find the episode click in and you've got everything you need there to catch up on all of this good stuff and find Wit everywhere he lives online. Uh, in the meantime, again, as another reminder for everybody who's still with us, please be sure to subscribe to like to rate, to review, to love to share, to comment to uh, whatever with this episode. Um, we are looking forward to seeing you next time. Thanks for joining us and thank you to Whit for sharing all of his insights, wisdom and ideas with us today. Have a good one everybody.

Speaker F: Thanks guys. Really enjoyed it.

Speaker E: Cool.

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