Preparing Leaders and Learners for Human‑AI Collaboration with Patrick Lynch

Acorn is a capability-led learning and development platform that maps roles to the capabilities they require, identifies gaps at the individual, team, and organizational level, and turns those insights into targeted development. Powered by an AI-driven library of over 1,600 capabilities and 4,800 proficiency levels, it works alongside existing HR and learning systems rather than replacing them, turning disconnected data into an evidence-based picture of organizational capability. Learn more at acorn.works. Welcome to ATV's Talent Development Leader podcast, featuring monthly conversations with the greatest influencers in the talent development field. We cover the latest trends, hot topics, and future-focused ideas that current and aspiring TD leaders need to know. Learn more by visiting www.td.org and searching for talent development leader podcast. Today I'm joined by Patrick Lynch. Patrick is a thinkers 50 Radar 2026 thought leader and one of the world's leading voices on human AI collaboration. As AI faculty lead at Holt International Business School and a former Accenture Research Fellow and VP at Walter's Clure Health, he brings Fortune 500 executive experience and behavioral science rigor to the most urgent leadership challenge of our time. His thrive framework has shaped leaders globally, author of How to Outsmart AI and Thrive to be published later this year, and contributor to the thinkers 50 AI Ready Collection. His TEDx talk has surpassed 400,000 views. Patrick's pragmatic frameworks, real world case studies, and actionable strategies are shaping global leadership, providing a practical roadmap for leaders who want to apply AI without losing what makes their teams valuable. Hi Patrick, thank you for joining me today. Thanks Ann, that's really nice. So glad to be here. You will be attending the ATD International Conference and Exposition in Los Angeles this May, and you will be speaking at two separate sessions on the topic of human AI collaboration. ATD is super lucky to have you, very excited to see you there. And I'm pleased to discuss with you today in broader strokes, some of the ideas that you'll present at the conference. So first I want to talk a little bit about your TEDx talk and some of the big themes that I pulled from that when I got the chance to listen to it. 400,000 views certainly, there's a lot that you shared there, and a lot that's gotten a fun conversation going in the space of human AI collaboration. You've explored how the workforce has been and will continue to be significantly impacted by widespread AI adoption within organizations. You claim that this impact is less about job loss and more about job transformation. Can you talk about this? - This is a great place to start. And the pessimists are going to find the day to day fear and the optimists are going to find the day to day want. But I'm a realist. There's absolute agreement that it's going to have some kind of job change. And I think this is something that we need to prepare for. Sometimes our going to disappear and yet others are going to create it. In between is going to be a bumpy ride that we all should be preparing for. So currently you can see in the media every day that there are roles that are being disrupted. You can see in the software industry, I think the data is very clear from just a few years ago how much software engineering has changed. But the real data that is being unveiled as we speak almost daily is that the impact is relatively minor, at least right now. While we need to be mindful that the disruption is possible, we're not really seeing this in mass. In fact, if there's some good evidence that a lot of earnings calls and sea suites, people are touting changes because of AI. But we're not really seeing it yet in productivity or in those gains. I look at this other perspective. Many out there are familiar with the Godfather AI, Jeffrey Hinton. Years ago he had advocated that we should stop training radiologists. And it really wasn't too long ago. And that was because deep learning, the ability for AI to use visual analysis to detect disease or other kinds of things that a radiologist may be looking at was going to be superior to a human. Well, punchline is that didn't come to pass. In fact, radiology has become one of the better professions that you could be trained in and may have clicked. It has expanded. There's staff to over 400 radiologists. I believe that's over 55% of what they were at that time. And many medical students are choosing radiology. And that has doubled from 2020 to 2024. The point is that we need to see that there's going to be dramatic changes. While no one has a crystal ball on this, we can be certain that there is going to be a change between here and there. And we need to prepare ourselves for that. One of the things I share with our MBA students all the time is that data is a catalyst of all change. When we can measure something, it changes what it is that we do about that. And what is AI but data? So we should be expecting a lot of change. But where that change is going, I think that we have that opportunity to scare and take heart that it's something that's happening with us rather than to us. When we think about this future and prepare for this future, you talked in your TEDx talk quite a bit about creative decision making and how that's a big component of this preparation. I appreciate that you're a realist. It's not about loss and maybe even about this rapid transformation but more about change, right? Really focusing on just change. And so how can we be really good about preparing ourselves for this change? I'm aging triathletes. I don't want to look or sell accomplishments. But in training for my first full Ironman, which is 140 mile within 12 hour event, if you do swim bike and run, I was giddy telling my coach at the time about how fast I had run my latest workout. And he smiled at me. He said, that's nice. But you need to learn to run long, not just fast. So taking that perspective of the long view is the way that I think that we need to start to be preparing more for creativity in the workforce. We've inherited some fallacies or certainly things that no longer hold true, like span of control of being say five to 10 direct reports. It's really being inherited from an industrial revolution of the past. Clearly, this isn't going to take-- or be appropriate for the AI future, where we have individuals managing not just people, but bots or AI agents that are going to be also doing tasks. It's a hybrid model that we haven't seen before. Recently, you might be aware that the CEO of Salesforce said that you or your parents are the last generation of people, of managers, will ever only manage people. The future generation of managers will be managing a combination of people and bots of some kind. This is really where the creative decision-making is needed. And we're not measuring the right things, I think, right now. The take on this from many economists, in fact, is that if you're only managing automation and tracking speed, that is the quantity of more deliverable sort of quantity and more stuff, you're really leading a lot on the table of what's possible. And instead, the real thing we need to be measuring are games, that is, things that we can do, that augment, what it is that we're trying to accomplish. And that means jobs are going to expand, that we need new tasks, that we need new solutions, things that we couldn't do before. That means that as companies grow into these new jobs, we're going to win by helping them tap into the creativity. That sounds maybe like a platter tube, but this is not something that is new. Again, I give you the training example. I watched an Olympic athlete that was training to run faster. And she was pushing her legs forward. Again, my coach had us watch this on slow motion. And what he counseled was that you don't run faster by pushing, you run faster by pulling your leg through the stride. And this allows your body to naturally run faster. And this is, in fact, what happened to this Olympic athlete. We know how to help our workers, our employees, pull things toward them and enhance their creativity. So we can see this all the time. That means that we're going to probably have jobs that have more autonomy, that give more decision-making power to the workers to do the things that are appropriate, that tap into intrinsic motivation, that allow them to draw the kind of cognitive flexibility that really inspired them. Today, we just may not have those kinds of things. So that's why I think the lesson of change is so important here. So if we want to tap into that creativity, we're probably going to need to have new kinds of job roles that allow people to do new things that they couldn't do before. And it's going to be done in new ways. And we can do that by constructing the right kinds of conditions that are for that. I'm not saying that we don't need appropriate controls, but micro management, rigid processes that work for an industrial era that has now passed us in peak creativity. So I think we need to think about augmentation. And that means we need creativity, curiosity, critical thinking, communication, collaboration. These are one set of the five C's that you can find out there. And I think that there's great value in all of our leaders thinking about this and I think that's what the audience I hope. can take away from the ATD conference. - Well Patrick, I have heard that the number one way, you know someone is a triathlete, is that they tell you. You have confirmed that for us today. And I say this because my husband is one as well. So I, you know, we like to talk about it. And I'm a long distance runner. I could geek out with you over this all day, but I love that analogy about the long view, especially when it comes to creativity. And I think the idea of setting the context to, I mean, talent development and the way that field has been transformed over the years is all about, we're no longer pushing out content, we're pushing out learning or training, but we're creating a context in which learners can pull from. So I think that's the same when you look at human AI collaboration and think about the ingredients for creativity and the skills and the habits that you develop there. - I think that's a good example. The amount of ability for us to push out training. I'm a trainer, I'm a professor at university. And it's easier than ever for us to spin up more training. But then I think it puts a premium in fact on making sure that it's appropriate and tailored. And also there's new opportunities to personalize that. So we're now training because we're helping learners learn in new ways. One of the things that we can agree on that I think the evidence is very, very clear is the more AI tools that we adopt for AI state, there is a tax. There's a cognitive tax on workers or on productivity. And in fact, in some professions, now the job of managing the AI is causing AI brain fry because you're having to check and recheck the work that maybe a bot is doing for you. This has a real deterrent, I think, on appropriately applying them. And also for us to reach there are a lot that we're looking for. So there is a greater oneness on us as leaders and as L and D leaders and managers in all levels to think about where it's appropriate. And that's what I think the poll analogy, oftentimes the best people who will be able to know whether it's appropriate for an AI tool to assist them in automating things that are routine, that they can trust with confidence and then augmenting the things that really they do best is going to be the workers themselves. I would really applaud as to take heart that we can allow to have a conversation, a collaboration with our teams on what's appropriate. And indeed, I think the best companies that are seeing the value add from this are doing that. They're asking workers for those ideas, there's many different ways that you can do this and then they're adopting, they're pruning really out what doesn't work. I can see this kind of poll analogy whether you want to talk about. Your runner or the traffic in any of us, (laughing) we're a manager, we need to probably adopt some of that because no one knows different from in the past where learning could be structured where there was a sage on the stage wisdom that we were trying to impart. This is the time where the tools are so flexible and they become so embedded that we're gonna need to have collaboration. I think that's where the poll analogy comes in. - It's also an exciting time for TD leaders. You think about the emphasis that needs to take place on human AI collaboration on the human side of that and all the possibility and opportunity there. I think that's where in this area of change, people can take hard and get excited about what's to come. So immersive learning, kind of a shift in topic, if you will here, but still really focusing on your TEDx talk, which I encourage listeners to check out in full. You talk quite a bit about that and immersive learning has existed certainly in the TD field for quite a while, but now with in the age of AI, the element there, has really changed things and the lines between digital and physical, as you have said, are blurred. What does that mean for immersive learning in organizations? - It's interesting just around the corner from where I live, there's a new theater, movie theater. People used to go to movies by the way, and I'm gonna check that out. To bring people back into the theater 'cause now some layoffs are just streaming on TV, they're installing a new 4D theater. 4D is gonna be all the things that you're used to, but then maybe you have sense or smells or even sensations that you can feel something tactile. And in the L&D space, this offers a gold mine for us because especially when we're talking about safety or any kind of risky activity that we have, humans involved, having some kind of assimilation that's as close to real life as possible is likely going to mean that we have better outcomes in terms of reducing risk. And also, it improves learning because it's in Bevo, it's going to be as close to the real life experience as possible far better than reading it in a book. And so I do, and the TED Talks, speak about these 4D experiences. One of the opportunities we all have is, go to Vegas, go check out this area. There's gonna be some great experiences there if you haven't seen this as a consumer. But while certainly those kinds of immersive experiences are 4D, not all immersive learning require 4D kinds of theater experiences. You can have an immersive learning experience through a roleplay. You can have immersive learning through assimilation or a gamification, something that raises the stakes where there is gains and losses. And we're familiar with that, but now these tools do make those kinds of learning experiences more approachable than ever before. We also have the ability to customize that. I know of many, many companies that are tailoring these kinds of learning experiences so that we no longer have to have the same kind of responses to check for competencies. But we can tailor that and vary that based on the evidence that we see happening in real time. This offers a huge opportunity for better transmission of the learning and better building of those competencies. Immersive learning can be in all kinds of ways, not just the 4D experiences. One of the examples that recently happened, and I think really illustrates this is the use of digital twins. So this is the use of the AI to have a simulated environment, a safe environment, but very real to what's going on. I believe it was the physicians at John Hopkins that used this digital twin for modeling heart ailments, specific to the patients that they were treating. This allowed for much more tailored intervention, whether that be a therapy or some kind of surgery, that led to increased outcomes and better outcomes for the patients. So I think L&D leaders at all levels, what you're looking at is how can I mimic in real time and in real life more the situations that I need performance out of the teams. And now the tools are more ahead. I think that we're going to see more and more of that through spatial computing. You might be familiar with the glasses that are becoming much easier. And we don't need to have these full masks on anymore in order to communicate that. We're going to see those kinds of things become much more commonplace the way that we do with other kinds of technologies. And I do you don't need something even as sophisticated as that. A lot of these things can be done through the phone or other kinds of technologies that workers already have access to. So I see a great opportunity for us to not just in training, but also providing expertise in the moment where it's needed. I think it's obvious in high risk situations. There have been rough necks, which are, I believe that's the correct term for them, for oil workers in the field, that are touching high risk equipment to get expert advice in real time. These kinds of learning experiences, but what does that mean for white collar workers, for people that are facing challenges every day? We're going to see lots of improvements coming up for learning and development on those aspects that were previously impossible, but they're going to have better outcomes, I think, for all of us. And they're right around the corner if you're not already here today. We've been talking in a field forever about performance support, learning in the flow of work, create these kinds of things, the tools that are possible now, just change the game, which is, again, I think exciting. You have said because of AI, we can design these immersive learning experiences that are active, collaborative, and personalized. Learning is not something that is confined to a classroom or bound in a book or trapped on a screen. How profound. I know that this will resonate, does resonate with our listeners today. What actions might they take to be part of this game, to be on the leading edge, to continue to drive the transformation that's happening in the future of work and learning? I'm honored that you picked up that quote from the TED Talk, that's music to my ears. As an educator, as a professional, that's dedicated to this, I've seen that for a long time, and certainly in my lifetime, went from the only way that you instructed was in person in real life to effectively being trapped on a screen. And there's nothing that matter with that. Those things have their place, and I think there's good evidence that we are reaching broader audiences. It has its purpose, but it's not the only way to communicate learning. How can an LED person or any leader really tap into that? I think it goes back to what we had started on our conversation out to expect changes, to expect changes in jobs. And we're seeing evidence of this right now. What we could expect to see is many more player coaches that you are maybe taking out some roles of hierarchy or leadership. And jobs are expanding with these kinds of opportunities that we will see individual contributors expand, we will see the idea of leadership or management expand the kinds of things that are touching on. A simple example that I think I did have this in the TED Talk, but it's a good one because it's easy. The marketer now writes the copy, creates the ad, and posts online herself. These are roles that would in the past require siloed individual expertise, where we're throwing something over with a help ticket or a juror ticket to get done by somebody else. We're seeing jobs expand. So I think we need to think about those opportunities to step in to more those kind of player coach roles, where we need the technical expertise of some domain, which is going to be-- to be easier than ever for us to acquire and build those skills and capabilities for the same reason that we just discussed with immersive learning or just better learning techniques. And we're going to see jobs expand to do that. I would say get it start on piloting that it might be carving out some section of the team or some section of the function to try this out roles and responsibilities that used to be handed off look for any kind of hand off. I'm a student of the six sigma era. We are trying to six sigma everything. I remember the day in my data analytic company that I was working at where we were advised by a consultant to take down the partition walls. Now there's nothing that matter with an open workspace. I've been in many of these. But if you're trying to retrofit a space that isn't ready for that kind of work and you're suddenly staring at the backs of people's heads or the sides of their faces, it's not the best thing. And I think this is the kind of whole over idea of something that worked in a prior industrial era being misapplied for the kind of work that we have today. So it's not easy to say all the different ways that we can start to lean into this. But the idea of a player coach, the idea of breaking down silos, I think is tilting us in the right direction. I thought about three things here that leaders can do. Stop treating AI as an adoption or a training program and start to think about it as part of the job design itself. How are we going to collaborate with AI? We should anticipate these org structure changes are going to be part of that. And that means there's lots of role for L&D to think about the new kinds of things and new kinds of skills abilities and talent that we're going to be needing in these new roles and make a plan. It should not just be something that happens and probably not something that happens all at once, but more that we're piloting. So I can anticipate the next three to five years. A lot of these pilots are going to need to be going on. And I think L&D along with peers in these other functions are going to need to be collaborating on what that looks like appropriate for these functions that we can figure out how to pull rather than push these kinds of solutions out to our teams. I like the idea of the org structure changing. So it sounds like maybe flatter organizations, more opportunities for all when you think about this. You had mentioned earlier, we've talked among an executive group I work with in talent development about when you think about talent management in the coming years. You're not just onboarding. As you said, people are humans anymore. You're onboarding a mixture of agents and humans. And what does that mean for your talent management, your acquisition strategy? I think about the span of control that I mentioned earlier. I don't think we have a good answer right now on what the appropriate span of control is. But we need to be aware that just because an AI is running, there is a cognitive tax or cognitive debt that occurs with the addition of each one of these. So it's a very interesting space that we will collaboratively, I think, figure this out. So in May at ATD26, you'll be unpacking more around human-centered AI implementation. And you'll be talking about your model thrive. So this model, the Supreme Work, helps leaders design adoption as elevation, not replacement. And I assume this is a big topic in your upcoming book as well. Let's talk a little bit about this framework. Let's just kind of tease out some ideas ahead of the conference. So the framework starts with purpose and gives talent leaders a shared language for guiding their organizations beyond use cases. I love that. And into strategic implementation. Can you talk about the model? Also, your impetus for designing it and why you believe it's particularly useful to TD execs. The impetus is easy because you can see the headlines daily. Most companies are throwing millions at these implementations, but very few are able to scale it or scale it with any kind of measurable benefit yet. It goes from BCG, McKinsey, Goldman Sachs, basically zero impact right now in the ways that it was promised. What's going on here? I offer this is this pattern. We can break this pattern. We can be smarter about how to implement that. Along the lines that we've been talking about this framework, these six components, I'll just touch on them here because it's a lot to take in maybe just listening, but it starts with this acronym of Thrive. And so the T is about transformative kinds of engagement. And that is using AI to do the work that really matters to you. So it's always going to start with defining that purpose. This again is high productivity. We don't want to just do more stuff. We want to do the right stuff. And so by having it help automate the kinds of things that are appropriate, that's great. But then what's left over? That's the stuff that I want to own. It's probably going to be requiring my judgment. The R is resilient adaptability. We're going to need to have a team of learners because it's a lifelong learning. We've been talking about this. It's a commitment to absorb whatever the next wave of change is. So we need people that are adaptable to that. The I is about your imagination, your creativity, your ability to tap into things that the AI simply can't is your territory and you need to own that. The V is value through ethics. Again, where is the human in the loop? This is going to get harder and harder as these tools get implemented. We're going to be delegating a lot of decision into to AI. But where are the checkpoints and where are the stock gaps and where are the appropriate ways for you to be involved? And the last is about being efficient and being efficient is pulling all together. I think about this idea to not just streamline, but dream line. And I know that's a funny play on rewards. But the idea is when we were in six sigma, we always talked about the happy path through a set of processes or steps. And I think that AI allows us to tap into that. So don't lose your dream line. But when you're doing that, you need to think about where it's appropriate. So to be efficient is to be looking at this all the other steps and be holistic about that. As a guide, I think that you can use it as an individual. You can use this as a way of understanding what you want for your team. I think it's a shared language to think about like a roadmap. And as an organization, it's a blueprint for how to maybe adopt AI. So this is what I've been helping company with for years. This model took off a while ago. And I don't really think about it just as a model, but more like a game board as a game board. You're in the center. And these are just for an area that you need to visit on the game board by visiting these each corner is going to help with clarity of a purpose for that thing. And by going across this and whether I'm talking about this as if I'm coaching individuals to think about what it means to them or you think about teams. This is I think what the community should take away that we can have a framework or guide or game board in order to guide or thinking we need something like this because the evidence is throwing AI at everything. Just thinking there's some magic bullet that knows more than we do or it's going to do something more than we do. I think that the evidence is that's not going to happen. But there is evidence that they can augment and prove productivity in certain cases. And we need to figure out where those are. That's great. I know there's so much chaos right now, so much uncertainty, so much inconsistency in organizations when it comes to AI implementations. So I love how this like you said, it provides a shared language. It centers people. You have a game board to work with. Curious about the use case piece of this. How does the thrive game board help leaders avoid the trap of chasing AI use cases and instead building that long term plan or the long term capability. There has been just a lot of obsession with use cases. How's everyone else doing it? But to instead look at your organization and what makes sense within. I see the weakness of the use case that it worked over here, so it should work for us. And when I'm advocating for as much more of an experimental mindset, there's a very good evidence coming out now from different companies that are looking at appearing AI to do different tasks with individuals, with teams. And having I think very good scientific ways of measuring the benefits. It's not just the productivity benefits, but it's also the experiential benefits of the workers. Are they feeling that they are doing more that they are designed to do? I haven't met a customer service operator anywhere that doesn't feel that they aren't deploying strategy. They're very high order kind of tasks when they're managing, especially their top clients, and they feel that's what they were there to do. They're not there to simply push buttons. They're adding overall value. I don't really have a problem with the use case because I suppose that it's some level of those hard use cases you're trying to figure out where it works. But I think that the opportunity is to look at what's appropriate for your organization. It doesn't slow you down to do that. In fact, I think you go faster. And the risk is it worked over here, so it's going to work over here. I gave you the example very much in my own experience and thank goodness for Jack Welch. But applying that kind of six sigma thinking to knowledge work, if you bid around for a while, I'm unconminced that was the best use of our time. And yet I trained many yellow belts and green belts and black belts in my career. I'm very proud of that. We did great work. It wasn't appropriate for every task. And this is what we're looking for for you. If that's a use case to figure that out, yeah, build your use case. But take the time to figure out what works for your situation. Don't just grab the next AI tool or something that is being touted in the media as the next new thing. Ask the deeper question of what does that mean to me and set yourself up for success by having some kind of pilots or experimentation to figure out what the use cases are. Otherwise, you're probably going to be driving cognitive debt and you're going to be causing a lot of rework because a lot of people are producing things that they have to double check. And that's slowing everything down and producing the kind of mediocre kinds of ROI that we're seeing. So it's about appropriate use. And I think the truth is somewhere in between. Additionally at the conference, you'll be introducing this concept of I love this the Alice Effect, which implies that continuous AI innovation trains people to habituate faster than organizations can differentiate. When AI makes knowledge and personality. Commodities, the only durable advantage is what it cannot replicate, which is the human premium. Again, when we're talking about the human element here, what is that human premium? And why is learning and development uniquely positioned to build it? Many people, I bet you too. You are amazed the first time that you saw AI summarize meeting notes or drive out those action items. That has quickly devolved into AI slot in all kinds of forms. Not just the video images of people doing things that are super ordinary, but you have colleagues who never wrote a paragraph in their life are now generating 20 page documents and distributing them to dozens of people for review. That is empty padded. They sound confident, but they are not in fact a strategy that you want to see at scale because it's going to be slowing you down. Wonder has a half life. And the Alice effect is showing how AI is speeding that up. The Alice effect is the Alice you know the Alice effect is akin to another effect called the red queen effect that was already established in the management of literature. And that has a lot more to do about how firms have to continue to innovate just to keep up with the competition. And this does go back to the Carol novels and it has a great history. You can read that. But the part that's missing was this other part, which is the Alice effect. And in the novel Alice has a great line that there were so much going on that she just ceased to find it unusual or even absurd. And I feel that's what's happening with AI. And you tool gets launched your colleague is start using it they're spinning out all this stuff that doesn't matter. The human side of that about what's happening and this is relevant for L&D relevant for any leaders. I think you have to look at the human premium as a check or as a backstop about whether you should be adopting or using that AI. The first is creation. Use your own judgment about whether it is appropriate for the AI to be involved in that process. Or creation just because contents unlimited to be produced or any tool could be used you have to make sure that it's appropriate created. The second is that it's connected. What is the capacity for somebody if you were to produce that thing or send it on for it to continue to add value. And you have to decide again where that's appropriate. And the 30s your capability. You want to tap into the own Googleable wisdom that you've earned through your career. Your knowledge matters your expertise matters. Creation connection and capability are I think the AI slop speeding up of this Alice effect that everybody can touch these tools and everybody can generate this stuff. This is a good time to check ourselves before we wreck ourselves with all of the wonder that's coming about. And listen more for the signal than the noise. This three things I think are just a backstop against producing more and more of this kind of output because that's not going to stop in fact is going to get easier as these tools are democratized and more people have access to them. I think it was a financial times report recently said that speed is now the common denominator. So things are moving faster and speed is the common denominator everybody can tap into. And AI just makes that faster for everyone what's left that differentiates is your human judgment your ability to say I trust this output first of all, which is often getting harder and harder because of that speed. And that is appropriate to add value to our mission. So going back to being mission driven in the solution. So I hope the idea about the creation connection and capacity your capability to choose is part of that solution. That's almost the element of slowing it down right where everything is moving so quickly and the human potential the ability to take a step back to be thoughtful intentional and think through it. There is a lot of power and slow go slow to go fast. I guess people say, but that is a really interesting way. I think of looking at it and helping to cut through the noise. The human premium is the strategic role. Otherwise you're just in support. So the human premium is really what's left. There's a saying that I would have written less. I just didn't have the time. This is the kind of idea that thinking slower or having discernment the wing when it's appropriate. And being careful with this is probably the wisdom that we need to take away. And believe me, it's wonderful, but don't lose the wonder don't do that you're doing something that is in fact magical and it can be appropriate if it's augmenting something that you do the strategic is just going to be part of that cacophony. It's going to get lost and I think that's why we're seeing in fact we're slowing down our teams in a bad way. We're not giving our customers what we need. We're not giving our learners what we're not giving our employees what we need because we're just throwing so much at them. So pure eating is going to be I think more important than ever speed is now the commonplace and so you've got to look for something that differentiates and I think it is going to be human premiums. As we wind down today Patrick one final question and I guess penultimate question here asking for a friend. What would you say to the average listener. So let's say someone who's super busy over committed yet high achieving they really want to know all the things be high adopters high implementers at AI certainly thoughtfully. But one of their first reactions includes the sense of overwhelm there's so much to know there's so much understand they can't keep up with it they want to remain relevant they don't want to get left behind. What would you say to them how might they address the sense of overwhelm what's a step they can take to get past it feeling overwhelmed I got it. I'm there right there with you but take heart because there isn't the need to keep asking what the AI can do. The need is to be asking what do I need to do. I can answer that question or better than to ask what the AI can do the answer is there's probably an AI for that out there. This is probably an opportunity that's spring a lot of entrepreneurs right now and that's a good thing maybe that's your answer. But for me and my function for what is I do trying to start there first the framework that I'm offering do put this front and center is the first question you should probably be asking is what do I need to do. It's likely now that there is a tool to help you but you don't need to be overwhelmed about what you need to do I think that should be inspiring about that the real risk is not having a runway that's going to enable us to do that. And so I think we start there do you have the power and can you build the willing coalition that you need to run those kinds of tests and give yourself that time or give yourself with the team to figure that out that's the idea of a pilot much more of an experimentation much more of a player coach or a player consultant. Kind of mentality that I think we're going to need to have embedded in different functions and your human capabilities are what need to be amplified by that so you don't want to just have it be something that's running but again your creativity or curiosity or things that you want to look to enhance and as a leader I think that you can do a lot more to support that and use AI to create some kind of elevation not anxiety if you're using it as a thread. It's probably not it could use a your time and it's not going to be helping your people really thrive with AI we don't want people that use necessarily all the features of AI we want people to use it again appropriately and that list is probably a lot shorter focusing on your purpose first. I guess like with any change focusing on what you can control and what you can control here is yourself right what do I need to do so as we finish today I like to ask this of many of my podcast guests what in your recent research reading or work has surprised you lately. Cost you to pause and think half or a half any epiphanies you'd like to share with us that's a great question and what really pops into my mind is. This idea of AI as a new labor force when I think of it more as a labor force rather than a tool there's also some lessons that I can take from history let me take you back not too long ago in the 1950s when there were a lot of. And it's for new home technologies like dishwasher and vacuum cleaners they were marketed as time saving devices and these were going to be things that freed up the home makers of the time so that they did less housework what did that happen the story is that it in fact didn't the idea that was promoted about all the minutes that you're going to say doing these tasks they did in fact happen because we have these appliances I'm going to wash your. And vacuum cleaner and I believe in all that but what it did was it reframed what it meant to be clean or reframed what it meant to have nutritious meals it reframed what it meant as a household standard I think that there's a lot that I see going on now with AI we started this with there's a lot of pundits out there that are talking about the reduction of force that's going to happen because of these tools. But I think we forget that there is an equal and maybe more powerful force to raise our expectations of what's possible when I look at and I can mention a few books that I've read on this if you're interested to just look at the evidence of what happened at the time for the adoption of those kinds of technologies for the very same reasons you could read those ads and replace what the vacuum or the dishwasher is going to do with AI that's being marketed by most of the companies out. There are about time savings and what they didn't say and what no one knew maybe what no one could have known is that at the same time it was going to raise our expectations of what the new normal is and when I look at adoption for those kinds of innovations and what it has done which is in fact it's made us healthier wealthier and wiser I think that those have been good things it's good that we have safer food it's good that we have cleaner homes but we need to understand. that the bar is being raised about what that new normal is. I think AI is going to be happening to do that. And it's a fallacy that the appliances were not a labor force that really saved us such time, but it did raise our expectations for what normal is. And I think that's what's going to be happening for the workforces all over. Patrick, thank you so much for your time. With us today, I encourage listeners to check out Patrick's forthcoming book, How To Outsmart AI and Thrive. And if you're going to be at ATD26, please check out one of his sessions, one of both of his sessions. All the information is on our website, www.td.org/events. And then you can search for the conference. In the meantime, Patrick, tell folks how they might continue the conversation with you. If they have any further questions, how can they get in touch with you? I really appreciate that. I think the best place is to go to my website. It's my full name, PatrickDlynch.com. If you want to join the club, you'll get some previews of the book and some free tools. I give those out to everyone. So I hope we can stay in touch or I'm linked in. Please connect with me and I'm happy to collaborate. I know that I am better for the folks at Reach Out and Better Part of building this community, the coalition of the willing for us to thrive with AI. Thank you so much. We will see you soon. Thanks so much, Anne. Thank you for listening to this podcast by the Association for Talent Development. 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