How to Build Elite Human-AI Teams in the AI Era

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In this episode, Dr. Jon Finn shares the audio from a recent webinar exploring one of the biggest questions facing professionals and businesses right now: as AI replaces more routine cognitive work, what new roles are emerging — and how do organisations build the human edge that AI can’t replace?

Drawing on the latest evidence from MIT, major tech companies, and real-world business case studies, Dr. Finn explains why we are moving from teams of humans to smaller teams of humans working with AI — and why simply giving people AI tools is not enough.

The webinar introduces the difference between:

• legacy teams
• AI-enabled teams
• and elite Human-AI teams

It also explains why the real competitive advantage now lies in helping people consistently access the high-charge Brain States needed for strategic, creative, high-value work — the kind of work AI still cannot reliably do on its own.

You’ll hear:

• why AI is already replacing significant amounts of cognitive labour
• the difference between “ice cube” tasks and “ice sculpture” tasks
• why most AI rollouts underperform without Brain State intelligence
• how the Human-AI Readiness Brain State Assessment works
• and the three new professional roles emerging to help businesses thrive in the AI era:
  • Human-AI Performance Advisors
  • Human-AI Team & Leadership Coaches
  • Habit Mechanic Coaches

This episode is for anyone who wants to understand the opportunity behind AI disruption — whether you want to future-proof your role, support your team, or build a new service offering in the AI era.

Transcript

AI Disruption As Opportunity

Introducing Human AI Performance Psychology

SPEAKER_03 0:20

Hello, habit mechanics, Dr. John Finn here. I hope we're having a great week so far. Today I just want to share a webinar that we um ran yesterday. So it's the audio recording. The world is changing faster than anyone anticipated. And you will see almost every other story you read about in the news, certainly on the business pages, is about AI disruption. It's nothing to be scared of. It's a massive opportunity and it's going to create some new professional roles. Whether you want to run your own business or you want to uh create a new role in the current business that you work in or in a in a different business. So this webinar goes into the the latest insights, the latest stories that we're seeing around disruption makes them simple to understand and shows what we can all do to move beyond being worried by this these changes. But and instead of doing that, actually capitalise on them. In the webinar I talk about um or I invite attendees to complete the human AI readiness brain state assessment. And you can actually take that using the link beneath the video or rather beneath the podcast. Um enjoy it as ever. If you have any questions, just um let us know and look out because we will be running more webinars in the near future. Enjoy. So thank you for joining us today. I'm going to talk about the new professions emerging in the AI era to help give businesses the human AI edge that they now need to stay competitive and to ultimately capitalize on this brilliant opportunity that the AI technology gives us. In case we haven't met before, I just want to start by introducing myself. My name is Dr. John Finn. I'm the founder of Tougher Minds. We specialize in performance psychology for the AI era. I've worked in the fields of resilience, performance psychology, leadership science for over 25 years now, and I've got three degrees in these areas, including a PhD. So I'm really interested in how we use insights from cutting edge neuroscience, brain maturation science, evolutionary science, behavior change science, and what I call uh leadership and team science to help people to do better. These are the kind of clients that we work with. And um about three years ago, four years ago now, maybe, I released my first best-selling book, The Habit Mechanic, which is a write-up of our approach, the approach we've developed back then over a 20-year period. In the summer of 2023, I was in the London Science Museum and I was in the gift shop, and I picked up a book uh which is about a scientist called Jeffrey Hinton, who is the British academic who's called the godfather of neural network AI. And I thought this book looks interesting, and um I started to read it and I got absolutely fascinated by neural network AI, really because it's designed to work like human brains. And I thought, well, I know a lot about how human brains work, so this is going to be interesting. And then pretty much soon after I read the book, I started to use AI tools in my own workflows, and I started to introduce those ideas to our team. And then for the last, I'd say 18 months to two years, we've been using those tools with our clients, and we were getting so much success. I decided to write a second book called Train Your Brain for the AI Revolution. And this has been out for about 10 months now. It was a little bit early when we first released it, but this is now absolutely the zeitgeist. If you want to thrive in the AI era, the key is understanding how your brain works. And what's emerged out of this work is a new scientific approach that we call human AI performance psychology. Traditional approaches to psychology, to change management, to digital transformation, they are not working in the AI era. So we need a different approach. So everything I talk about today is underpinned by this new science of human eye performance psychology that we've that we've created. So I want to talk about um these new professions that are emerging in the AI era to help businesses get that human AI edge. And I think there are three core new professions. So I'm gonna circle back to these, but this is what I um I think is so exciting is that it's a it's a big new opportunity for businesses, it's a big new opportunity for people that want to provide these services to businesses. So before I get there, first of all, I'm gonna talk about and look at some data around is human, is is AI taking human jobs? Then I want to talk about the difference between AI enabled teams and what we call elite human AI teams, and then we'll come back to the new professions emerging to help businesses build elite human AI teams. To get us going, I'm just gonna share a quick video clip from um a guy called Mustafa Suliman, who is the C the CEO of Microsoft AI. This is Mustafa Suleiman, and it's a Financial Times interview from just a few weeks ago.

SPEAKER_00 6:38

You talk about superintelligence. Most of your arrivals talk about HEMA, artificial general intelligence. Explain the difference between HEMA and superintelligence.

SPEAKER_02 6:51

I prefer the definition that focuses first on what would it take to build a system that could achieve most of the tasks that a regular professional in a workplace goes about on a daily basis. Think of it as a professional grade AGMA. I think that we're gonna have a human-level performance on most, if not all, professional tasks. So white collar work where you're sitting down at a computer, either being, you know, a lawyer or an accountant or a project manager or a marketing person, most of those tasks will be fully automated by an AI within the next 12 to 18 months. And we can see this in software engineering.

Cheap Brain Power And Agentic AI

Ice Cubes Vs Ice Sculptures

Human AI Readiness Assessment

Brain State Intelligence Model

Arrowhead Vs Cross To Bear Profiles

Enter The Human Phase Of AI

Legacy, High Performing, Elite Teams

SPEAKER_03 7:33

So this is this is not from a year ago, this is from a few weeks ago. So what's happening? The biggest companies in the world are investing unprecedented amounts of money to try to win the AI race. This year, they're going to be investing about 650 billion. The predictions that were made about levels of AI investments this time last year have already been blown out of the water for what was being predicted would be invested over a five-year period. And the sales pitch is simple. If you buy AI technology, you can spend less money on human labor. That's the sales pitch. And it's working. So I think that the best way to think about neural network AI is it's like cheap brain power. Um so this is just an article from a couple of days ago. As the price of intelligence collapses, agentic AI is replaced is replacing human workers. One really funny thing that I like in this uh the image here is the poster on the wall that you probably can't see. It says AI strategy, and it says step one, say AI a lot. And it says step two, we don't really know. So, but this is happening. AI is being used to replace human beings. This is a study from MIT from the end of November, and it's you know, you can read the headline MIT study finds AI can re already replace 17, sorry, 11.7% of the US workforce. So this is from an MIT project, which you can check out called the it's called Project Iceberg. And it shows that already, or you know, back then, so this this percentage will have increased now, AI could do the work that 11.7% of the workforce was executing every day. And the labor cost of that work in the US is uh is about uh$1.2 trillion. So AI could already replace about$1.2 trillion of labor uh three or four months ago. And this tech is getting smarter every week. What we saw in the first 40 days of 2026 was global tech companies um made about 30,000 people redundant. It's real, and more have been made redundant since. This is a story that's got a lot of people's attention that came out on Friday, and it's Jack Dorsey, who's a co-founder of Twitter. He has another tech company called Block. Block operate apps like Tidal and Square and Cash App, uh, apps that lots of us use. On Friday, they announced that they are reducing their workforce by 40%. 40%. They're laying off 4,000 people because they said we've been using these AI tools now for the last 12 months, and we've calculated that we don't need 40% of our workforce anymore. On announcing this, Block's share price went up by 20%, and I think it sort of stabilized just over 15%. So the markets have rewarded Block for doing this. So, what's going on? We are moving right now in real time from teams of humans to smaller teams of humans working with AI. So we call them human AI teams. Now, I started my career working in professional sport, and this picture is from about 19 years ago, where I was part of the team that won the league, uh, the English Professional Football League, League One title. And we were we were able to do it by spending 50% less on player wages than the teams that came second and third. They had significantly bigger budgets than we did, but we outperformed them. And from that point onwards, being part of that team, I've almost become obsessed with how do you create how do you max out performance? And that's been my career, I've pursued. And everything that I've been learning over the last 20 years, and very specifically since I got interested in high-performing teams, is coming into its own now. And I don't I don't just want things, I don't want just to help businesses build human AI teams. I want to help them to build elite human AI teams because this is where the big competitive advantage is. Um, and just like sports science revolutionized professional sport, AI is going to revolutionize the way that we work. Just like people like Arson Wenger and uh Sir Clive Woodward got massive advantages from being early adopters of sport science, then the people who are early adopters of elite human AI teams are going to get similar level advantages. Unfortunately, guys, this is a session where I'm going to ask you to do a little bit of work. So um if you have a pen and paper ready or somewhere to note down, I've got a test question for you. According to MIT, what percentage of the US labor market can AI already replace? You may have made a note of this already, you may not. So here is the answer. It's um 11.7%. This was from November, so it will have increased since then. If you got the answer right, you get 10 points. So the aim is to try to get as many of these test questions right as possible and be everybody else on the call. If you do have questions, we will take them periodically, but if you can pop them in the QA, that would be really helpful. So I'm joined today by our head of coaching, Andrew Foster, and he'll be looking at those questions as they come in. So if you do have questions, let us know and we will deal with them periodically. But I want to keep making progress. So what is AI then? What does it actually do? So human beings they have roles at work or in your own business. You have a role, and teams are made up of different roles. But each role has has a set of tasks that it needs to perform and execute every day. And we can broadly separate those tasks into uh cognitively simple tasks to execute. We can think of them as just freezing ice cubes, really simple things that we need to do. People often call it busy work, and the other type of task is more mentally complex, where we really have to think and use our best brain power. That's more what we call strategic work, and we can think of that kind of work, it's like building ice sculptures. AI can help out with both of these types of work. So, what is let's just call it agentic AI, we can use agents to now even fully automate some of the ice cube freezing tasks that we used to have to do manually. That's why Block is able to make 40% of their workforce redundant. And although AI can't build our ice sculptures for us, we can co-work with it. And we call that technology LLMs and uh generative AI. It's all called agentic AI, which is a bit confusing. So we're just gonna call the ice cube freezing uh technology agent agents, and we're gonna think of the ice sculpture building assistant AI, LLMs and generative AI, things like chat GTP, etc. And this has been deployed now in the workforce since 2025, so and even at the end of 2024. So this is the paper from Winning by Design in 2025, and it was published about probably 18 months ago now. So in 2025, AI won't just assist salespeople, it will replace them. When this came out, people were scratching their heads thinking, nah, this that won't happen. Well, it's happening. And particularly uh sales and marketing and tech have been early adopted of this technology, but this is a sales and marketing example. Says this transformation will enable companies to operate go-to-market functions, or you know, taking a new product to market at approximately 2% of the current costs. So the reason this technology is so attractive because it's significantly cheaper than paying a human to do it. And at its best, it costs about 2% of what it would cost to pay a human to do the same task. So maybe going out and finding leads or writing email copy or even sending emails and just communicating with people. So the tech is real, and this article goes on to say, you know, those who adopt this technology will get a competitive advantage so big that people won't be able to catch up with them in the future. And an early early adopter of this tech has been Salesforce. So Salesforce have cut their customer support team by 4,000 people. They still have 5,000 people doing that work, but 50% of the work now they say is done by agentic AI. But this is now, this this technology is now just not impacting um sales and marketing and um the technology sector, it's moving into other sectors at a fast rate. So this is a story about uh KPMG asking their auditors, or as the article says, forcing their auditors for a 14% discount because they said you should be able to do this work faster and cheaper this year with AI. So we're not paying the same price as we paid you last year. So it's starting to bring into question the value of human labour. Another story, this is just from a all these stories are literally from the last six weeks or so. This was from just a few weeks ago. This story is about St. James's place, which is the UK's biggest wealth manager. Uh its shares value fell by 13% in one day a few weeks ago, because a US-based company released a tool called Altarist that can essentially um do personalized tax strategy planning in minutes instead of days or weeks. So this technology is real and it's not going away, and it we're just gonna see more and more of these stories, I would say probably every day now. You're gonna see more of these stories and how disruptive AI is being. So, before we move on, another test question. And the test question is what are the two types of AI? It's really important that we get this framework in our heads because without it, we're going to struggle to understand how to capitalize on it. So we've got Ice Cube freezing work, we can use agents to semi-automate and fully automate lots of that work, and we have ice sculpture building work that we can use LLMs and generative AI to help us with. So if you got that right, then get 10 points. And this is really important ice cube freezing work versus ice sculpture building work. But we can't really understand this until we understand brain states. So now we're gonna think about our brain states, and I'm gonna ask you to do um an exercise. So we're gonna take the human AI readiness brain state assessment. So to do that, I'm going to um put a link in the chat for you so that you can take this assessment. Bear with me one second. So everyone should be able to get the um the assessment from there. And then let me just share my screen again so you can see uh what I want you to do. So you'll get this page load this page will load. You just press take the assessment and um press go. There are 15 statements. Here's the first one. I find myself responding to urgent issues instead of having a plan or sticking to my plan. If you always find yourself responding to urgent issues instead of having a plan or sticking to your plan, you give yourself a 10. If you never find yourself doing that, you give yourself a one. You're probably somewhere in between. So if you work through, eventually you'll get a scorecard. So over to you. Don't overthink it. Once you've got your score, you can write it down. What we're doing here is we're just trying to understand how well our brain is currently performing. If our brain is not performing well, everything in our life is more difficult. So we know that the conditions of the world we're living in are making it harder than ever for our brain to function properly. Um because our brain is encased inside a skull and it feels like it's quite complicated, we don't always pay too much attention to it. But what's going on for many people's brains like like right now, it's like they've got a strained calf or a um a tight hamstring or something. The brain's just not working as well as it as it should because it's overwhelmed. If we want to thrive in the AI era, the first thing that we need to do is get our brain working really well. Our brain is the most complex technology in the known universe, it's far more powerful than AI is. Um, and if we want to actually even Get AI working for us properly, it's going to be impossible unless our brain is working really well. So we need to understand our brain. Good news is we don't need to understand it at the PhD level. That's my job and my team's job. But we do need to have a model that is based on the best science, but is simple and practical to access. And this is our brain state intelligence model. So our brain, your brain literally is like a battery. It runs on chemicals and electricity. And the key thing is that it only has so much charge in every 24-hour period. And you can think of it as operating in three core charge states. There's the recharge brain state. This is the brain state we use to build our ice sculptures. There's the medium charge brain state. This is the brain state we use to freeze, to do our ice cube freezing work. And there's the recharge brain state. This is the brain state we use to recharge our brain. It could be sleep, could also be um non-sleep recharge. And we can use generative AI to help us to, if we're in a high charge brain state, we can use generative AI to help us to build ice sculptures faster, to do that strategically dense work more frequently and to a better quality. And we can actually now start to outsource either fully automatically or semi-automatically lots of the ice cube tasks that we have to do in our in our roles completely to agentic AI. And that means that we're going to make more progress every day because we're able to do more high charge work. We're going to be less consumed by our medium charge, busy, always on brain states. And that's going to free up more time for high quality recharge, family time, time with your partner, time doing whatever you want to do outside of work. And what we've seen, so you know, we've been working on this for this is 25 plus years of work. We've worked with well in excess of 20,000 people now, and we've probably got about um well, certainly over 19 million hours of data points on this. What we've consistently seen is that when people are really at their best, healthy, happy, high performing, their brain state profile in any given 24-hour period looks like this. It's a bit like an arrowhead. So the basis of the of the what they do every day is recharge. This could be 9, 10, 11, even 12 hours of high quality recharge. Then they have a middle layer of medium charge. Because medium charge isn't just what we do at work, it's also what we're doing at home as well. And then that frees up, say, five plus hours of high charge uh brain power every day, where we can do strategically dense work and build those ice sculptures. And if we get the basic habits right and then we build AI into that, we can even go six, seven hours of high charge work every day. So sounds easy, right? That's all we need to do. But the problem is that we don't do that. We don't single task on our brain states because the conditions of the world and actually the cultures of most businesses actually promote and support fragmented brain states. So often people are trying to do high-charge brain state work, but they're actually they keep getting sucked back into medium charge brain states. People are trying to switch off and relax, but they keep getting sucked back into medium charge brain states. They're they're scrolling on their phone, for example, and getting overly stressed about something. So most people's brain states look like this. We call this the cross the bear profile. It's not enough recharge, can barely access any high charge, and I'm just consumed by medium charge uh tasks, medium charge thinking. This is really bad for your health, your happiness, and your performance, but it also means most of what you're spending your time doing, especially at work, is semi-automatable or completely automatable by AI technologies. So if you've got a score from 91 upwards, you've got the cross to bear profile. If you've got a score from um 50, well, from 60 downwards, you've got that arrowhead profile. But wherever you are, you can improve. So I just want to zoom out and then give you a bit of time to digest this. So here's the big picture. We are now entering the human phase of the AI revolution, and it's a challenge. So the most um familiar revolution people are familiar with is the industrial revolution. The industrial revolution automated physical work. The AI revolution is automating cognitive work. So here's what we're seeing AI now is cheaper and more effective at many tasks than many professionals are. So it's amazing at freezing ice cubes. That's why people like Blook are making 40% of their workforce redundant because they don't want to pay humans to freeze ice cubes anymore. But businesses still need humans. They need humans to help them to build ice sculptures, but they only need humans who are what I would call elite cognitive performers, those with the arrowhead profiles who can consistently get into high-charge brain states every day so they can build up the eye sculptures. Unfortunately, most people are not elite cognitive performers, they're struggling. It's not because they don't want to be at their best, it's because they're overwhelmed. And that means that they spend most of their day freezing ice cubes, and this is stuff that AI can do cheaper than you. And being an expert doesn't protect you here because if you're an expert and you're not developing and working on yourself all the time, what you might think is an ice uh sculpture is actually an ice cube. And we've seen lots of examples where AI is doing work that we think only experts can do faster and cheaper. So I think about experts in two camps. You've got static experts and adaptive experts. So static experts are not protected uh by AI. So I want to just give you a bit of time to digest this. You can screen grab this if you want, but it's a breakdown of what I really mean by ice cube tasks and versus ice sculpture tasks. And ultimately, only you know what an ice sculpture task and an ice cube task is for you. But I just want you to spend a little bit of time just making a note of a few. What are the ice cube tasks that I do every day? Or what do I have to do for the rest of the day or tomorrow? And what are the ice sculptures I'm working on at the moment? So I'll give you a couple of minutes to do that, just so you've got those personal reference points. And just to give one concrete example, automating ice cube freezing tasks is an ice sculpture building task. Um I know you've got lots of smart people, my call today, so you'll get that. Um and that's why lots of people are not automating what they're doing because it takes too much cognitive effort right now. Okay, so I'll I'll I'll keep moving forwards. And I want to scale this to team level and I want to talk about three different types of teams. One is the legacy team. This is a team that's not really using any AI, it's working in the old way, the pre-AI way. One is a high-performing team, this is a team that is AI enabled, it is using AI. And then I want to talk about the elite human AI teams. This is a team that's optimized to build ice sculptures. And again, you can screen grab that and you can look at the details, but I'm gonna uh spend some time across some different slides talking about these different teams. But the gist is the legacy teams are falling further behind every day because they're just trapped executing medium charge tasks, tasks that can be automated or semi-automated. The high performing teams who've been given AI tools or are using AI tools, they are doing more high charge work. But what we're seeing is, and big sets of compelling data are showing this, plus our own experience, is that that high charge work is fragmented because their brains are still not working as well as well as they would like them to be. Elite human AI teams, these are high-charge brain state machines, ice culture building machines. So let's go into the detail of the differences. Before we do that, let's just zoom out to a kind of a simpler way of thinking about this. In a way, we're all on a journey up a mountain. The top of the mountain is our goal. This could be your business goal, it could be your team's goal, it could be your family's goal, it could be your personal goals. And we're making our way up the mountain. But what's happened, I think especially since the COVID and all the things that have just seemed to happen since then, is that it's become harder and harder to make progress. And we've seen uh, you know, we've seen that with the fact that we've got over 20,000 people a month in the UK being signed off work with anxiety and depression. In the US, we've got 54 million adults with a mental health diagnosis. But being our best is more difficult than ever before. So let's use that to try to understand what I mean by legacy teams, high-performing teams, and elite human AI teams. So look, legacy teams are falling behind. We've just seen it block laying off 40% of the people. The where the traditional way teams have worked isn't working anymore because AI has just disrupted things. And what I want to do is plot these teams on a on a on a graph that is showing high value strategic work per hour per human hour. And there are two axes on this graph. The y-axis is optimization of strategic work, so at the top of that, you're 100% optimized at building ice sculptures. The x-axis at the bottom, that's automation of routine work using AI. So 100% there, you are completely automated. You've completely automated how your ice cube work gets done. So, where does a legacy team sit? Well, they're mainly doing um most of their ice cube freezing work manually, and this consumes all their time, so they just don't have the mental capacity to do the volume of strategic work they need to do. So that's where the legacy team is at. Next team, high-performing team. So they've been given AI tools, which are like their uh their sticks and their special uh boots they've got to help them to go up the mountain faster. And we're always going to get the odd person in the team that takes those tools and flies with them, but they're often the exception to the rule. So what we're seeing is that even if you, and again, this is our own experience plus big sets of data, even if you have AI tools, many people are finding that they're like a heavy uh backpack that is slowing them down. Because if you've got AI tools without brain state intelligence, it actually makes your life more difficult. So that's what we're seeing. And you again, we can see this playing out. So businesses, business leaders, of course, expect AI to improve performance of their teams. Yet most people in teams are saying they're actually decreasing their performance and they've got no clue how to make the gains that their bosses are expecting these tools should deliver. A big study from MIT came out, I think, um, around October time, showing that 95% of generative AI pilots at companies are failing. So these pilots are designed to make it easier for people to build ice sculptures faster, but people are using the AI in fragmented brain states, so they're not getting um the results they want, they're getting fragmented ice sculpture building work. This is a really interesting story. This is in the from the UK, and um essentially, West Midlands police were assessing whether a team called Maccabee Tel Aviv whether their fans should be allowed to attend a Champions League game that Maccabee were playing against Aston Villa, uh, Premier League football team. And the West Midlands Police deemed that it wasn't safe for the Maccabee fans to come because they were dangerous and they wouldn't be able to police them properly. One of the main pieces of evidence that the West Midlands police used to justify that decision was a game that Maccabee had played against West Ham United, where the Maccabee fans were out of control. It turns out that game never took place, it was a fictitious game that was generated by a human being using AI in a in what I would call a fractured high-charge brain state. So just because we give a team a team AI tools, it doesn't magically make them ice sculpture building machines. So if we plot the high performing teams on this uh graph, they are starting to automate more of their ice culture building work, but they still don't have the brain state intelligence or the the culture to support really optimized strategic um work. And I'll talk about specific numbers later, but that's where I would place them. So the final team then is what we call the elite human AI team. This is really important. This is this this sequence is really important. If you want to build elite human AI teams, first of all, you've got to help people to optimize their brain states. And secondly, then you've got to show them how to build AI into their workflows in an optimized way. When you do that, it's like giving your to each team member a snowmobile, and they can move up the mountain faster and further than you ever thought possible. But it's only possible with brain state intelligence. This is why brain state intelligence is so important. What we're seeing is that teams who've got optimized brain states and optimized use of AI is they're able to build eye sculptures three to five times faster. Because they're able to access those high-charge brain states much more consistently. Let me show you an example of someone that uh we supported to help them to do that. This is Eva, who is an attorney uh in New York.

Why AI Pilots Fail Without Brain States

SPEAKER_01 38:36

But what I was struggling with was identifying exactly what I needed to do every day, and to balance that everyday set of priorities consistently. Just even understanding that there's a whole neurochemical thing happening. That it's not you, it's not your motivation, it's your environment, the things that you are surrounding yourself with, your external factors are something you can control to work for you to promote that hormonal activity you need to switch your brain on. So just even knowing that that's not my fault that I feel gray and down and I don't want to do my work. It's my brain isn't getting what it needs, the brain food, the stimulation, the activity. Um, so yes, gaining that understanding is extremely liberating. The information in the book and in the program is extremely helpful to get you to where you need to go. Because a lot of us who are in this very high-level professional functionality, we're very cerebral people. And until we have a kind of aha moment in our minds, we're not going to subscribe to a theory or commit to a program or a new way of doing things. We're not going to bother to spend that one minute. And especially as an attorney, every minute is billable. So you are very, very careful about how you spend your time. But when you have this empowering knowledge that you can apply every day, um, it's very transformative and it takes away that self-hate that we so often bog ourselves down with, you know, like, oh, you're so lazy. You only got up at 5 a.m. You should have gotten up at 4 30. Okay, so when I first met Andrew, I was working on my laptop till 10, 11 every night and struggling to get up in the morning because I couldn't get my work done. Because of the program, it's very proactive. It's like go, and but it gives you the tools to make that very, very compact your day. I get out of the office before five, almost without fail, every day, which is the first time in my career that I have done that because I want to be home. And I'm I leave this is the best part. I leave my computer at the office. And on the weekends, I usually don't work. And so I would say to anybody who's thinking about this big looming problem of AI, yes, it is a very serious threat. That's the first thing to look at. But does it matter that much for me? And if it does, well, what am I gonna do to change how I handle this rather than this is a crushing pressure? And how can I adapt best to cope with this? So, in my practice area that I'm breaking into, trust and estates planning, I'm seeing that AI could actually be a massive advantage to me if I pivot and incorporate it into my practice and start to work with it. Um, and that's what I'm doing. I'm starting to see the advantage of getting those tools on board with my approach to make it more efficient.

Eva’s Story: Liberating Performance

Scaling Elite Human AI Teams

SPEAKER_03 41:38

Eva didn't stop there. So Eva essentially built her own human AI team herself, working with AI. And that's the place to start. Sure. So and Eva was working with our head of coach, Andrew Foster, but and it and still is, and she just messaged Andrew out of the blue saying, Oh, yeah, I just got a seven, I got a new job and a$70,000 pay rise. This was about six months ago, because the the new law firm recognized the value she could bring in actually understanding how to get the most out of these AI tools. Um, and the last time I heard she was uh uh studying for the bar exam in California. So this is an I that's an ice sculpture she's building, right? Because she's got more brain capacity to do that. And what we want to do is scale that advantage to the team, and that gives everybody the capacity to build ice cubes faster, three to times, three to five times faster. We see examples of these pro of of this all the time, but here's one from ourselves, you know, building our own human AI high-performing team, sorry, elite human elite human AI team. So we had a benchmark for how long it it takes to build for us to for us to create an audiobook, because we we we did one with the habit mechanic. And what we then very deliberately did when we wrote Train Your Brain for the Air Revolution is we wanted to apply this system, and we were able to create Train Your Brain for the Air Revolution, the audiobook. So think of this as an ice sculpture, 90% cheaper and 17 days faster than it took us for the habit mechanic. So this is absolutely real, but you've got to combine brain state intelligence with the AI together. You can't just give people AI tools and expect them to become, you know, super people. So if we plot elite human AI teams on here, they're automating most of their routine work and they are getting very close to optimizing the strategic density of their work. So if you look at that in numbers and notice here in the headcount um column that teams that are working with AI are smaller in headcount. So if you just take the Jack Dorsey, the block number, they're reduced if you know for every 10 people they employ, they've they're at least four of those people. So let's just say that right now, um human AI teams are maybe 40% smaller than. Um legacy teams. But if you look at the high performing AI-enabled team, there, and this is this is based on about 20,000 data points, and I'd say over 19 million hours of real-world data that we've been collecting over a long period of time, and that's been amplified by AI, they're maybe doing 15 hours, those six people, of ICE sculpture building work every day, but it's fragmented work. And often they're introducing errors into their workflows because they're not really in true high charge brain states. So big sets of data are showing that is that if the teams are not in the right brain states, they're introducing errors. Whereas the elite human AI team that's both AI enabled and brain state intelligent enabled is able to do double the amount of that high charge work in a day. So 30 hours of ice sculpture building work. This is where the competitive, the real competitive advantage in the AI era lives. It's not just bringing AI technologies in, it's forming elite human AI teams. So the question then becomes is how do we create this and how do we scale it in an organization? The logical solution is you say, well, okay, we need our people to be um thinking better. We need to give them psychological support. But here's the challenge: people have more access to tips, tricks, and hacks than ever. People have more, you know, easier access to talk therapy than ever. But these solutions are not helping people to do better. Um, by and large. If we look at the data, these are huge sets of data looking at CBT interventions, cognitive behavioral therapy, which is seen as the gold standard of uh psychology and coaching, gold standard of behavior change. It's only actually helping one in five people to do better. So that's the equivalent of every five people that break their arm and go to the hospital to get it fixed. That fix is only working for one in five of those people. And I'll explain why this is broken shortly. The other thing that businesses are default into is change management, digital transformation programs. Let's bring in a change framework, let's give AI training to people. But again, these are not working. I hear it every day from senior leaders that they're not these things are not working for them. But if we look at again big sets of data, they show that even before the AI era really kicked in, 70% of large-scale transformation initiatives failed to meet the expectations. And it's very clear why these things don't work, and they're working less well in the AI area because AI is just speeding up everything up and it's creating more overwhelm and it kind of speeds up problems and mistakes. Whether it's traditional uh coaching, psychology, change management, digital transformation, they're all designed with one simple premise. If you can get people to know what you want them to do, then they'll do it. Walk 10,000 steps a day, think more positively, use AI more often, do more strategic work. People nod and they go, Yeah, I'll definitely do that. We know that that isn't the case. People don't do what they know they should do or even agree they should do, they do what they're in the habit of doing. But the reason that these models are in play, the traditional coaching models, the traditional change models, is because they were designed before we actually understood how brains worked. And they're built on what we call black box models, often from the 60s and 70s. So they were designed without understanding how brains work. And the fact that brains are largely running on autopilot most of the time, which is why they're so powerful. So if we actually want to help people to do better, we've got to help them to not only know what to do, not only help them to practice doing it, but to help them to build new habits. And even that isn't enough. Because once we've started to help people to build new habits, we've got to make sure that the culture around them is supporting those new behaviors. And that means we've got to use cutting-edge insights from behavioral science. But again, the traditional approaches to change, whether it's individual level change or organizational level, they're just not using comprehensive behavior change models because they're drawing insights from academia and the things that are coming out of academia are very fragmented. Um, so that's why we created human high performance psychology. And our practical application of that is what we call the habit mechanic AI system. So the habit mechanic AI system is built on cutting-edge insights from neuroscience, from brain maturation science, from evolutionary science, from uh behavior change science, from what we call leadership and team performance science. And the whole goal is to help people to become individually and collectively more brain state intelligent. And we do that by helping people to understand how their brain works, like we've started on the session today, identify what we call their destructive habits, the habits that are stopping them managing their brain states really well, and then help them to build more um what we call brain state management habits. And there are six core habits that we show them how to build. Then we show them how to use behavioral science so they don't just know what they need to do, they can actually hardwire it into their brain so it has lasting impact. And we've been doing that um for the the period of history before Neural Network AI turned up. So this was a system that we crafted over about a 20-year period, but now we've also worked out how to use AI to supercharge this process. So, as I said right at the start, AI is just cheap brain power. So we can use AI to speed up our ability to change our own behavior, but also to change our team's behavior. So that's really exciting. And so the question then is how do we actually use this to move our teams from legacy teams and high-performing teams to become elite human AI teams? And this is where the new professions come in. So, to do this, you're not going to do it with a workshop or a coaching session. You've got to build what I call human AI performance architecture into your organization. And the whole purpose of that human AI performance architecture has to be to create what we call a habit mechanic AI edge culture. And we do it in three core steps. One is we've got to help C-suite to understand this, and we've got to help them to become what we call chief habit mechanics. Then we've got to embed this at a team level to support our teams becoming elite human AI teams. And then we've got to embed this at the individual level as well to empower our people to become what we call habit mechanics. So we've got three core rules that are emerging that support each of those three steps. So, number one, businesses are now starting to look for human AI performance advisors. So leadership teams are looking for guides to help them to build elite human AI organizations because they're realizing that just buying the tech isn't enough. And that's the work that we're doing with businesses, but it's also the work that we're training others to do. So we're training people to become certified human AI performance advisors. And we're just simply showing them how to use our nine action factor system to help C-suite build cultures, make it really easy for people to get into high-charge brain states more consistently so they can build new, more new um i sculptures faster. The second professional role that's emerging is businesses are looking for coaches to help them to build elite human AI teams. So not traditional uh team and leadership coaching, human AI, team and leadership coaching. So again, we're starting to support businesses to do this, but we're also training and certifying other coaches or people that want to become coaches, so that they can actually help teams and their leaders to move from high-performing teams to elite human AI teams. And the core method that we use to do that is our elite human AI team, uh team power five-stage model. So that's a professional career opportunity. And then the third one is that businesses need coaches that can help individuals become what we call habit mechanics, as I've explained. So again, we're doing this work with businesses, but we're also training people to become certified habit mechanic coaches. Um, we've trained up about 50 of these so far, and they're helping people to embed what we call the six habits of high-performing A era professionals into their brain, essentially, so that they automate um brain state intelligence and uh brain step management. And to do that, they use our simple four-step AI success cycle. So as AI transforms the world of work, then these professional opportunities are emerging. So I'm not trying to sell you anything on this call, I'm just trying to make you aware of these opportunities. But if you're a business and you think, yeah, we need some of this support, then we're happy to have a conversation. And I'll show you how we can do that shortly. Or if you're a coach or a consultant or an advisor, or you'd like to become a coach or consultant or advisor, and you're interested in any of these three training programs, then we're happy to explain more about those as well on a call. So that's the opportunity. I hope you're as excited as I am about this. Um I think that the next period of history, we're going to see more changes to professional work life, especially you know, in white collar work where people are sitting at computers every day than we've ever seen before. So individuals, teams, organizations, they need help. And this is the the proven way of supporting people.