17 Feb 2026 · 31m · Don Tapscott, Adi Ignatius, Alison Beard · 22 quoted facts
Don Tapscott argues that the next stage of AI is 'identic AI': personal agents trained on your own work, judgment and values that act on your behalf. He says this goes beyond efficiency and will change how people work, how firms are built and what managers are for, because execution becomes cheap and judgment becomes the scarce skill.
The central tension is power versus control. Tapscott describes agents as a near-infinite team of expert assistants, while the hosts worry about errors, lost jobs and dulled thinking. His answer is checks and balances, new management practices, and above all ownership: he insists these agents must be self-sovereign, owned by individuals and not by big platforms.
Tapscott says agents can handle coordination, analysis and scheduling at machine speed. That undercuts the old idea that execution is strategy, and shifts managers toward choosing goals, defining purpose and supervising direction.
Citing Peter Drucker, Tapscott says hierarchy existed to relay faint information signals. When agents surface insights in real time, the information reason for layers of management disappears, and many such jobs will go.
Drawing on Ronald Coase, he says firms exist because of transaction costs such as search and coordination. Agents and blockchain-style smart contracts push those costs down, which could allow new organizational models like DAOs.
Tapscott warns that if a platform owns your agent, it could place products, ideas or political views inside your extended intelligence. He argues for self-sovereign agents, and for letting employees keep personal patterns while leaving company data behind.
He compares delegating to agents with signing authorities and checks and balances for people. Training, review cycles, accountability and values-setting for agents become core management work, and leaders should use an agent in real work to learn it.
Tapscott uses the term for personal AI agents that learn who you are, reflect your values and act as extensions of you. He treats them as a subset of agentic AI, which is AI that can pursue goals and manage tasks without being prompted each time.
Tapscott says everything he described is available and in use now, with platforms rolling out capabilities at different levels. He says he has built a 'digital Don' by feeding it about 500 of his documents.
Tapscott says a lot of management jobs will disappear, and already are, because agents remove the need for layers that relay information. He says the role shifts toward judgment, governance and accountability, and that people will still report to people, not to agents.
Tapscott argues that you should, not a big tech company, because the agent is an extension of your own intelligence. He fears platforms could use it for their own purposes, such as placing products, ideas or political views.
Tapscott says to get knowledgeable, build and use an agent in real work rather than as a demo, and map which roles will be amplified or squeezed. He also recommends rethinking HR functions such as recruiting, training and performance evaluation.
Stated by the speakers. Each quote matches the transcript, which shows what was said, not that it is true.
Don Tapscott is CEO of the Tapscott Group and author of the book You to the Power of Two, Redefining Human Potential in the Age of Identic AI.
“is CEO of the Tapscott Group and author of the new book, You to the Power of Two, Redefining Human Potential in the Age of identic AI.”
Don Tapscott describes the first phase of modern generative AI as AI that could generate content such as text, data and graphics, used as a tool.
“AI has really gone through three phases modern generative AI. The first was gen AI, where AI could generate content with amazing capability text, data, graphics, all kinds of stuff.”
Don Tapscott says the second phase of AI gave agents the ability to manage tasks and pursue goals without being prompted.
“Then AI went through a second phase where it acquired some agency, where agents could act, and they could manage tasks, they could pursue goals without prompting it with questions or requests.”
Peter Diamandis, founder of XPRIZE, told Tapscott and his co-author that his AI agent Peterbot is like having an infinite number of vice presidents.
“as Peter, uh, Diamantis, the founder of XPRIZE, said to us in an interview, he's got Peterbot, and it's like having an infinite number of vice presidents.”
Adi Ignatius says many people have interacted with Reid Hoffman's Reid AI, which he describes as possibly a digital clone.
“A lot of people have interacted with Reid Hoffman's, you know, Reid AI, which is, uh, I don't know if the term is a digital clone.”
Don Tapscott says he fed about 500 documents of his own writing, speeches and interviews into his personal AI agent, 'digital Don'.
“I've input about 500 documents, everything I could find that I've written, my speeches, my PowerPoints, my, you know, books and articles and interviews and all kinds of stuff like that.”
Don Tapscott says Claude is currently one of the leading platforms offering a capability to build your own agent.
“Claude right now is one of the leaders, Claude, excuse. It's got a capability to build your own agent.”
Larry Bossidy and Ram Charan famously argued that execution is strategy, a point Tapscott says breaks down in an era of identic AI.
“you were editor of HBR when Larry Bossidy and Ram Shankarm famously argued that execution is strategy.”
Don Tapscott recalls Peter Drucker describing middle management as the boosters of the faint signals that passed for communication before the information age.
“Drucker, the founder of management science, uh, referred to middle management as the boosters of the faint signals that pass for communication in the pre-information organization.”
Don Tapscott says his 1994 book The Digital Economy was the first big book about the web.
“I don't know if you remember, but in 94, in the digital economy, it was the, I guess, the first big book about the web.”
Ronald Coase won a Nobel Prize for explaining that firms exist because of transaction costs, including the costs of search and coordination.
“and he won a Nobel Prize for saying this, the answer is transaction costs. He defined these broadly, the cost of search, of finding all the right people to do something, the cost of coordination.”
Don Tapscott says blockchain produced decentralized autonomous organizations (DAOs), which often lack traditional management and use tokens as incentives.
“the DAO, the decentralized autonomous organization. In many cases, they're organizations without a traditional management structure, and that use tokens as mechanisms for incentive rather than the traditional command and control.”
Don Tapscott explains that DAOs run on smart contracts, which are agreements between people made in software.
“these DAOs function on something called a smart contract, which is basically a contract, an agreement between people made in software.”
Don Tapscott says AI engineer Harper Carroll is chief engineer at a company that was sold to OpenAI.
“There's a AI engineer named Harper Carroll, the chief engineer at a company that was sold to OpenAI.”
Citing Harper Carroll's framing, Don Tapscott says that when an employee leaves, their agent could keep personal patterns and skills but lose the company's proprietary data.
“The agent retains the patterns and skills and the knowledge about the individual, but it loses the proprietary data that's unique to the company.”
Don Tapscott argues that identic AI must be self-sovereign, owned by individuals and not by technology companies.
“We argue strongly that no, identic AI needs to be self-sovereign. We need to own our own super intelligence.”
Don Tapscott names Mark Zuckerberg and Google as examples of parties he does not want to own people's personal AI agents.
“the biggest question for me is who's going to own digital Audi? Mark Zuckerberg? Google?”
Don Tapscott says building self-sovereign identic AI would require reinventing the AI stack, which he believes is feasible technically, socially and economically.
“that means a modest little undertaking reinventing the AI stack. And we think that that's feasible technically, and it's achievable socially and and economically.”
Don Tapscott says hearing Joan Osborne's song 'What If God Were One of Us' led him to think about living in a world where humans are not the apex intelligence.
“What if God were one of us? Remember, that was, uh, Joan Osborne.”
Don Tapscott says that during the internet era people outsourced the storage of information to the web, whereas AI now lets them outsource thinking.
“During the period of the internet, we outsourced storage of information to the web.”
Don Tapscott recalls Peter Drucker saying stable times need good management while times of change need good leadership.
“he talked about in times of stability, you need good management, and in times of change, you need good leadership.”
Don Tapscott says he planned a speech with himself on one screen and his AI agent 'digital Don' on another to help answer questions.
“I'll be giving a speech in a week where there's going to be me on this one screen and digital Don on the other screen”
Tapscott defines identic AI as the third phase, after generative AI and task-doing agents, focused on personal agents that reflect their owner.
“the agents that really matter are the personal agents, the rise of intelligent companions”
A concrete picture of what a personal agent does for a manager before and during the workday.
“it's like having an infinite number of vice presidents”
Tapscott says the capabilities are already available, citing his own 'digital Don' built on his writing.
“everything I described is available and it's in use.”
If agents handle execution, the advantage moves to strategy, purpose and judgment.
“Execution increasingly becomes commoditized.”
Delegating decisions to agents requires the same kind of checks and balances as delegating to people, plus new practices like agent review cycles.
“You're potentially delegating to an infinite number of vice presidents who have an IQ of a thousand.”
Tapscott asks whether outsourcing thinking makes us lazy or deepens it, and says learning should build capabilities like critical thinking.
“now we're not just outsourcing storage, we're outsourcing thinking”
Using Drucker, Tapscott argues agents remove the information role of hierarchy, forcing managers into judgment and governance.
“Middle management didn't fail, it's just that its job has kind of disappeared”
AI and blockchain cut search and coordination costs, which could produce radically new organizations.
“the answer is transaction costs”
Tapscott makes self-sovereign ownership the central issue and discusses what an employee's agent keeps after leaving a company.
“We need to own our own super intelligence.”
Practical advice: learn the technology, use an agent in real work, map uneven impacts and redesign HR.
“Develop an agent, not as a demo, but in real work.”
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I'm Adi Ignatius.
I'm Allison Beard, and this is the HBR IdeaCast.
All right, so we are back again this week to the topic of AI. One of the things that I find most interesting about AI is that despite its huge potential, there's no blueprint for how to use it, right? So we're all essentially pioneers experimenting with this powerful technology to figure out how it can help us.
Yeah, I'm constantly hearing from colleagues, guests on this show, other contacts about how they're using AI in really new and creative ways. And I think, gosh, I should really try that. But at this point, I'm using it for writing article summaries that we need to do for the magazine and hbr dot org. And honestly, feedback on which colleges my daughter should apply to. But I know that I could use it for so much more if I just put the work in to better understand it and train it.
I think the breakthrough AI opportunity is still slightly ahead of us, or slightly ahead of most of us. And that is the widespread introduction of AI companions that we'll have at our disposal at work and home that are trained by us, that know everything we know, and that can take action on our behalf across a range of activities.
Okay, so now that's beginning to sound a little bit creepy. I don't know that I'm willing to give an AI companion that much control over my life.
Yeah, look, that's a fair point, and I think a lot of people share that. I do think it's coming, and I think it'll be hard to resist. Our guest today, Don Tapscott, will talk about what he calls identic AI. Tapscott, who's been spotting future trends in the tech space for decades, is CEO of the Tapscott Group and author of the new book, You to the Power of Two, Redefining Human Potential in the Age of identic AI.
Here's my conversation with Don. Now I want to make sure we're grounded in this conversation. So most of our listeners are probably comfortable using AI in their work and personal lives. They may or may not be experimenting with AI agents to handle certain tasks. Your book is projecting us forward, though, to a not mostly not yet available technology that you're calling identic AI. Talk about what that is.
Well, AI has really gone through three phases modern generative AI. The first was gen AI, where AI could generate content with amazing capability text, data, graphics, all kinds of stuff. We used it as a tool. Then AI went through a second phase where it acquired some agency, where agents could act, and they could manage tasks, they could pursue goals without prompting it with questions or requests. They're all kinds of agents. They're agents in supply chains and call centers, financial systems and so on.
But our view is that the agents that really matter are the personal agents, the rise of intelligent companions that really learn who we are and they reflect our values and ultimately operate as extensions of ourselves. So the shift is that AI is no longer just an extraordinary technology, it's becoming part of the human experience, and we call these personal agents a subset of agentic AI. We call them identic AI.
Why do business leaders need to understand what you're calling identic AI right now?
Well, if identic AI is going to change everything about the human experience, it's going to have huge implications for the enterprise and for management. A way of thinking about it is this is how we started the book, thanks to the Beatles. Uh, you wake up, you get out of bed, you drag a comb across your head. And before you've engaged with the day, before you've gone gone downstairs to take a cup, as the Beatles say, your agent's already figured out what's going on.
It's summarized your health data, checked your schedule, it's flagged a traffic delay, it's curated and summarized the news, picked some articles that you actually care about. It reminded you of your sister's birthday. It outlines several conferences that you will attend on your behalf. And by the time you reach the office, your agent has, you know, it's not just an assistant updating your agenda and so on. It's drafted replies to emails. It's optimized production schedule, it's tackled some customer complaints.
And as Peter, uh, Diamantis, the founder of XPRIZE, said to us in an interview, he's got Peterbot, and it's like having an infinite number of vice presidents. And so this thing is going to act as your concierge, your doctor, that's been to every medical school in the world, your tutor, that's literally a know-it-all, your planner, your counselor. But more than that, it's going to learn your values, it's going to anticipate your needs, really propelling your capabilities forward.
This is not sci-fi. This is happening right now, and all the main technology companies have geared up to be delivering this technology right now. And I'll be giving a speech in a week where there's going to be me on this one screen and digital Don on the other screen, and he's going to help me answer questions. I'm pretty good at answering questions, but I don't know what I wrote on page 232 of, you know, the digital economy in 1994.
Maybe somebody wants to know about that. So it means for the manager that you have a superpower now, and this will change literally everything about the deep structure and architecture of the firm, about the way that people operate. There's a huge shift from execution now to strategy, because this technology does the execution, HR, and everything that we know about that is about to change. So, uh, buckle up.
I want to go step by step here. So, you know, as you said, this already exists, so I'm familiar. A lot of people have interacted with Reid Hoffman's, you know, Reid AI, which is, uh, I don't know if the term is a digital clone. I think that's more just so that we can all experience it rather than necessarily a tool for the future. But there are people, as you mentioned, who are creating digital twins, or, you know, identical AIs, whatever you call it.
But I I want to get a sense to what extent, because I think when you listed all the things this can do, it probably sounded sci-fi to most people. What exists right now? To what extent is everything you described already available and in use?
everything I described is available and it's in use. You can look to any one of the platforms and they're rolling out their capability at different levels. You know, Claude right now is one of the leaders, Claude, excuse. It's got a capability to build your own agent. And the important thing here is that rather than using a bunch of tools, these are all coming together to have persistent memory and to get to know about you and to reflect your goals.
And as you build them up, they become an extension of you. So for Digital Dawn, for example, I've input about 500 documents, everything I could find that I've written, my speeches, my PowerPoints, my, you know, books and articles and interviews and all kinds of stuff like that. And it's learning about me and how I view things and how I think about things. I don't know if I'd describe it as a superpower yet, but wow, I'm a lot more capable than I was six months ago.
So what does this look like in, say, five years for a white-collar executive? What is the human doing? What is the identical doing in five years? You know, your your best guess.
I think that we'll spend a lot less time in execution related activities. You remember, I think, uh, you were editor of HBR when Larry Bossidy and Ram Shankarm famously argued that execution is strategy. In an era of identic AI, that equation really breaks because AI agents can handle coordination, analysis, scheduling, flow through, all the other stuff about execution. They can do that at machine speed. Execution increasingly becomes commoditized. And so as a manager and executive, what differentiates a firm is no longer your ability to execute, but your ability to think big picture, to choose the right goals, to define purpose, to make high quality strategic judgments and and so on.
Now, this has been going on for some time, but it's being supercharged now with identic AI. You know, management shifts from supervising work to supervising direction.
For this to have maximum value, it sounds like, you know, these identical AIs will have far more power to make decisions and complicated decisions that really multiply the number of Dons who are out there, you know, or AUDIs interacting with people making decisions. And that sounds great in terms of efficiency. It also, at least at this stage, seems scary. You know, what if it makes a decision that actually is a misinterpretation of what I had wanted or what my company wants?
Are we gonna get to a point where we're truly gonna let AI make complicated decisions valued at millions of dollars that affect Well, us, that affect our companies? And do we need to worry about checking or or is it gonna be fine?
well, no, it's not gonna be fine. It's really delegation. It's a good question. We've always delegated certain things to other people, including making decisions. We have signing authorities and so on, but we have checks and balances and and ways of ensuring that good decisions get made. The same is true for an agent, only you're not delegating to someone who's newer in the workforce or who's a subordinate or something like that. You're potentially delegating to an infinite number of vice presidents who have an IQ of a thousand.
What could go wrong?
Well, I don't know. I think if someone's got an IQ of a thousand, as opposed to, you know, 115, chances are they're gonna make some good decisions as long as you train them and equip them, and as long as there are checks and balances.
What does training mean then? Because I think anybody listening to this is going to think, Okay, I see the potential, I see the risk, I see the ethical considerations and risk. So what does training mean? How do we how do we make sure the parameters are such that this is doing what we want and will not do what we do not want?
You're not just training an individual, you're training your agent, and it's the same. You're not just hiring an individual, you're hiring someone with a capability. So what are you going to look at? Their resume, their experience? Well, maybe someone with a highly developed agent who's new in the workforce can perform better than a seasoned executive. The management of our agents, not just their training, but their review cycle, their accountability systems, their overall directions, their shaping, equipping them with the values that you and your organization care about.
These are going to become new, powerful, critical, central elements of management that just don't exist today.
I find more and more companies are hiring for critical thinking, for agility, for adaptability. You know, the same is true with education, but within companies, how do you make sure you maintain your own agency for one, but also how do you keep your skills sharp as you hand off more and more decision making to AI? Is this going to make leaders lazier or somehow keeping them sharp? And this may be a question of faith rather than evidence at this point.
So let's step back a sec. During the period of the internet, we outsourced storage of information to the web. You know, you didn't have to remember the name of that street, cause you could look it up on GPS or that date. Well, now we're not just outsourcing storage, we're outsourcing thinking. So am I going to think about this? Or am I going to let my agent think about it? So does that make us lazy thinkers, or does it radically enhance our capacity to think much more deeply as we interact with this powerful thinker to come up with something that's even better?
And you use the word skills. I'm not sure that's a good word. Now. This also gets into a whole chapter that we wrote. What do we do with the education system? And what does lifelong learning look like? You know, I remember my dad graduated, he had a career, he was set for life. Well, now, young people coming into the workforce today are set for 15 minutes. And you've got this superpower that's going to help you learn throughout your life.
So the purpose of education and of learning is not really the development of skills, in my mind, it's the development of these underlying capabilities, like critical thinking, having good BS detectors, because Lord knows there's so much BS, and that's about to increase exponentially. You know what is true and what is not, the ability to collaborate, to see the big picture, to see the interrelationship between things, your passion for not getting lazy and for doing research and learning lifelong.
These are the kinds of capabilities that we need to develop in order to be able to manage having a superpower.
So it changes in many ways the concept of management, or certainly middle management, where, you know, there are people who have had fantastic careers executing, as you say, which is less and less important, and executing efficiently. That's sort of what they do. And if you tell them, no, no, no, the the bot can do this and you should think deeper, I'm sure a lot of people are like, Okay, what? What am I supposed to be deeply thinking about?
So I I feel like this changes management, it probably changes the the very nature of the corporation, how we're structured, how we how we manage one another. This is a big deal. And as you sort of hinted, we have to adapt the educational system, finally, to keep pace with with all these changes.
Well, let's take those two, okay, management and middle management, and what does it mean to the architecture of the firm? You remember Drucker, the founder of management science, uh, referred to middle management as the boosters of the faint signals that pass for communication in the pre-information organization. That notion was built into the concept of hierarchy, that hierarchy existed to collect, to amplify, and to relay all these signals. Well, identic AI eliminates these signals, and information becomes direct, continuous, it becomes contextual.
When individuals and teams have agents that surface relevant insights in in real time, the information rationale for layers of management disappears. So I don't think it means that management disappears altogether, although a lot of management jobs will, and already are. It means that the role changes. It's, again, less about supervision and coordination and more about judgment, about governance, about accountability, but also about harnessing the superpower to contribute to value creation in the firm. And so, you know, this is a whole new area of management thinking.
You know, you think about management science. We've got these, uh, publications, and we've got, I don't know, hundreds, probably thousands of business schools and millions of books. And this whole discipline that we've developed is based on the concept that we have these human beings that work within a firm that has boundaries and structures and so on. Well, I think all of that is about to be turned on its head. Middle management didn't fail, it's just that its job has kind of disappeared, so it's got to do some rethinking.
I mean, the implication I would think is that many, many jobs are going to be eliminated. Like, you may decide, Don Tapscott is my best employee, and he is, you know, creating a digital twin or or identic AI, and he will manage that, and it will be amazing. We'll get him, you know, to some exponential power. But a lot of the people who would have executed on that are redundant, are no longer necessary. I I can't really imagine an alternative to what I just described.
I don't know if you remember, but in 94, in the digital economy, it was the, I guess, the first big book about the web. I was wondering, is there an economist that can help us understand all this? And I came across the work of Ronald Coase, who wrote a paper, I don't know, 80 years ago, and he asked a deceptively simple question. He said, Why does a firm exist? If Adam Smith is right and the market is the best mechanism for organizing people and resources and money and information, why isn't everybody an independent contractor at every step along the way in production?
And he said, The answer is, and he won a Nobel Prize for saying this, the answer is transaction costs. He defined these broadly, the cost of search, of finding all the right people to do something, the cost of coordination. Imagine getting all these people together to create a a microphone they'd never met and so on. The cost of overall of of building trust, of search, of basically transaction costs. So he said, well, we bring these inside the boundaries of a firm because the costs are lower there.
Well, we had these different waves of technology. First was IT, and the boundaries of the corporation came more porous, and then there was the rise of the internet, but the the core structure of the firm has remained somewhat stable today. Well, now you've got AI coming in. Think about the implications of AI and related technologies like blockchain on search, finding the right people, the right information, the right designs and so on, the cost of coordination. Well, you have these agents that are now working together to do things.
So I think that these transaction costs are being devastated in an open market. And so we're going to see radical new models of the firm emerge. Now, blockchain brought about some of these, the DAO, the decentralized autonomous organization. In many cases, they're organizations without a traditional management structure, and that use tokens as mechanisms for incentive rather than the traditional command and control. But you add in AI, and the and the reason that becomes important is these DAOs function on something called a smart contract, which is basically a contract, an agreement between people made in software.
Well, now, think of what AI does to the smart part of that smart contract. So I think we're into a period where we're finally going to start to see radical new models of how we orchestrate capability in society to innovate, to create goods and services, and to create value.
So one of the many unresolved questions in this for this future is who owns the AI, right? If I have an identic AI working for me at Harvard Business View, you know, what happens when I leave to go somewhere else? Can I take identical Audi with me? You know? So this reinvents the concept of the very person. What are the rights and responsibilities that we need, that we have, you know, what do we need to work out as these become commonplace?
I mean, I know this is not resolved yet, but is it clear to you what needs to happen?
the biggest question for me is who's going to own digital Audi? Mark Zuckerberg? Google? This is an extension of you and your intelligence, and if they own it, that's a big problem. You just think about something like product placement. You're watching a movie right now and it's got a Coke or something in it, and there's a subliminal impact. Well, imagine if you can place that in your extended intelligence. Or forget about a product. How about placing an idea or a political point of view?
We argue strongly that no, identic AI needs to be self-sovereign. We need to own our own super intelligence. So how does that work for a corporation? When someone leaves, what do they take with them? There's a AI engineer named Harper Carroll, the chief engineer at a company that was sold to OpenAI. And she has some very useful framing that when an employee leaves a company, they lose access to internal systems today, but they don't lose the knowledge and judgment they've developed.
And the same principle could apply to identical agents. The agent retains the patterns and skills and the knowledge about the individual, but it loses the proprietary data that's unique to the company. And that distinction between personal cognitive development and institutional knowledge, which kind of exists today, is where future management frameworks need to land.
So how do we cope with some of the more fearsome elements? You know, it's not hard to get to a very dark place, right, where AI is overruling, you know, mere human notions of what the technology should do. I don't think it's fanciful to imagine the dark side, where there are really bad consequences because we have not anticipated or we've not created guardrails. What do we do about that? I I feel like we're moving so quickly and there's resistance to having a conversation before we hurtle forward that we might end up in a bad place.
H- Uh, you know, in this context, how do you think about the risks?
My view is the future is not something to be predicted, it's something to be achieved. We're building a movement, really, with this book for self-sovereign identic AI. And as an aside, that means a modest little undertaking reinventing the AI stack. And we think that that's feasible technically, and it's achievable socially and and economically. But I'll tell you, I was sitting here one night, kind of just musing about stuff, and I had some music going on in the background, and this song came on.
What if God were one of us? Remember, that was, uh, Joan Osborne. And I started thinking about living in a world where we are not the apex intelligence. So if these agents become so powerful that they become an apex intelligence, then what does that mean? And if these agents align with us, or if they reflect our values, our best selves, then we can evolve into capabilities almost that are, uh, godlike. You know, we'll see further, we'll act faster, we'll remember more accurately.
But if they become independent, and as we can see a little hint of that in these social networks that are appearing, if they're capable of setting their own goals, they, you know, may cease to represent us and begin to transcend us. The point is that what, and I'm reinforcing what you're saying, that rather than something that becomes the divine, it becomes something that could truly be demonic. How are we going to deal with that? And this is not just the issue of super intelligence that everyone worries about.
It's a new issue that we've not come to grips with. Who's going to control that capability? And I want to control digital Don, I want to control the extension of me, I want to own it, and I don't want some platform using it for their purposes rather than mine. So we each need to become aware of what's at stake here, and the question of sovereignty becomes the central issue of our time.
How does leadership need to evolve? You know, we're still essentially managing people. Yes, there are agents here and there, but we're essentially, I don't think very many people have agents as bosses yet. We're going to go from the standard paradigm to, you know, leadership, as, you know, orchestrating these human and AI systems, having, probably, you know, AI as your boss, AI as your your charge. How do we even think about evolving leadership into this unusual new world?
Well, I think leadership is the right term, and again, to go back to Drucker, you know, he talked about in times of stability, you need good management, and in times of change, you need good leadership. And the characteristics of a good manager and a good leader, as we know, are very different. But I don't think you're going to be managed or led for or report to agents. You will report to people who have a superpower. You will have people reporting to you who also have an extraordinary capability as well.
So we still have individuals working with and for individuals. It's just that their capability is being enhanced, well, almost infinitely, in theory, at least.
So if somebody's listening to this and thinks, you know what, I don't know if I like it or I don't like it, but it feels like this is inevitable. It's the next step toward this ever more capable AI that can create efficiencies that can help in our work. How do they get from here to there? How do they start to experiment with, let's say, these identical agents, these very skilled agents, to try to make that part of the workforce, part of what their company can do?
Well, the first thing is to get knowledgeable. You know, it's happened to me a few times in my life where I thought, Wow, this thing is huge and nobody knows anything about it. And I got lucky enough to write the first big book about it. Well, nobody really knows much about identic AI. We still have this view of AI as tools or AI as agents that are out there sort of doing things, but you need to get knowledgeable.
I would spend every waking moment learning about this, trying to understand it. And then, secondly, and I've always said this over the years, you need to use it yourself. I said this about, you know, in the 80s, when they said every manager is going to use a computer, you should try and use it with your own fingers, not your secretary's fingers. You know, same with the web, same with social media. Develop an agent, not as a demo, but in real work.
If you don't know what it feels like to delegate cognition to an agent, you're going to learn. And in doing so, you can govern it responsibly for others. You need to map where augmentation will be uneven. You know which roles are going to be amplified, which will be compressed, which will shift towards supervising agents, managing expectations. And we need to start to think about the redesign of management and work so that people aren't competing against their own tools.
If you like, I would start to rethink as a manager every different part of an organization, starting with HR, you know, the recruiting, training, compensation, performance evaluation and so on. Just go through all of those, and we talk about these in the book and how these will change radically. If I were a manager listening to this, you know, the fastest way to lose control and a lot of people will, or to lose their relevance and lose control to identic AI is to ignore it.
It's time to get up to speed.
Don, this is all fascinating. Thank you very much for being our guest on the HBR IdeaCast.
Well, it's great to chat with you again.
That was Don Tapscott, author of the book You to the Power of Two, Redefining Human Potential in the Age of identic AI. Next week, Allison learns more about the power of positive intent and what that means for businesses. If you found this episode helpful, share it with a colleague and be sure to subscribe and rate IdeaCast in Apple Podcasts, Spotify, or wherever you listen. If you want to help leaders move the world forward, please consider subscribing to Harvard Business Review.
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