In this lecture, Scott D. Anthony explores how generative AI and a cascade of macro‑economic shocks—most notably the 2025 tariff policy shift—are reshaping the way knowledge is created, taught, and applied. He begins with a classroom experiment, questioning whether AI‑generated essays reflect true learning and describing alternative assessment methods that require students to demonstrate their process and understanding. He then frames the current era as a massive “unfreeze” in Kurt Lewin’s change model, arguing that the pandemic‑induced supply‑chain fragility and the new tariff regime together constitute a prolonged, climate‑change‑like disruption that forces organizations to rethink proximity, redundancy, and flexibility. Drawing on his dual‑transformation framework, Anthony explains that firms must simultaneously (Transformation A) reinforce their existing business against disruption and (Transformation B) build a strategically related new growth engine, linked by unique capabilities. He illustrates this with a case study of a major law firm confronting an “information‑action paradox” – the tension between abundant freedom with little data and abundant data with no freedom – and outlines three leadership crises (commitment, conflict, identity) that arise during such change. Throughout, he uses the historical analogy of Gutenberg’s press to show how new technology (AI) can empower both incumbents and challengers, emphasizing the need for active experimentation with AI teammates, awareness of their strengths and hallucination risks, and the importance of team‑based learning. The talk concludes with practical guidance for leaders: seek weak signals, act before data fully validates, maintain a clear purpose and vision, and communicate relentlessly to navigate the intertwined crises of disruptive change.
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TranscriptAuto-generated · 12 min
There's this new technology that you probably heard of called generative AI, large language models from ChatGPT and Anthropic and so on, that really changes the way you think about transmitting knowledge, producing knowledge, consuming knowledge, teaching, assessing, and so on. I teach a class called Leading Disruptive Change. Historically, at the end of class, I would have students write an essay. Take what we learned in class, apply it to a company of your choice. Over the last couple years, I've noticed the quality of those essays has gotten better and better. No surprise, students are using the best available tools to produce the best prose that they can really quickly. The question is though, are they actually learning anything? I've begun to experiment with new approaches. Last year, I tried out a couple times where I would interview students At the end of class, sit down with them for 30 minutes, quiz them, see what they actually could retain, or give them a chance to lean into AI, giving them this as an assignment: use AI to create an innovative way to teach a leader of your choosing a concept from the class. Show me all the work that you've done so I can see through the guts of your mechanics of working with AI whether you've learned something or not. I'm not sure this is the answer, but these are the things that we are wrestling with How do you think about teaching and assessing in a world that is being fundamentally changed? We're grappling with, at our school, the same forces the world is grappling with. Now, is this good or is this bad? The answer, of course, is some of both. In the 1940s, the psychologist Kurt Lewin put forward one of the first models of organizational change. It's a really simple model. He says at any given moment, An organization is frozen. Change is next to impossible. Something happens to lead to that organization unfreezing. Maybe it's a charismatic leader, maybe it's a great shock, whatever. In the unfrozen state, change is possible, but you gotta move with pace because the 3rd phase is the organization refreezing. The window to change is temporary. When it refreezes, change is once again impossible. For better or worse, you can argue that right now we're in the middle of the great unfreezing, where things that were facts turned out to be assumptions, where things that appear to be impossible are things that you can actually go and try. That is really bad for some, no doubt about it, but it also creates a once-in-a-lifetime opportunity to reimagine everything. I want to focus on changes in tariff policy. Now, I'm not an expert in all tariff policy, and I'm not going to be able to tell you that the government is going to do this or going to do that. I have no idea what they're going to do. What I am an expert in is how do you navigate disruptive change. So let me apply some of the things that I see from organizations dealing with broad disruptive shocks to think about how you think through tariff changes. First, I think it is important to recognize that while we have a shock that has happened in 2025, this is the latest in a series of things that goes back a number of years. You go back to the COVID pandemic and it exposed fragility in global supply chains that made very clear to many leaders that the way they had done things for decades needed to change in some way. That meant things needed to move closer in some cases. It meant creating redundancy in supply chains so you build in more flexibility. It meant really rethinking what they were doing. As you then deal with the present shock of big changes in tariff policy, one of the big questions for leaders to ask is, is this an event that's temporary that won't last for too long, or is this climate change where we're in a new environment where this will be the reality of what we have to operate? Again, I don't know the answer to this, but there's plenty of signs to suggest that it's more like climate change, where there is agreement both among Democrats and Republicans that the U.S. needs more, not less production happening in the United States. The U.S. needs more, not less supply chains being moved closer to the United States, and companies based in the U.S. need more, not less flexibility and adaptability in what they do. Exactly what impact that will have depends on your industry, depends on your locus of activities. But I think being prepared for this being something that's longer lasting versus shorter lasting is really important. My 2 careers are consulting and academia. These are 2 fields that really in essence deal with ideas, 2 fields that are right now being fundamentally reshaped by generative AI. I can't help but reflecting as I think particularly about consulting, about something that took place about 600 years ago. It was a disruptive technology, Gutenberg's printing press. An early customer of that disruptive technology was the Catholic Church. No surprise. The Catholic Church was a dominant force. One challenge it had was that producing new Bibles took a long period of time because you had to get an expert scribe that would handwrite a more than 1,000-page document. So the printing press, it looks like a gift from— pardon the pun— God, because it allows you to go and produce more Bibles more quickly. So the Catholic Church is fired up about the technology until it turns out that not only does it help to produce more Bibles, it helps Martin Luther, who's got very different views about religion, to go and produce and share and disseminate that information more rapidly than he ever could before. The Reformation split the church, led to numerous conflicts, and fundamentally changed Europe and indeed the world. The Catholic Church ultimately ruined an invention that it helped to hasten by making investments in it. You have a new teammate. That teammate is your large language model of choice. Your new teammate is amazing. They can do some things at amazing speed. They can produce great written documents. They can synthesize information like that. They don't get tired. They almost never complain. Your new teammate has some limitations. Sometimes they'll just make stuff up. It will look like it's really right, but it actually is quite wrong. So what do you do when you have a new teamwork? How do you figure out its strengths and weaknesses? Well, you go and do things with that teammate. You iterate with them. You work closely with them to figure out what their capabilities are, what their liabilities are. You can't just outsource things to them because number one, you can't then figure out what they've done that's right and what they've done that's wrong. And number two, you don't learn anything yourself. The struggle is the learning. You have to remember that. Finally, as you think about all this, remember all the research shows clearly life is better when we work in teams. The research also shows clearly life is even better when we work in teams with AI. So you have this new powerful companion that you have to use in the right sort of way. The only way you figure out what that right way is, is by active experimentation. So what do you do as a leader in a time like this where there's disruption after disruption coming at you? Well, the 2017 book that I was the lead author of, Dual Transformation, offers my answer to that question. Great news. I can explain the essence of the book just by dwelling on the book's title. Disruption's coming at you. You need transformation. It's not enough to do what you're currently doing better, faster, or cheaper. You gotta do that, but you have to have a fundamental change in form or substance, the organizational equivalent of a caterpillar becoming a butterfly. The word dual in the title suggests this is not a one-shot effort. It's not a monolithic effort. You're doing 2 things in parallel. Number one, what we call Transformation A, you're reinventing today's business to make it more resilient in the face of the disruption. Number 2, what we call in the book Transformation B, creating a powerful new growth engine that picks up that disruption and turns it from threat into opportunity. One more piece of the dual transformation equation. Transformation B is not about unrelated diversification where you take cash flow from one business and invest in something completely unrelated. Instead, it is strategically related diversification. The idea here is you've got unique capabilities. That's the C. You've got know-how, processes, brand distribution, whatever it is. If you smartly leverage on those capabilities, Through a carefully and actively managed capabilities link connecting the two transformations, you can do something that few other companies can do. Leaders demonstrate the courage to choose before the data are clear. Let me tell you a story. A few years ago, back when I was still active at Insite, I got a call from the leadership team of King& Wood Mallesons Australia. This is a leading law firm. They said, we are in trouble. I said, that's strange, as I look at the data and the data does not say you're in trouble. Record revenues, record profits, loyal clients, lawyers all want to work with you. Everything looks great. They said, yes, but we read all this research about disruptive change and it is clear to us that there are big things going on in our industry. This is about now 7 years ago. So it's before ChatGPT had burst into the mainstream and so on. But you had a lot of legal technology solutions that were beginning to emerge, and people were taking them seriously. So we worked with them over the course of about a year and got them to realize collectively that they were in fact facing a hidden crisis. Through that work, we learned something: when you're dealing with disruptive change, you have to confront what we call the information action paradox. Here's the paradox: the freedom to act. and the data that you have are inversely related. In the early days, you can do whatever you want. You have infinite freedom, but there's no data to justify doing this or doing that. At some point, you have perfectly clear data that tells you exactly what to do, but no freedom. Why no freedom? Well, where'd that data come from? People launched businesses, locked up markets, got customers, and so on. By the time the data are clear, it's too late to act on it. So what you need to do as a leader is recognize you have to act when the data tells you not to. You don't ignore the data, you pay attention to it, but what you're really looking for are the weak signals that suggest change is coming. Do you see developments in the lowest part of your market where people are flipping to simpler, easier-to-use solutions? Do you see startups gaining traction following disruptive approaches? Do you hear things from your customers saying, you know, I'm still choosing you, but the gap between you and your competitors is closing. You see those kinds of signs, it suggests that change is coming. Demonstrate the courage to choose. There will be 3 categories of crises. There will be the crisis of commitment. Are you serious about allocating resources to do new stuff? There'll be the crisis of conflict between the new and the old. They will fight. And it can be brutal sometimes. Crisis number 3, the crisis of identity. We were, we are, we will become. That might be very exciting. It also can be really scary and trigger all sorts of hidden defense mechanisms. How do you get through these 3 crises? The conviction to persevere is grounded in having a purpose for your transformation, a clear vision of what you're getting to, And a very powerful way to communicate it throughout the organization.
