Sangeet Paul Choudary, the founder of Platformation Labs, is the author of Reshuffle:Who Wins When AI Restacks The Knowledge Economy, which was published in July. He previously wrote two best-selling business books Platform Revolution and Platform Scale.
Choudary has advised the leadership of more than 40 of the Fortune 500 firms and has been selected as a Young Global Leader by the World Economic Form. His work on platforms has been selected by Harvard Business Review as one of the top 10 ideas in strategy, alongside Michael Porter, Clayton Christensen and others, and is one of the rare articles to have been featured on four occasions in the HBR Top 10 Must Reads compilations.
He is currently a Senior Fellow at the University of California, Berkeley and a Scholar at Dartmouth College and was formerly appointed to the World Economic Forum’s Global Future Council. He formally served as the co-chair of the MIT Platform Strategy Summit. He is a frequent keynote speaker at leading global forums including the G20 Summit, the World50 Summit, and the World Economic Forum. Choudary recently spoke to The Innovator about his new book and rethinking systems in the age of AI.
Q: There is a lot of discussion these days about AI and the Jevons Paradox, which states that, in the long term, an increase in efficiency in resource use will generate an increase in resource consumption rather than a decrease. In your book you say this focus misses what’s really happening. Why is that?
SPC: AI is often treated as a binary issue. You’re supposed to pick one of two camps. One is the Jevons Paradox camp, which says that when the economics around the usage of a technology change to allow more efficient usage, its overall demand increases as it can be applied to many more use cases. This is used to make the case that AI will have a positive impact and lead to a growing pie. Then there’s the other side of the equation, where people say that AI is going to take over jobs. The positive camp says that it’s not zero sum, it’s positive sum and the negative camp says that we don’t yet see where the positive sum is going to happen, we only see things going away. Today’s polarized debate frames the issue in terms of productivity gains or job loss, but overlooks how AI changes how systems are restructured and who has control over them.
What both these camps miss is that it’s entirely possible for the pie to expand while also creating the conditions through which the pie gets sliced unevenly, so that the positive outcomes that are normally attributed or associated with the positive sum effect do not actually play out because the pie gets sliced unevenly.
My point here is that the very factors that grow the pie are also responsible for slicing the pie unevenly, and we’ve seen that over the last 15 years with the rise of platforms. This happens because when new technologies are introduced you have an opportunity to reorient and redesign the entire system. It’s not just a fixed set of tasks that is being replaced, or for which the demand is increasing. New technology fundamentally restructures the entire system. That allows you to create alternate centers of power within that new system to shift the point of extraction and the point of leverage. As a result, some of yesterday’s winners lose, and some become even stronger, and entirely new winners emerge. The key point is that, yes, the pie will expand, but it is far from likely that it will expand proportionately for everyone.
Q: In Reshuffle you argue that success is no longer determined by getting better at playing yesterday’s game by using AI, but rather on whether you’re playing the right game. Can you please elaborate.
SPC: I think one of the key ideas in strategy is really being challenged these days. Strategy has always been the question of where to play and how to win. You choose your playing field, and then you choose an advantageous position within the playing field. Traditionally, before the proliferation of digital, the competitive playing field was relatively static, meaning industry boundaries were relatively fixed. Your competitors looked like you. They were very clear guidelines on how to compete, and those guidelines stayed fairly constant and static, hence positional advantage was what worked, because you knew that the playing field was static, and you knew which positions would hold value, and you accordingly would look to acquire those positions and strengthen those positions through assets regulation, etc. What’s happening today – and this speaks to my point about applying new technology to old systems – is that the way to play is up for grabs. Industry boundaries are no longer impermeable. When industry boundaries become permeable, your competitors don’t look like you anymore, because competitors also start moving across industry boundaries. So, both the where to play and how to win are up for grabs, which essentially means that you can’t just take technology and say ‘this is my position in the static playing field, and I’ll use technology to strengthen my current position or even to find a better position’ because value has shifted within the static playing field. All of that assumes that you’re still on the same playing field, but the way to compete has changed. Technology offers you the opportunity to re-imagine the game itself. When new technologies are introduced, the least advantageous position is to use those technologies to figure out how to play your game better. Instead, think about how you can fundamentally change the game for everybody else. How can I change the rules of the game so that the way the industry competes completely changes?
Former giants collapse not because they didn’t adopt the tools, but because they adopted them into old systems. Kodak went digital, and Barnes and Noble had a website and an e-reader, but in the end, it didn’t really matter.
Kodak is an interesting example because it it’s obviously an interesting failure, but people keep looking for convenient explanations. One of the most prominent explanations among innovation professionals is that a fast moving startup beat a slow moving industry giant. That’s too simple and inaccurate. Just five years before its bankruptcy, Kodak was the number one digital camera manufacturer in the US. It invented the digital camera and waited for the right time to introduce it. It made a lot of the right investments and even though it was traditionally a film and a chemicals company it had shifted to becoming a digital printing company. Kodak had nationwide deals with Walmart and others and and it had displaced Fuji film as the number one digital printing company in the US by 2006 as well. So, it was both the number one digital camera company and the number one digital printing company. What broke Kodak was that the entire playing field in which photos are taken shifted so that owning and collecting photos was no longer valuable. What was valuable was sharing and commenting on photos,and that meant that fundamental rules of the game had completely changed. Any business that was using technology to improve the ability to own and print photos would lose, even if it had the best technology, just because it was putting it into an older system that did not matter anymore.
Q: Reshuffle talks about how what really drives change is a shift in power owing to new tensions that AI introduces on three levels: the task level, the organizational system level and the competitive ecosystem level. How does this impact business?
SBC: The way we’re thinking about AI today is fundamentally wrong, because we are thinking about it in terms of the tasks that companies perform, the tasks that individuals perform and we’re seeing AI merely as an efficiency play of either speeding up those tasks or substituting tasks with a lower cost alternative. My point is that these tasks do not exist randomly. They exist inside a value framework. That value framework is about how these tasks are organized in workflows to create value towards solving a customer problem. And that organizational framework itself sits inside a competitive framework. It’s not just a set of tasks that create value, but a set of companies competing and collaborating in competitive ecosystems through which that value is created and through which companies find which parts of the customer problem they solve, where they partner, where they compete and who they compete with. And , when we think about the impact of AI, if we just think about it at the impact level of individual tasks, we’re essentially trying to solve a very, very complex, multi- dimensional mathematical problem by looking at a single addition or subtraction operation. We are not thinking about all the other interactions around which that task holds value in today’s system, and when the whole system changes whether there will still be value.
I use the example of container shipping, which I believe is one of the most transformative technologies of the last 100 years, as a case in point, because it heralded globalization and changed the nature of geopolitics and changed the nature of industries. When the container was first introduced, it was seen as a faster way to load or unload cargo that was shipped. Before that we had breakbulk shipping of cargo of different sizes. With the container standardizing you could now have a mechanized port running all that loading and unloading. Ports moved faster, so goods could now be shipped faster. The mechanization of ports, the automation of loading and unloading and the loss of jobs of dock workers, was just the first order effect. The second-order effect was what mattered. Even if ports moved faster, rails and roads could still slow things down. The real impact of the container became visible only when trucks, trains and ships all agreed on a standardized version of the container, so the container could easily be moved from one to the other. That made intermodal transportation possible, which dropped the cost of logistics and freight globally. That changed the nature of manufacturing globally because you no longer needed to manufacture products end-to-end inside a facility. You could source components from anywhere across the world because freight was reliable. Global supply chains emerged as a result and component level competition started happening. The computing industry is a great example. Before the container, we had the mainframe industry, which was vertically integrated, but the container made it possible to have Intel and AMD compete on components, rather than run the whole thing end-to -end like an IBM used to do. And alongside this, because freight was reliable, the role of middlemen also diminished, because you could now have just-in-time inventory. So, manufacturing fundamentally changed. The organizational system changed and then the entire competitive ecosystem changed as a result as well. Competition shifted to improving components. Before this, companies were focused on monolithic products. As components improved, new companies emerged to take existing components and innovate new combinations of components into new products, and so the nature of innovation fundamentally changed as well. If you had only seen or tried to understand it in terms of its effect on ports, and most people initially saw only that, you would have missed what was about to happen as a result of containerization. I take the example of Singapore in my book. It’s the opening story. I spent a lot of my adult life there. What helped Singapore move from being a village into a global city within a short span of 30 years was the fact that it bet on this shift in global trade. It realized that intermodal transportation and reliability were going to become important, so it invested heavily into that, and that really helped it exploit all the global activity that started around the shipping container. So companies today need to really think about how the overall system is changing.
If you do not see the overall system, if you cannot place a bet on what the future system is going to look like you won’t become a Singapore and benefit from all the new value that gets unlocked, you’re just going to keep upgrading your ports, which is what Bangkok did, or end up like Liverpool, which lost all of its traditional port activity, as well as its manufacturing industries, because it did not embrace the container.
So what advice do you have for large corporates to help them end up on the winning side?
SBC: I wrote this book because when my books Platform Revolution and Platform Scale became successful, I was called into boardrooms around the world with one single question: ‘What should our platform strategy be?’ It was the wrong question. The real question was what’s a new way to play and what’s a new way to win given the reality of today’s platform economy? Today, companies are making the same mistake when they ask ‘What should our AI strategy be?’ They are looking at what they do and how AI’s capabilities can help them do that better. They look at companies that have got that right. They get in speakers from those companies, and then they try to see how they can emulate those things. The same thing happened when platform business models emerged. Incumbents tried to emulate what startups and Big Tech were doing and learned the hard way that these approaches did not apply to them. The reason for that is not just a mismatch of culture, or slow-moving giants versus fast moving startups. Those things matter as well but the fundamental reason is an incumbent has a very clear architecture of advantage. An incumbent does not win just because of a better product or a better access to customers. They’ve created a whole system of interacting choices: an architecture of advantage. You cannot just take new technology into an old architecture and think that it’s going to make you win and it’s going to improve what you already do. You need to look at that new technology and the assumptions which your current architecture of advantage is based on, and you need to ask yourself which of those assumptions will completely change because of this new tech? The moment that change happens, the assumptions on which your entire architecture of advantage is based need to change as well.
That’s the key point that I would make. You don’t need an AI strategy. You need a strategy for the conditions that AI creates. Strategy has always been about where to play and how to win. Conditions are changing. A big part of that change is AI, for sure, but you really need to think about this more holistically. Think about all the forces that impact your company’s playing field and your game and then reimagine both in light of those forces.
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