Bill Gates recently said he is using generative AI as part of the annual, two-week strategy session that determines how the Gates Foundation spends its next $10 billion. He'll be "taking the strategy notes and actually engaging in a dialogue with ChatGPT, Claude, Copilot, and even having them talk with each other," he said.
I don't have $10 billion that I'm considering how to spend, and you may not, either, but genAI has now improved to the point where it can at least be an aid in setting strategy at almost any level.
An old boss, Mel Bergstein, used to say: "Strategy is what you don't do." The idea worked for Mel, who founded a consulting firm, Diamond Management & Technology Partners, that pioneered the notion of digital strategy in the mid-1990s. Chunka Mui and I took Mel's adage further in our book, "Billion Dollar Lessons," for which we had 20 researchers spend two years looking at 2,500 major failures to identify the warning signs.
Our recommended solution boiled down to having a "devil's advocate" identify all the underlying assumptions for a strategy, to keep problems from being glossed over as an executive team rushed to realize the CEO's plan. GenAI, used right, can now do a pretty good job of filling that role for anyone.
Let's have a look.
Gates told the New York Times that, "in a few of the reviews, we’ll actually have the A.I. sit in. In a few cases, we’ll tell it: Hey, only speak if we ask you. And then in a few other cases, we’ll say: Hey, if you hear something you think is wrong or you hear us thinking about, for example, what are these statistics? Please engage. So we’ve gone from it being a joke [when someone suggested using genAI a year ago] to it will be a peer — not making any final decisions, but it will be a peer in deep, complex strategic discussions, making a significant contribution."
I'm not willing to go that far just yet, partly because I'd need to test the domain knowledge that the large language models have about a subtle, heavily regulated business like insurance and partly because genAI has shown itself to be a sycophant. The biggest, overarching pattern of failure that Chunka and I found in the research for "Billion Dollar Lessons" was that people were reluctant to point out obvious problems that could derail initiatives that had the imprimatur of the CEO, and we don't want to replace human sycophants with AI ones.
But you can describe your strategy to an AI, then pepper it with questions, going deeper each time while demanding evidence for its thinking and insisting it be blunt.
Let's say you're thinking of buying a company. You could start with a general question: What could go wrong? Then you probe. How will our competitors react? What if interest rates increase? The economy goes into recession? The war in Iran escalates? Will we actually be able to cross-sell to our customers? Will the efficiencies from scale be as great as we expect? Who's done something similar and had problems? What were the problems? And on and on and on.
You can do the same exercise if you're thinking of a new line of business, a software overhaul, adopting AI chatbots — or if you want to explore the dangers of standing pat, of not undertaking a major initiative that is under consideration.
Major corporations have staff do extensive analysis along the lines I'm suggesting and, in the case of a possible acquisition, draw on their investment banks for advice — but the bias is always toward acting. If the perception is that the CEO backs an idea, the staff strives to make it work, not to kill it. Investment banks only collect their hefty fees if the deal happens, so why would they recommend against it?
When Chunka and I did a consulting project with a major company that was considering launching autonomous vehicles, we saw elaborate studies it had commissioned from consulting firms that said the robotaxi business was a slam dunk and that the first to enter would win big. That was more than eight years ago.
It turned out, however, that the executives working on the AV project internally were aware of all the sorts of operational and safety issues that we've all seen play out and that have slowed the robotaxi rollout. Those concerns were brought to the surface in the interviews for our devil's advocate review.
Warren Buffett used to set aside two, equal pots of money when asking investment banks for advice on possible acquisitions — one for a bank that argued in favor of a deal and one for a bank that argued against it. Whichever carried the day collected its fees, while the other got nothing. You can be sure the "anti" bank worked as hard as possible on its arguments and evidence.
In my experience, many big ideas should fall apart at the slightest scrutiny. As we wrote in "Billion Dollar Lessons," we thought 47% of the failures we investigated were based on strategies that never should have made it out of the strategy room — and not because those involved were stupid or inexperienced.
The fifth-biggest cement maker in the world reasoned that it was really in the home products business because so much of its cement was used there. It began also making furnaces and lawn mowers... then went bankrupt and was bought by a competitor. Avon decided that its core competency was its culture of caring — not, you know, its line of cosmetics and its devoted salesforce — so it bought a maker of medical equipment and an operator of retirement homes. It had no idea how to operate the new businesses and quickly sold them at a major loss. In the early days of fax machines, FedEx spent hundreds of millions of dollars to set up a business that would collect a document from you, drive it to the nearest office, fax it to the office nearest your destination, then drive the fax to the recipient. The company somehow missed that Moore's law would soon make the devices so inexpensive that every company would have its own.
It may take time to learn how to use genAI to avoid costly strategic mistakes — and that's even before we start using it as broadly as Gates is planning to. You'll likely also need to introduce to the LLM information specific to your market, including regulatory issues that it likely doesn't have even as these models try to Hoover up everything available on the internet. Insurance is a complicated market.
But I think we're now at the point where genAI can, if managed correctly, start to catch strategic errors. We won't get that 47% figure for obviously bad ideas down to zero, but even heading toward 40%, maybe even 33%, would mark real progress.
Cheers,
Paul