We’re Not Asking the Right Questions on AI

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• The investing world is flatter now than in the lazy days of value investing, says Aswath Damodaran, professor of corporate finance and valuation at the NYU Stern School of Business.
• AI may be significant, but not for the reasons most people think: We don’t ask the right questions. There are too many viewpoints and not enough time to think for ourselves as investors.
• Investing styles that lack dynamism and focus on what worked in the old time value investing world won’t work in this ones.

In a world beset by AI hype, here’s a hot take: “The net effect of AI is going to be close to zero.”

That’s what Aswath Damodaran, professor of corporate finance and valuation at the NYU Stern School of Business, says in conversation with Alan Dunne during a recent episode of Top Traders Unplugged. Aswath is the go-to expert in all things valuations, with multiple books and papers published on valuation, corporate finance, investing and portfolio management.

But he’s not just markets through and through: “My first passion is teaching,” he says. Corporate finance and valuation just happens to lie “at the intersection of numbers and stories, people and businesses. It's the combination of psychology, statistics, data and economics that makes it fascinating.”

And the most fascinating thing of all? We’re not even asking the right questions about AI, which means we could be getting all the investment stories wrong. “Unless we ask the right questions, we could be right about the big story of AI being a revolutionary change, but wrong about every investment story we create,” he explains.

When not teaching, he shares his musings on markets and lectures on YouTube. At the same time, he strongly recommends giving yourself idle time and space to think. “We're surrounded by so many opportunities to go look things up and read what other people think that we're drowning in other people's opinions,” he warns.

Aswath’s incisive opinions span Nvidia, AI, valuations and why value investing isn’t going to work like it used to.

What follows are some of the biggest takeaways.

Bullish on big tech? Not likely

If you want real performance, look at the Magnificent Seven (mag seven) stocks — Apple, Microsoft, Google parent Alphabet, Amazon, Nvidia, Meta Platforms and Tesla — but don’t expect a repeat in the near future.

While Aswath bought Nvidia six years ago, he doesn’t consider himself bullish by any measure. “This notion of bullish and bearish is a fancy way of saying I can't make a decision,” he says.

Instead, buy what you want to own when it’s cheap based on your valuation. “If I'm really bullish on something, I should own it. If I don't own it and claim to be bullish on it, you should be skeptical about what I'm bullish on,” Aswath says.

And what’s all the fuss about with Nvidia anyway?

“I don't think AI or any other buzzword adds a half a percent or 1% to GDP on a net basis,” he says. “It might do on a growth basis, but it does so by destroying other businesses that contribute to GDP.” He has the rise of PCs, the internet, smartphones and social media in his sights as what everyone presumed would make the economy grow faster, but at what cost?

GDP growth was lower during the 1980-2010 period before winning businesses grew as much as the buzzwords that boosted their growth. They came at the expense of other businesses that shrunk and went away. For that reason, “the net effect of AI is going to be close to zero,” Aswath explains. That doesn’t mean no winners and losers from AI: just that, economically, it won’t make much difference.

“We talk about disruption a great deal — we don't talk about the disrupted along the way,” he says. “This notion that AI is somehow going to carry the entire economy and the market upwards is a delusion.”

AI is here to stay and may well herald a revolutionary change — for both business and society. All four technology innovations — PCs, the internet, smartphones and social media — bore winners now worth trillions, but “the net effect on markets was surprisingly neutral, because for those winners, there were dozens, even hundreds of losers,” Aswath says.

AI winners may not be the companies you think. Bringing it full circle, “Nvidia reminds me of Cisco,” he says. Cisco didn’t gain as much as some — like many of the mag seven — from the growth of the internet. Nvidia is an AI architecture business that’s monetizing revolutionary changes, but even if the AI industry overall is worth trillions of dollars, the architecture charging that isn’t more than half of that.

Where does that leave Nvidia?

Asking the right questions to break the delusion

“AI is a buzzword,” Aswath says. “Using AI as a rationale for pushing up the prices of companies without getting specific” is an unsustainable tactic.

Nvidia’s $3 trillion market cap — with a built-in expectation of an exploding AI chip market — highlights what Aswath calls “the big market delusion, which is when you have a big market and people keep using the macro story to justify why they’re paying more for the company.”

But he also points out that “eventually the delusion breaks because the numbers start to roll in,” and optimism can no longer carry momentum. “AI is B2B: It's not what you and I will be spending on AI — it's what companies will be spending on AI.”

Identify the winners and losers from this latest change, and you’re closer to asking better questions. Rather than pushing up prices on the back of expected AI use, ask for specifics. Continuing the delusion is like being on the losing end of the dot com boom.

“Unless we ask the right questions, we could be right about the big story of AI being a revolutionary change, but wrong about every investment story we create based on it,” Aswath explains.

AI is a combination of “two big forces that have been in markets for the last two decades: more powerful (and miniature) computers and data.” The winners — big tech companies like Facebook, Apple and Google — exploit AI by using rather than creating the architecture that enables AI. “They have the data, cloud systems on which we store the data, and they have powerful computers.”

The question is: How do young startups match the data and computing power of these giants? That remains to be seen.

Here’s what investors need to remember

“This is the strangest business on the face of the earth: In any business, professionals do better than amateurs,” Aswath says. “But professional money managers have been losing this war for four decades.”

Active investors who didn’t own FANGAM stocks in the last decade are at a huge disadvantage. “If your investment strategy is focused and concentrated — like old time value investing — that’s a huge red flag,” he says. Maybe you lucked out and got onto a winner, but many investment philosophies — like buying stocks with low PE ratios or small cap investors — are structured away from them.

“Any style that's not dynamic and doesn’t allow you to stretch across the market is a style I would avoid,” he says. “If you’re an active investor, you can’t be rigid.” So, what’s changed?

“The market and economy have changed,” he says. “More businesses have become winner-takes-all businesses.” Compare hospitality in the 2000s — splintered, with no hotel company owning more than 6% market share — with Airbnb today. As recently as 2008, the car service industry was similarly splintered — with the largest cab companies owning a maximum of 1% market share — but ride-sharing today allows for a monopoly. Networking effects snowball success: as businesses get bigger, it gets easier to get bigger.

If you’re in a winner-takes-all economy, it shouldn’t be surprising to see the biggest winners being the biggest companies. In four decades, the investment world has flattened. Old time value investors could be lazy and still make money. No longer is that the case.

“What I heard from value investors was we’re the grown ups. These traders and tech investors are shallow,” Aswath says. “The problem with being righteous is you think you deserve to be rewarded for doing the right things.” If you don’t get rewarded, you suffer, and double down — then go bankrupt short selling.

Every single company was a momentum stock at some point in time. “Every one of the mag seven stocks in the last 15 years has been cheap at least three times,” Aswath says. “The word you should avoid in investing is never. When you say I will never buy that stock, you've drawn a line in the sand. At the right price, you should be willing to buy any stock. I want investment philosophies that start with and then build on that premise.”

Establish the equity risk premium

Start with the premise that sensible, rational investors should demand more than the risk-free rate when investing in risky assets. Then, take an average of what a group — such as finance students, some of whom are more risk-averse than others — demand as a premium over a risk-free rate. That’s a market’s equity risk premium and how you establish valuation.

But you need a forward-looking number, not a historical, backward-looking premium. Valuation textbooks are no good for the 21st century. “What I'm trying to estimate is what I tried to do in my room for the entire market,” Aswath says. Instead of asking them, he looks at what they pay. “I can then reverse engineer what you can expect to make,” he says. “It's very grounded in reality and is completely model-agnostic.”

The equity risk premium becomes a number to debate the correct prices of stocks. Expecting to make 16% based on the last decade isn’t the right approach. The equity risk premium replaces the blunt instrument that is the PE ratio, which fails to factor in rate levels, growth and cash flows.

What investors should really do about AI

If Aswath had one piece of advice for investors, it would be to “read less and think more.”

In a world of too many opportunities to drown in others’ opinions, “part of the investing journey is developing your own original way of thinking that reflects who you are as a person, what makes your investment philosophy. For that, you’ve got to allow your mind some idle time. We don't really have that idle time anymore.”

AI can work with data, charts and a replicated Warren Buffett mindset, crushing any advantage that we, as humans, have against AI — if we don’t give ourselves time and space.

“There’s a bot out there with your name on it that's coming for you, and your job is to find things to do that your bot can't do. Think of that as your 10-year mission. You have about a decade to play this out, because if all you do is mechanical stuff, a bot will do it much better than you can very soon.”

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This is based on an episode of Top Traders Unplugged, a bi-weekly podcast with the most interesting and experienced investors, economists, traders and thought leaders in the world. Sign up to our Newsletter or Subscribe on your preferred podcast platform so that you don’t miss out on future episodes.