The dot-com playbook is back… AI’s gains are going to fewer companies than you think… how to trade when narratives mislead… tomorrow’s AI Signals Trading Event at 10:00 a.m. EasternVIEW IN BROWSER In January 1999, MIS International hadn’t made a dime of profit, and its stock traded below $0.50 per share. But MIS management was aware of a powerful sentiment shift rippling through the broader business and stock market landscape. It had to do with a new, electrifying phrase… “Dot Com.” Younger investors might not recall, but in the late 90s, the term “Dot Com” was magic. It promised vast riches from companies that had found a way to leverage the power of the internet. Virtually any company possessing even the faintest scent of “Dot Com” was investment gold. MIS realized this and decided to signal to the business world (and Wall Street) that it was now a budding digital economy leader. And how would it signal this, exactly? By changing its name to include “Dot Com.” And so, MIS International became Cosmoz.com. You know where this is going… How much of a bump do you think the stock enjoyed? 100%…? 300%…? From less than $0.50 a share, Cosmoz.com – which again, had never turned a dime of profit – soared nearly 1,000% to $5 a share. Fast forward to 2001 in the wake of the Dot Com meltdownAs analysts and commentators sifted through the wreckage after the Dot Com crash, three Purdue University finance professors published a fascinating takeaway… They looked at 95 companies that had added “Dot com” or “Internet” to their names during the ‘90s bubble run-up. What was the impact on the stock prices of these companies in the wake of this branding shift? On average, they enjoyed a 74% stock price surge. It didn’t matter whether the “Dot Com” addition accurately reflected the company’s core business operations – the average stock price surged in the wake of the name change. That’s how much investors wanted to be a part of “Dot Com.”
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How history likes to repeat itselfLast week, Allbirds (BIRD) – the sustainable sneaker brand once valued at $4 billion (now trading at a fraction of that) – announced a pivot from shoes to artificial intelligence. The company will now be called NewBird AI (still with the same ticker “BIRD”), will raise up to $50 million in new funding and will provide GPU-based cloud compute services. And what did the stock do in the wake of this AI pivot? It soared 582%… in a day. Our global macro investing expert Eric Fry, editor of Fry’s Investment Report, reminded his readers that we have seen this movie before. In his recent analysis, he drew a direct parallel to Algorhythm Holdings (RIME) – formerly The Singing Machine Company, a karaoke machine maker that pivoted to AI logistics in 2024. The stock surged on the announcement, then logged losses in both 2024 and 2025 (and is flat so far this year). Here’s Eric drawing the comparison to Allbirds:
Like the hype chasers in the dot-com era, Algorhythm came from a non-tech sector and experienced a valuation spike after announcing a pivot into AI. That spike proved to be short lived.
Allbirds will likely find itself on a similar path.
I’ll note that BIRD has fallen more than 50% from its pivot peak. Eric’s analysis cuts to the heart of why: there’s a meaningful difference between companies that are “AI Survivors” and “AI Appliers” – businesses whose models genuinely benefit from AI or can outlast it – and companies that are simply chasing a hot narrative. Allbirds, in his view, falls squarely in the latter camp. For a contrast, Eric points to Birkenstock (BIRK) – another simple, comfortable shoe brand, but one with genuine competitive advantages. Here’s Eric:
To plainly state the differences: Birkenstock is a profitable, growing, brand-driven business.
On the other hand, Allbirds is a shrinking, unprofitable, trend-driven business.
Beyond Birkenstock, Eric recommends a range of AI Survivor and AI Applier companies in his Fry’s Investment Report portfolio – including a brand of outdoor recreation products, a drive-through coffee shop with a cultlike following, and a king among princes in the drug sector. For the full list, click here to learn more. Now, looking wider, recent data are beginning to show that simply pivoting to “AI” isn’t the fix-all that C-suite managers – or investors – might think. It turns out, the companies actually capturing AI’s economic gains are a much smaller, more disciplined group than the headlines suggest. As for everyone else, so far, the evidence is underwhelming… AI is everywhere…except maybe the dataIn 1987, economist Robert Solow made a fascinating observation… Corporate America had been adopting computers throughout the American workplace for a decade. Productivity growth was supposed to surge. Instead, as Solow realized, it had slowed. From Solow:
You can see the computer age everywhere but in the productivity statistics.
That line became known as “Solow’s productivity paradox.” And according to Apollo chief economist Torsten Slok, we may be living through its sequel:
AI is everywhere except in the incoming macroeconomic data.
Today, you don’t see AI in the employment data, productivity data or inflation data.
Similarly, for the S&P 493, there are no signs of AI in profit margins or earnings expectations.
That’s a startling takeaway, but it’s consistent with results from a new study by the National Bureau of Economic Research. Among 6,000 CEOs, CFOs, and other executives surveyed across the U.S., U.K., Germany, and Australia, nearly 90% reported that AI has had no impact on employment or productivity over the past three years. Among those using AI, average weekly usage is roughly 1.5 hours. That backdrop makes a new global study from PwC released last week even more interesting. Their AI Performance study – based on 1,217 senior executives across 25 sectors – found that nearly three-quarters of AI’s economic value is being captured by just one-fifth of organizations. Here’s PwC’s Global Chief AI Officer Joe Atkinson:
Many companies are busy rolling out AI pilots, but only a minority are converting that activity into measurable financial returns.
The leaders stand out because they point AI at growth, not just cost reduction, and back that ambition with the foundations that make AI scalable and reliable.
The gains are real – they’re just concentratedThese findings echo our March 26 Digest in which we discussed how, even within AI, a new divide is forming. There’s a split between the “secure elite” – companies at the center of the AI buildout, like chipmakers, data center suppliers, and infrastructure players – and various consumer-facing AI products that may be at risk as newer, more intelligent versions of AI cannibalize older ones. Outside of the secure elite, the question is whether the lack of ROI is a structural reality or a timing issue. Fortune laid out the case for the latter back in February, pointing to the IT boom of the 1970s and ’80s. Productivity growth slowed for two decades after computers arrived – but then surged in the 1990s. Returning to Slok, he sees a similar possibility with AI – what he calls a “J-curve” effect:
Maybe there is a J‑curve effect for AI, where it takes time for AI to show up in the macro data. Maybe not.
Whether there is a J-curve effect depends on the value creation from AI.
There is fierce competition between the builders of large language models (LLMs), which is driving the price of LLMs toward zero for end-users.
In other words, from a macro perspective, the value creation is not the product, but how generative AI is used and implemented in different sectors in the economy.
Stanford’s Erik Brynjolfsson, writing in the Financial Times, noted that fourth-quarter GDP was tracking up 3.7% despite only modest job growth – a pattern he sees as consistent with a productivity surge already underway. His analysis points to a 2.7% jump in U.S. productivity last year, which he attributes to AI investments beginning to pay off. So, what does all this mean for us as investors? It paints a complex picture of some winners, many underperformers, and a varied timeline of returns – certainly a more nuanced take than “Allbirds is now an AI stock! Buy it!” Bottom line: The J-curve may be real… the AI productivity gains may be coming… but the data show they’re arriving later than the market has been pricing – and they’re going to a much smaller slice of companies than most investors assume. Which raises a practical question for anyone trying to trade AI stocks in this environment. A different way to read the marketGiven this uneven AI growth story, we need to be especially careful about building trading strategies around AI narratives. But as we’ve been highlighting in the Digest over the past few days, investors have other options. Our corporate affiliate TradeSmith has been developing an approach that sidesteps the problem entirely. Instead of analyzing what AI does or doesn’t do for a given business, their system looks at each stock’s own historical behavioral patterns. Here’s TradeSmith CEO Keith Kaplan with how it works:
Every great trade has its own thumbprint.
In linguistics, it might be a writing style or a phrase.
In the stock market, it’s a unique combination of data points that, taken together, signal a high-probability trade.
In a live internal beta test, the top 100 signal trades produced an average gain of 2.6% over nine trading days – roughly 7x the S&P 500 over the same stretch. Annualized, that’s the equivalent of a 73% return. Here’s Keith with a specific example:
One of our beta test trades was on Equifax Inc. (EFX).
Two factors had to align for this signal to fire. The stock had to close down four consecutive days. And market volatility had to rise above its 10-day average.
When both conditions aligned, the result was a 15.2% gain in seven days — against a 91% historical accuracy rate.
Keith will walk through the system and share far more examples tomorrow at 10 a.m. ET in his AI Signals Trading Event. He’s also opened a beta version of the platform ahead of the event. You can reserve your spot and get access here. Back to Keith:
This new kind of trading system doesn’t care whether we’re in a bull or a bear market. It doesn’t need a strong economy or a calm geopolitical environment.
It just needs certain factors to align. That’s what makes it so powerful in today’s market.
I’ll walk you through how it works in more detail – including the signals it’s tracking right now and the trades it’s flagging for the weeks ahead – during our AI Signals Trading Event launch tomorrow morning.
Again, you can register right here. Overall, the throughline from Cosmoz.com to Allbirds to the productivity data is the same story… Markets move fast on narratives, but the underlying reality often takes longer to arrive – and lands more unevenly – than most investors expect. Knowing that doesn’t mean avoiding AI. But it means being thoughtful about how you invest in it for the long term and disciplined about how you trade it in the short term. Have a good evening, Jeff Remsburg |
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