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In January 1999, MIS International did not make a single profit, and its stock was trading at less than $0.50 per share.
But MIS management was aware of the strong shift in sentiment that rippled across the broader trading landscape and the stock market. It had to do with a new and electrifying phrase…
“Dot com”.
Younger investors may not remember, but in the late 1990s, the term “dot com” was magical. It promised huge fortunes from companies that found a way to harness the power of the Internet. In fact, any company that had even the slightest whiff of “dot-com” was investment gold.
MIS realized this and decided to signal to the business world (Wall Street) that it was now an emerging leader in the digital economy.
How exactly could he be referring to this?
By changing its name to include “Dot Com”. Thus, MIS International became Cosmoz.com.
Do you know where this is headed…
How much of a bump do you think the stock enjoyed?
100%…?
300%…?
From less than $0.50 per share, Cosmoz.com – which had never made a single profit – rose almost 1,000% to $5 per share.
Fast forward to 2001 in the aftermath of the dot-com crash
While analysts and commentators were sifting through the wreckage after the dot-com crash, three finance professors at Purdue University published a fascinating conclusion…
They looked at 95 companies that added “dot-com” or “Internet” to their names during the run-up to the 1990s bubble.
What will be the impact on these companies’ stock prices following this brand shift?
On average, they enjoyed a 74% rise in stock prices.
It didn’t matter whether the addition of “dot.com” accurately reflected the company’s core business operations — the average stock price rose in the wake of the name change. That’s how much investors want to be part of Dot.com.
How history likes to repeat itself
last week, all birds (bird) — the sustainable sneaker brand once worth $4 billion (it now trades at a fraction of that amount) — has announced its shift from shoes to artificial intelligence.
The company will now be called Newbird AI (which still carries the same ticker “BIRD”), will raise up to $50 million in new funding and provide GPU-based cloud computing services.
What did the stock do in the wake of this artificial intelligence pivot?
It rose 582%…in one day.
Our global macro investing expert Eric Fry, editor Fry investment reporthe reminded his readers that we had seen this movie before.
In his final analysis, he draws a direct parallel with Algorithmic Holding(Reem) – Formerly Singing Machine Company, a karaoke machine manufacturer focused on AI logistics in 2024.
The stock rose after the announcement, then posted losses in both 2024 and 2025 (and is flat so far this year).
Here Eric draws the comparison to Allbirds:
Like the hype chasers of the dot-com era, Algorithm came from a non-technology sector and saw a sharp rise in valuation after announcing a shift to artificial intelligence. This rise proved short-lived.
Allbirds will likely find itself on a similar path.
I will note that the BIRD has fallen more than 50% from its pivotal peak.
Eric’s analysis gets to the main reason why: There’s a big difference between companies that are “AI survivors” and “AI adopters” — companies whose models truly benefit from or can outlast AI — and companies that are simply chasing a hot narrative.
In his view, Allbirds falls squarely into the latter camp.
By contrast, Eric points out birkenstock(Burke) – Another shoe brand that is simple and comfortable, but has real competitive advantages.
Here’s Eric:
To clearly state the differences: Birkenstock is a profitable, growing, brand-driven company.
Allbirds, on the other hand, is a shrinking, unprofitable, trend-driven company.
Aside from Birkenstock, Eric recommends a range of AI Survivor and AI Applier companies in his country Fry investment report Its product portfolio – including a brand of outdoor recreation products, a car dealership with a cult following, and a king among princes in the drug sector. For the full list, Click here to learn more.
Now, looking more broadly, recent data is starting to show that simply turning to “AI” is not the solution that executives — or investors — might have imagined. It turns out that the companies actually capturing the economic gains of AI are a much smaller and more disciplined group than the headlines suggest.
As for others, so far, the evidence is disappointing…
AI is everywhere… except maybe in data
In 1987, economist Robert Solow made a fascinating observation…
American companies have been adopting computers throughout American workplaces for a decade. Productivity growth was supposed to rise.
Instead, as Sulu realized, it slowed down.
From Solo:
You can see the computer age everywhere except productivity statistics.
This line became known as “Solow’s productivity paradox.” And according to Apollo’s chief economist, Torsten Slok, we may be experiencing a sequel:
AI is everywhere except incoming macroeconomic data.
Today, you don’t see AI in employment data, productivity data, or inflation data.
Likewise, for the S&P 493, there are no signs of AI in profit margins or earnings forecasts.
This is a startling idea, but it is consistent with the results of a new study conducted by the National Bureau of Economic Research.
Among 6,000 CEOs, CFOs and other executives surveyed across the US, UK, Germany and Australia, nearly 90% reported that AI had had no impact on hiring or productivity over the past three years.
Among those who use AI, the average weekly usage is about 1.5 hours.
This background makes a new global study by PricewaterhouseCoopers released last week even more interesting.
The AI ​​Performance Study – which was based on the views of 1,217 senior executives across 25 industries – found that nearly three-quarters of the economic value of AI is captured by just one-fifth of organisations.
Here’s Joe Atkinson, Global Head of AI at PricewaterhouseCoopers:
Many companies are busy rolling out AI pilots, but only a minority are turning this activity into measurable financial returns.
Leaders stand out because they position AI toward growth, not just cost-cutting, and they support that ambition with the foundations that make AI scalable and reliable.
The gains are real – they’re just concentrated
These findings resonate with us March 26 digest We discussed how a new division is forming, even within artificial intelligence.
There is a divide between the “safe elite” — companies at the center of building AI, such as chip makers, data center suppliers, and infrastructure players — and various consumer-facing AI products that may be at risk as newer, smarter versions of AI cannibalize older versions.
Outside the safe elite, the question is whether the lack of return on investment is a structural fact or a matter of timing.
luck I brought up the latter issue last February, referring to the IT boom of the 1970s and 1980s. Productivity growth slowed for two decades after the advent of computers – but then picked up in the 1990s.
Returning to Behavior, he sees a similar potential with artificial intelligence – what he calls the “J-curve” effect:
There may be a J-curve effect of AI, where AI takes time to appear in macro data. Maybe not.
Whether there is a J-curve effect depends on value creation from AI.
There is fierce competition among makers of large language models (LLMs), pushing the price of LLMs toward zero for end users.
In other words, from a macro perspective, value creation is not the product, but how generated AI is used and implemented in different sectors of the economy.
Erik Brynjolfsson of Stanford University, writing in Financial TimesHe noted that fourth-quarter GDP rose 3.7% despite modest job growth — a pattern he sees as consistent with the productivity increase already underway.
His analysis points to a 2.7% jump in US productivity last year, which he attributes to AI investments starting 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 view than “Allbirds is now an AI stock! Buy it!”
Bottom line: The J-curve may be real… and AI productivity gains may be coming… but the data shows that they are arriving later than market pricing – and that they will reach a much smaller segment of companies than most investors assume.
Which raises a practical question for anyone trying to trade AI shares In this environment.
A different way to read the market
Given the uneven growth story of AI, we have to be especially careful about building trading strategies around AI narratives. But as we highlighted digest Over the past few days, investors have had other options.
Our affiliate, TradeSmith, is developing an approach that avoids the problem altogether. Instead of analyzing what AI is doing or not doing in a given company, their system looks at historical behavioral patterns for each stock.
Here’s TradeSmith CEO Keith Kaplan with how it works:
Every great trade has its own mark.
In linguistics, it may be a writing style or a phrase.
In the stock market, this is a unique combination of data points that together indicate a high probability trade.
In a live internal demo test, the top 100 trades produced an average gain of 2.6% over nine trading days – nearly 7 times the S&P 500 over the same period. On an annualized basis, this equates to a 73% return.
Here’s Keith with a specific example:
One of our demo trades was running Equifax Corporation (EFX).
Two factors had to be aligned to trigger this signal. The stock had to close lower for four consecutive days. Market volatility had to rise above its 10-day average.
When both conditions were met, the result was a 15.2% profit in seven days – versus a historical accuracy rate of 91%.
Keith will walk through the system and share more examples Tomorrow at 10am ET In his country Artificial intelligence signals trading event. He also opened up a beta version of the platform ahead of the event. You can reserve your place and access it here.
Back to Keith:
This new type of trading system does not care whether we are in a bull or bear market. It does not require a strong economy or a calm geopolitical environment.
It just needs certain factors for alignment. This is 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 now and the trades it’s flagging for the coming weeks – during the AI ​​Signals Trading Event launch tomorrow morning.
Again, you can Register here.
Overall, the line from Cosmoz.com to Allbirds to productivity data is the same story…
Markets move quickly based on narrative, but the underlying reality often takes longer to arrive – and falls more unevenly – than most investors expect.
Knowing this doesn’t mean avoiding AI. But it means being deliberate about how you invest in it for the long term, and being disciplined about how you trade it in the short term.
I wish you a good evening,
Jeff Remsburg
