Remember when everyone declared the AI trade dead after DeepSeek’s breakthrough?
Wall Street just proved them spectacularly wrong.
As I write this, the S&P 500 sits tantalisingly close to all-time highs. US stocks have added nearly $10 trillion in market value following their recent surge.
Nvidia just hit a record high, reclaiming its crown as the world’s most valuable company at US$3.78 trillion.
It’s a remarkable comeback from the US$600 billion wipeout during the DeepSeek panic.
But before you rush to buy every AI stock in sight, let’s talk about what this recovery really means. And consider some of the major themes for investors as the AI revolution enters its second act.
Because the story isn’t as simple as ‘AI is back, buy everything.’
In saying that, the bulls are in control right now.
The $600 Billion Resurrection
The numbers are undeniably impressive.
The chip giant has roared back after export restrictions and DeepSeek’s breakthrough sent Nvidia tumbling.
CEO Jensen Huang painted a bullish picture at Wednesday’s shareholder meeting. AI’s a ‘multitrillion-dollar opportunity’, he said, promising a decade-long infrastructure build-out.
Supporting narratives are everywhere. Last quarter, Microsoft processed five times more AI requests than a year ago. Chip-memory supplier Micron just posted record revenue of US$9.3 billion.
The broader tech sector is now up 40% from April’s lows.
And retail investors just poured US$3.2 billion into stocks in just five days.
In the long term, I am very bullish on AI’s prospects. But here’s where I think thoughtful investors need to pause.
Reality Check: AI Won’t Transform Everything Overnight
In 1987, economist Robert Solow famously quipped, ‘You can see the computer age everywhere but in the productivity statistics.’
Now, decades on, AI could be the latest iteration of this paradox.
While there’s a steady drumbeat of new studies supporting the idea of productivity gains while using AI, there are also gaps.
As Chief Information Officer, Paul Hlivko wrote in his brilliant piece this week.
‘AI will transform industries. However, this transformation will happen on enterprise time: longer, slower, and with far more friction than most expect.’
The parallels to prior technology revolutions are instructive.
Electricity revolutionised manufacturing, but it took 40 years before factory design caught up.
The internet was born in the 1970s, and the World Wide Web in the 90s, but it didn’t rewrite business models until the 2000s.
Yes, technology is accelerating everything. You only have to look at the news cycle to see that.
However, this new technology still needs an adjustment period to take hold, especially for enterprises trying to adopt AI.
That’s great; that’s an opportunity for investors to target companies that are facilitating the change.
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The Human Authentication Opportunity
This is where the story gets interesting for discerning investors.
While everyone focuses on building bigger AI, Reddit CEO Steve Huffman revealed what might be a real goldmine: proving you’re human.
‘We’re in an arms race,’ Huffman told the Financial Times yesterday.
As AI-generated content floods the internet, platforms ensuring authentic human interaction could become far more valuable.
However, maintaining that authenticity will be a massive problem for social media platforms. Another problem — another investor opportunity.
Reddit is exploring partnerships with Sam Altman’s Worldcoin for eyeball-scanning verification. I’m sceptical that eyeball-scanning is something many will line up for.
But this points to a broader investment thesis: The real value in AI might not be in the models themselves, but in the data that trains them and the systems that verify authenticity.
In my opinion, there are still gems to be found in AI — you just need to do some digging.
Lessons from History
The lessons from previous tech cycles are clear. Infrastructure providers get the headlines, but companies operating on that infrastructure capture the value.
I believe AI is following the same pattern. The companies that will create lasting value aren’t building AI models — they’re solving specific problems with AI in their solutions.
Here are some examples:
- Industry-Specific Applications: Harvey.ai (AI lawyer), Abridge (AI medical scribe), Factory.ai (AI software engineer) are some examples.
- Data Authentication Services: As AI content proliferates, verifying human-generated data becomes critical. Adobe [ADBE] is worth watching here.
- Enterprise Integration Platforms: Companies helping businesses embed AI into existing workflows. UiPath [PATH] is one such undervalued play.
- Proprietary Data Owners: Businesses that hold unique, real-time data that can’t be scraped from the Internet can be found everywhere, including the ASX.
Building Your AI Portfolio
The market’s exuberance is understandable. AI represents genuine transformation. But transformation doesn’t equal instant profits.
For individual investors, this means asking harder questions and not chasing expensive AI plays.
Nvidia’s recovery shows the market believes in AI’s future. That’s not wrong. But believing in the future and profiting from it are two different things.
The thoughtful investor’s approach? Acknowledge AI’s transformative potential while considering our history with technological change.
Look for companies with real moats — whether that’s proprietary data, distribution advantages, or real AI capabilities beyond hype.
And remember: In technological revolutions, real money rarely goes to the first to arrive. It goes to those who build something lasting.
Who’s currently building that future?
Our own James Altucher has considered this problem. As an ex-hedge fund manager and early tech investor, he’s seen this playbook before.
He thinks he has the next major AI investments for your portfolio in his latest Wealth Window.
Be sure to take a look.
Regards,
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Charlie Ormond,
Editor, Alpha Tech Trader and Altucher’s Early-Stage Crypto Investor
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