As debates rage over whether the artificial intelligence (AI) stock rally has spiraled into a bubble, a top analyst who accurately predicted the dot-com bust is pushing back with a starkly different view.
“We are not in a bubble; the AI party is not even close to midnight,” said Dan Ives, renowned tech analyst at Wedbush, in his latest report. He asserts that the AI revolution is not in its final chapter but its early innings, and has identified what he calls the 10 essential stocks to own for the future.
In a recent interview with Yahoo Finance’s “Opening Bid,” Ives highlighted that only about 3% of U.S. companies and less than 1% globally have genuinely started implementing AI. While the hype is deafening, he argues, real-world adoption remains in its infancy, far from the late-cycle froth typical of a bubble.
Ives emphasizes that today’s elevated AI stock valuations are not driven by mere speculation. Instead, they are fueled by tangible enterprise spending, significant government demand, and a critical shortage of advanced AI chips.
Having covered the tech sector since the dot-com era, Ives draws a clear distinction between then and now. “During the 1999 bubble, the average tech stock traded at 30 times sales, often with little more than slide decks and unproven business models,” he noted. “Today’s leaders are generating hundreds of billions in cash flow, backed by real infrastructure and massive customer bases.”
He points to Nvidia (NVDA) as a prime example, where demand for its AI chips continues to drastically outstrip supply—a clear sign, in his view, that the industry is nowhere near meeting actual demand.
Ives has curated a list of 10 companies he believes possess “structural advantages” in the AI economy, spanning semiconductors, hyperscale cloud providers, consumer electronics, cybersecurity, and autonomous driving.
Notably absent from this core list are tech giants like Amazon (AMZN), Salesforce (CRM), IBM (IBM), and Intel (INTC). Ives clarifies this is not a bearish call on these companies—they are still included in his broader “AI 30” watchlist. However, he believes they currently lack what he defines as “category-defining AI innovation leverage,” positioning them in more supportive, rather than foundational, roles.
Ives forecasts that AI-driven capital expenditures will surge to $550-$600 billion by 2026, with successive waves of spending expected from governments and enterprises. He stresses that less than 5% of U.S. companies have deployed AI at scale, meaning most investors are still underestimating what lies ahead.
Using his now-famous analogy, Ives concluded, “If this AI party goes until 4 a.m., it was 9 p.m. a year ago. Now it’s about 10:30 p.m…. and the bears are still watching from outside the window.”
