Lee McCabe Compares Today’s AI Hype to the Dot-Com Boom

In a recent LinkedIn post, Lee McCabe draws a striking parallel between the current artificial intelligence (AI) surge and the dot-com boom of the late 1990s. McCabe, a figure in the venture capital and private equity space, argues that while the underlying potential of AI is immense, the current market is characterized by a similar pattern of inflated expectations, buzzword-driven investment, and foundational weaknesses that ultimately led to the dot-com crash.

McCabe elaborates on this comparison, noting the rapid proliferation of AI claims across industries. He writes:

“AI today feels like the dot-com boom on steroids. The pattern is almost identical, only faster, louder, and with more zeroes. In 1999, we had people registering random domain names and raising millions because they had a “web business plan.” No product, no revenue, just a buzzword and a slide deck. Sound familiar? Now it’s AI. Every company suddenly “powered by AI.” Every VC deck dripping with references to “transformative machine learning.” Every incumbent rushing to sprinkle “AI-enhanced” across their website like it’s SEO in 2007.”

The Foundation Problem: Data Over Hype

A key point of comparison McCabe highlights is the critical role of infrastructure. Just as the early internet struggled with inadequate bandwidth and nonexistent infrastructure, he posits that today’s AI development is hampered by a shaky data foundation.

“Today’s equivalent is data. Everyone’s building on shaky data foundations. You can’t run great AI on garbage data any more than you could stream Netflix over a 56k modem,” McCabe explains. This suggests that the focus on superficial AI applications, rather than robust data pipelines, mirrors the dot-com era’s emphasis on domain names over functional websites.

Beyond the Gimmicks: The Infrastructure Play

McCabe distinguishes between the current wave of consumer-facing AI applications and what he believes will be the more impactful, long-term developments. He categorizes the initial wave as consisting of “consumer gimmicks” like AI-generated headshots and basic chatbots.

The Second Wave: Real-World Impact

According to McCabe, the true value will emerge from a “quiet second wave” focused on infrastructure, tooling, and vertical integration. He predicts that the ultimate winners will not be companies solely selling AI, but rather those that leverage AI to deliver tangible outcomes in specific industries.

He provides examples of these future leaders:

• Insurance firms using AI for real-time risk pricing.
• Manufacturers employing AI for predictive maintenance.
• Retailers automating pricing based on complex data signals.
• Hospitals integrating AI diagnostics into clinical workflows.

McCabe emphasizes that these companies will sell results, not the technology itself. He draws parallels to Amazon’s early focus on logistics and data infrastructure, and Salesforce’s pioneering of SaaS, suggesting that the next decade of AI will follow a similar pattern of building foundational capabilities.

“Most of today’s “AI startups” will vanish……not because AI failed, but because they mistook the technology for the product,” McCabe writes. “The eventual giants will use AI the way we use electricity: invisibly, everywhere, and never as the selling point.”

Lessons from Tech History

McCabe concludes by reiterating that the current AI landscape, while noisy and marked by high valuations, is akin to the early stages of the internet. He advises that the real progress is being made by those focused on building the essential infrastructure, much like the companies that laid the groundwork for the internet’s widespread adoption.

“History doesn’t repeat, but in tech, it rhymes so loudly you can hear it through the servers,” he states, underscoring the cyclical nature of technological innovation and market enthusiasm.