Legendary venture capitalist Vinod Khosla has revealed his unique approach to determining whether the artificial intelligence industry is experiencing a bubble, and it has nothing to do with volatile stock prices. In a recent episode of OpenAI’s podcast, Khosla explained that he measures the AI bubble by tracking API (Application Programming Interface) calls rather than market valuations.
Khosla, whose portfolio includes major AI investments like OpenAI, DoorDash, and Block, argued that stock prices merely reflect “fear and greed among investors” and are unreliable indicators of true market health. Instead, API calls—the process where software applications communicate to request data or trigger actions—provide a more accurate measure of actual AI usage and demand. “If that’s your fundamental metric of what’s the real use of your AI, usefulness of AI, demand for AI, you’re not going to see a bubble in API calls,” the 70-year-old investor stated.
Drawing parallels to the dot-com era of the 1990s, Khosla noted that he monitored internet traffic as his key metric during that period, and API calls serve the same purpose for evaluating AI’s real-world adoption today. He dismissed Wall Street’s tendency to swing between extremes, noting how investors can go “from loving Nvidia to hating Nvidia” in a single day based on valuation concerns.
The AI bubble debate has intensified significantly in recent months. According to AlphaSense analysis, the phrase “AI bubble” appeared in 42 earnings calls and investor conference transcripts between October and December 2025—a staggering 740% increase from the previous quarter. This surge reflects growing concerns about massive investments in AI infrastructure potentially outpacing actual returns.
Industry leaders remain divided on the issue. Microsoft cofounder Bill Gates acknowledged AI’s high value while admitting the industry is experiencing “a frenzy,” with some companies committing to expensive data centers they may regret. “Big Short” investor Michael Burry sounded more alarming notes, warning that tech giants like Microsoft and Alphabet are wasting trillions on microchips and data centers with “no clear path to utilization by the real economy.”
Conversely, Nvidia CEO Jensen Huang has firmly rejected bubble concerns, arguing that AI represents a fundamental transition in computing rather than overspeculation. His company reached a historic $5 trillion market cap in October, driven by AI chip demand.
Key Quotes
People equate bubble to stock prices, which has nothing to do with anything other than fear and greed among investors. So I always look at, bubbles should be measured by the number of API calls.
Vinod Khosla, the prominent venture capitalist with major AI investments including OpenAI, explained his fundamental approach to evaluating whether AI is overvalued. This statement challenges conventional market analysis by focusing on actual usage metrics rather than investor sentiment.
If that’s your fundamental metric of what’s the real use of your AI, usefulness of AI, demand for AI, you’re not going to see a bubble in API calls. What Wall Street tends to do with it, I don’t really care. I think it’s mostly irrelevant.
Khosla doubled down on his methodology, dismissing Wall Street’s volatility as irrelevant to AI’s true value. This perspective suggests confidence that actual AI usage remains strong despite market fluctuations and valuation concerns.
We also know that AI has become good enough because of reasoning capability, and research capability, its ability to think — it’s now generating tokens and intelligence that is worth paying for.
Nvidia CEO Jensen Huang defended the AI industry against bubble accusations, arguing that AI has reached a maturity level where it delivers genuine value. His company’s $5 trillion valuation depends on sustained AI infrastructure demand, making his perspective particularly significant.
But you have a frenzy. And some of these companies will be glad they spent all this money. Some of them, you know, they’ll commit to data centers whose electricity is too expensive.
Microsoft cofounder Bill Gates acknowledged both AI’s value and the existence of speculative excess. His nuanced position suggests that while AI is transformative, not all investments will prove wise, particularly those with unsustainable cost structures.
Our Take
Khosla’s API-focused approach represents a refreshing return to fundamentals in an industry often driven by hype. His methodology echoes Warren Buffett’s value investing principles—look at actual usage and utility rather than market sentiment. The dramatic 740% increase in bubble discussions suggests the market is reaching an inflection point where companies must demonstrate real returns on AI investments.
What’s particularly telling is the split among tech luminaries. Huang’s dismissal of bubble concerns is understandable given Nvidia’s position as the primary AI infrastructure provider, while Burry’s warnings about obsolescence raise legitimate questions about the sustainability of current spending levels. The truth likely lies between these extremes: AI is transformative and generating real value, but not every investment will pay off, and some infrastructure will indeed become stranded assets. Khosla’s metric offers a practical way to separate signal from noise in this critical debate.
Why This Matters
This debate over AI valuation metrics carries profound implications for the technology industry’s future trajectory. Khosla’s focus on API calls as a fundamental measure represents a shift toward usage-based evaluation rather than speculation-driven market sentiment. This approach could influence how investors, analysts, and companies assess AI’s true value and sustainability.
The 740% surge in “AI bubble” mentions during earnings calls signals that corporate leaders are grappling with justifying massive infrastructure investments. Companies have poured hundreds of billions into AI data centers, chips, and research, and stakeholders are increasingly demanding evidence of tangible returns. If Khosla’s metric gains traction, it could pressure AI companies to demonstrate real-world adoption through measurable usage data rather than relying on future promises.
For businesses and workers, this discussion matters because it will determine the pace and sustainability of AI integration. A genuine bubble burst could slow AI development and deployment, while sustained API growth would validate continued investment. The outcome will shape job markets, business strategies, and the broader economic impact of artificial intelligence for years to come.
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Source: https://www.businessinsider.com/vinod-khosla-looks-at-this-metric-to-gauge-ai-bubble-2026-1