Top AI investors say the AI bubble is good for innovation despite inflated valuations

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Leading venture capitalists Steve Jang of Kindred Ventures and Cathy Gao of Sapphire Ventures argue that the AI bubble, while real, is essential for driving innovation. Speaking at Fortune Brainstorm AI conference, they explained how market excitement attracts top talent from tech giants and secures capital for ambitious AI projects, even as concerns about inflated valuations grow.

AI Investors Defend the Bubble as Innovation Catalyst

The current state of the AI market has sparked intense debate about whether we're witnessing a dangerous bubble, but two prominent AI investors are making a counterintuitive case: the AI bubble might be exactly what the industry needs. At the Fortune Brainstorm AI conference, Steve Jang of Kindred Ventures and Cathy Gao of Sapphire Ventures confronted the question head-on, arguing that while inflated valuations exist, the market heat is functionally necessary for breakthrough innovation

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Source: Fortune

Source: Fortune

"I think it is a bubble, but bubbles are good for innovation," Jang stated, framing the term as finance shorthand for a "new technology wave" that occurs every five to seven years

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. According to Jang, this market excitement serves a dual purpose: attracting the world's best talent to work on critical problems while generating the capital needed to fund ambitious projects. The talent migration to startups from stable roles at tech giants like Google, Meta, and Uber represents a "good signal" rather than a warning sign, he argued

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Valuations Exceed Fundamentals But Growth Curves Are Unprecedented

Gao acknowledged that in certain pockets, valuations have far outstripped fundamental metrics, but she cautioned against dismissing the trend entirely

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. The growth curves of current AI companies "far outstrip the growth curves of companies we've ever seen before," making the total addressable market difficult to calculate, she explained. "I don't think we have a good sense of how big some of these companies can ultimately become," Gao added, suggesting that traditional valuation frameworks may not adequately capture the potential scale of AI-driven businesses

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This perspective contrasts sharply with recent warnings from other industry figures. Investor Michael Burry and Google DeepMind CEO Demis Hassabis have flagged overvaluation risks, with Burry criticizing overspending on data centers without real demand and Hassabis questioning how some AI startups raised tens of billions before launching products

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. Hassabis noted that AI was "overhyped in the short term" but underappreciated in the medium to long term, reflecting how hype often inflates valuations rapidly

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AI Infrastructure and Enterprise Applications Emerge as Strategic Focus Areas

The two investors outlined divergent strategies for navigating a potential market correction. Jang emphasized that in a true technology wave, "the whole stack changes," creating opportunities from the bottom up

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. Kindred Ventures is focusing heavily on AI infrastructure, including chips, GPU marketplaces, cloud systems, and specialized frontier models. Despite new entrants, margins remain high for cloud and chip providers, giving them "pricing power on all of the application-layer companies," Jang observed

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Gao, who concentrates primarily on enterprise applications, offered a stricter framework for survival. "Let's get real: AI is no longer a differentiator," she warned, noting that "AI for X" companies are vulnerable

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. Instead, she looks for companies transitioning from simple features to complex workflows that embed deeply into enterprise operations. "In the future, it's just going to be a customer support workflow tool, and every company will be powered by AI," Gao said, arguing that despite volatility, "first-mover advantage is actually real" in the enterprise sector, citing the enduring dominance of Salesforce and Workday from the cloud era

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Robotics Startups Face Heartbreak as Models Evolve

The conversation took a cautionary turn regarding robotics startups, with Jang offering a "spicy" prediction that many current ventures are building on "primitive models" roughly equivalent to the "GPT 3.5 phase" of robotics

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. "A whole bunch of robotics startups ... are going to have a lot of heartbreak when the models improve and they've built for something sort of in the past," Jang predicted

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Source: Benzinga

Source: Benzinga

He added that many consumer robotics companies will likely "fall by the wayside" because societal and governmental adoption cycles will be too long for startups to survive.

Jang emphasized the deep technical challenges ahead, noting that humanoid robots will need to prove they won't malfunction while moving around offices, households, or streets. "Every part of the physical world is going to have to prepare for humanoid robots potentially malfunctioning. Think about that. And that is a deep tech problem," he stressed

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Trust and Visibility Remain Unresolved for Enterprise Sales

Looking toward 2026, Gao offered her own forecast: despite better models, enterprise sales are "going to be even more difficult"

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. She cited unresolved issues regarding trust and visibility as hurdles the industry has yet to clear. "People are going to be more focused on trust and visibility, and we haven't really solved that problem yet," Gao warned

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. This challenge could determine which companies successfully embed AI into enterprise workflows and which struggle to gain traction despite technical capabilities.

Jang suggested that as long as the media continues to question whether we're in a bubble, it helps "release pressure" and keeps the ecosystem healthy, potentially preventing a catastrophic market correction

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. While both investors acknowledged that "bubbles popping are bad," they maintained that the current market dynamics are essential for attracting capital and talent to solve the most pressing technical challenges in artificial intelligence.

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