The surge in AI innovation has pushed venture capital into unfamiliar territory, and the usual benchmarks for judging a startup no longer apply. At TechCrunch Disrupt 2025, several high-profile investors stated that the industry has entered a unique, hyper-accelerated moment, one where traditional investing logic no longer applies.
Aileen Lee, founder of Cowboy Ventures, captured the energy perfectly. She told the audience that VC investment in AI startups is happening in a market where companies can suddenly rocket from zero to massive revenue within a matter of months. That kind of pace breaks the models VCs have used for decades.
Why the Usual Metrics Don’t Fit AI Startups Anymore
Lee explained that Series A investors aren’t just staring at revenue curves. Instead, they’re evaluating a new blend of inputs:
- Is the company generating high-quality proprietary data?
- Does the product create a defensible moat?
- Does the founding team have deep technical credibility?
- Is the product evolving fast enough to stay ahead?
She described it as a new algorithm with new variables, and each AI startup outputs a different answer.
This shift is redefining VC investment in AI startups, making the fundraising process unpredictable but also full of possibilities.
Jon McNeill, co-founder of DVx Ventures, said something many founders won’t want to hear: even AI startups that hit early revenue milestones are struggling to secure follow-on rounds.
He argued that investors have raised the bar across every stage of the process. Metrics once expected at Series B are now being applied to seed deals. It's a sign of how seriously the industry is treating the AI wave and how cautious capital has become despite the hype.
McNeill added that while strong tech matters, breakout winners usually succeed because they build an exceptional go-to-market strategy, not because they had the “best” model.
But Some VCs Say Great Tech Still Matters A Lot
Not everyone agreed. Kindred Ventures’ Steve Jang pushed back, saying founders shouldn’t assume clever marketing can compensate for mediocre engineering.
He argued that VC investment in AI startups is only effective when top-tier technology is paired with a strong go-to-market plan. In other words, AI founders must excel at both; there are no shortcuts.
One theme united the entire panel: the pace of shipping matters more than ever.
Aileen Lee highlighted the aggressive pace at which companies like OpenAI and Anthropic release updates. That cadence has become the standard, and AI startups must keep up if they want to stay relevant.
Investors now expect founders to ship features, improvements, and experiments at a blistering speed, without sacrificing quality.
This expectation is reshaping hiring, product cycles, and even how teams structure themselves internally.
The AI Race Has No Clear Winners Yet
Despite the intensity of the moment, the panellists agreed that the industry is still in its early innings. Even the most prominent players don’t feel invincible.
“There are no outright winners in AI yet,” Jang said. “Every leader has challengers catching up fast.”
That uncertainty is precisely why VC investment in AI startups continues to evolve. New contenders show up weekly, and the gap between a newcomer and a market leader can vanish faster than ever before.
