From Anthropic to Waymo: Kleiner Perkins Bets on AI’s Next Act

Kleiner Perkins partner Ilya Fushman says AI remains in the early stages of reshaping the economy, with opportunities in frontier models, consumer agents, autonomous vehicles and robotics. He describes physical AI as a potential source of the next trillion-dollar companies and says he is increasingly optimistic about IPO and M&A markets; no specific company metrics or market moves are reported.

Analysis

The signal is more useful as a map of where venture capital may flow than as a near-term earnings catalyst. If AI moves from software into vehicles and robots, value can shift toward sensors, actuators, power management, edge compute and industrial automation—not accrue solely to model providers. But physical deployments carry longer validation cycles, integration costs and safety constraints; impressive demos may therefore translate slowly into recurring revenue. Incumbent manufacturers could benefit from automation while facing pressure to fund upgrades and defend labor or service advantages.

A healthier IPO/M&A window would improve exit optionality and private-company financing, but it would not by itself validate private valuations. Public-market read-through is strongest if listings clear at durable prices and transactions show strategic buyers paying for monetizable assets; weak issuance or withdrawn deals would reverse the sentiment quickly. Near term, this interview is unlikely to move fundamentals. Over 1–3 months, monitor IPO execution, announced deal terms and large-company AI capex conversion. Over 6–18 months, the key test is paid deployments and repeat orders in physical AI. The contrarian risk is that investors capitalize a broad “next trillion-dollar” narrative before unit economics and deployment timelines are observable.

Key Decisions for Investors

• No immediate trade on the interview alone. Treat it as a watch item, not independent evidence of revenue acceleration.
• For relative exposure, favor diversified industrial-automation and semiconductor supply-chain beneficiaries with demonstrable orders over speculative, single-product robotics exposure; verify backlog quality and customer concentration before adding.
• Track IPO pricing and aftermarket performance, completed M&A versus announced intent, and whether strategic buyers disclose measurable AI productivity or revenue gains. A deterioration in issuance or deal completion would weaken the private-market optimism thesis.
• Falsify the physical-AI thesis if paid pilots fail to convert into repeat deployments, customer adoption timelines lengthen, or relevant companies guide down orders/backlogs. Reassess only as company-level financial evidence emerges.