Cathie Wood on What Comes Next in AI and Big Tech

Episode Summary

Executive Summary: The episode is a live Odd Lots interview with Kathy Wood at Bloomberg Invest, centered on her bullish view of AI, open source models, Tesla, robotics, and healthcare innovation. She argues that recent tech selloffs reflect macro fear, not weak fundamentals, and predicts an era of broadening market leadership, rising productivity, and major deflationary pressure from AI-driven disruption.

Main Topics: AI adoption and DeepSeek/open-source competition (Priority: 5/5): Wood says DeepSeek was not a surprise to her team, emphasizes its open-source nature, and argues that open source is accelerating innovation rather than undermining the AI investment case. No evidence of an AI capex slowdown (Priority: 5/5): She rejects the idea that DeepSeek or recent market volatility has changed hyperscaler spending behavior, saying enterprises, governments, and schools are still aggressively adopting AI tools. Tesla, autonomy, and Elon Musk (Priority: 5/5): Wood defends Musk’s multi-company focus, highlights Tesla’s refreshed products and upcoming lower-cost model, and frames autonomous driving as the key to Tesla’s future economics. Market selloff, concentration, and macro fears (Priority: 4/5): She attributes recent tech weakness to fear, recession concerns, and an overly concentrated market, while arguing the post-election broadening of equities is healthy and likely to continue. AI’s impact on software and productivity (Priority: 4/5): Wood says AI is already pressuring software-as-a-service and making engineers more productive, which may reduce hiring even if layoffs are limited. Healthcare, robotics, and long-term innovation wave (Priority: 5/5): She sees the biggest gains from AI in autonomous vehicles and healthcare, especially where AI converges with sequencing and gene editing to drive a new golden age of R&D. Interest rates, valuations, and policy tailwinds (Priority: 4/5): Wood argues that higher rates, valuation headwinds, and regulatory barriers are easing, and that deregulation plus tax cuts could create a Reagan-like but larger innovation boom.

Key Arguments: DeepSeek did not change the long-term AI thesis; it reinforced the importance of open-source models and algorithmic progress. There is no observable slowdown in AI capital spending; major enterprises and institutions still believe AI is transformational. Open source models may trail closed models today, but their improvement slope is steeper, which supports faster competition and diffusion. AI is already making engineers more productive, reducing the need to hire additional workers even without broad layoffs. Software-as-a-service may lose share as AI-native applications emerge, while new companies in garages and R&D centers build the next wave. Autonomous taxis are the largest AI project on earth and could generate trillions in revenue over the next decade. Healthcare is the most profound AI opportunity because sequencing, AI, and CRISPR are already producing real cures. Tesla’s autonomous network could have software-like margins far above its current EV business, making the stock fundamentally different from a carmaker valuation. Recent market concentration in the Mag-6 is unhealthy; a broader market advance would be more durable. Deregulation, lower taxes, and a more competitive stance toward China could provide major policy support for innovation stocks. Wood expects inflation to surprise on the downside as AI, slowing velocity, and recessionary pressures work through the economy.

Data Points: DeepSeek build cost: $6 million - Wood references the market shock around claims that DeepSeek built its model very cheaply. GPU cluster size: 50,000 GPUs - She says DeepSeek apparently used a 50,000-GPU cluster for pre-training. Job type decline: coding employees in the United States has dropped “off a cliff” - Wood uses this to argue AI is boosting engineer productivity and reducing hiring needs. Tesla lower-cost model price: $30,000 or less - She says Tesla plans a cheaper vehicle in the first half of the year. Autonomous launch timing: June - Wood says Tesla is launching autonomy in Austin in June. Tesla autonomous gross margins: 70% to 90% - She argues Tesla’s autonomous platform could have SaaS-like economics. Tesla EV gross margins: mid-teens - She contrasts current EV economics with autonomy economics. Autonomous revenue opportunity: $8 trillion to $10 trillion - Wood says robo-taxis could generate this amount globally over 5 to 10 years. Healthcare returns on R&D today: 4% - She says broad pharma/biotech R&D returns are currently low. Healthcare returns on R&D in the 1980s: 30% - Wood cites Genentech-era returns as a historical benchmark. Potential future healthcare R&D returns: 30% to 40%+ - She expects AI and related tools to restore a golden age of healthcare innovation. Interest-rate shock: 24-fold increase in little more than a year - Wood describes the rate hiking cycle as a major headwind. Long-bond yield: 4.12% - She cites the move as a signal that real activity is cooling and rates are not heading higher. Market concentration: MAG-6 - She says post-election leadership broadened away from the dominant mega-cap group. Consumer and small-business stress: 30% net income decline - Wood says small businesses have seen net income fall about 30% over roughly three years.

Pivotal Quotes: "The most profound application of AI, we believe, is going to be in healthcare." — Kathy Wood: She explains where she sees the biggest long-term economic and scientific impact from AI. "The largest AI project on earth is robo-taxis, autonomous driving networks." — Kathy Wood: Wood frames autonomy as the central embodied-AI investment opportunity. "We think that the market will, it has started and will continue to broaden out." — Kathy Wood: She argues the recent concentration in mega-caps is unwinding into a healthier market structure.

Implications: Wood’s thesis implies that AI-driven productivity and autonomous/biotech breakthroughs could reshape equity leadership, pressure legacy software, and eventually lower inflation. For investors, she favors long-duration exposure to disruptive innovation over current market caution.