The Inevitability No One Sees | $11 Billion Tech Manager on What Investors Miss About AI
The Inevitability No One Sees | $11 Billion Tech Manager on What Investors Miss About AI  
Podcast: Excess Returns
Published On: Mon Apr 06 2026
Description: This episode of Excess Returns features Tony Wang of T. Rowe Price discussing how investors can identify “inevitabilities” in technology and position portfolios to benefit from long-term innovation trends. The conversation explores AI, semiconductors, and the evolving investment landscape, while also breaking down Tony’s portfolio construction process and how he navigates cycles, valuation, and disruption risk.Tony explains why AI is fundamentally changing the cost of intelligence, how agentic systems could reshape software and labor markets, and why the current AI buildout may differ from past tech cycles. The discussion also dives into where we are in the AI cycle, how to think about the Mag 7, and what investors may be missing across the tech stack.T. Rowe Price Science and Technology Fundhttps://www.troweprice.com/financial-intermediary/us/en/investments/mutual-funds/us-products/science-and-technology-fund.htmlTopics CoveredWhat it means to invest in “inevitabilities” and separating signal from noise in marketsWhy AI and compute demand represent a structural shift similar to past tech wavesThe rise of agentic AI and how it could transform software and productivityWhether AI is underappreciated or already priced into marketsThe “multiple moons” idea and why AI may not be a winner-take-all marketHow AI could reshape the labor market, productivity, and economic growthThe AI CapEx debate and why this cycle may differ from the dot-com buildoutWhere we are in the AI cycle: training vs inferencing and deployment phaseThe impact of AI on software companies and the innovator’s dilemmaHow semiconductors, memory, and infrastructure remain key bottlenecksThe changing nature of the Mag 7 and capital intensity in AITony’s portfolio construction framework across compounders, emerging tech, and valueHow he generates ideas using S-curve adoption and economic bottlenecksPosition sizing, risk management, and balancing growth with drawdown controlSell discipline: valuation, fundamentals, and market signalsTimestamps00:00 Introduction and Tony Wang overview01:05 Investing in inevitabilities and long-term thinking03:00 Differentiating inevitability from hype and consensus04:45 AI inevitability and the rise of agentic systems07:00 Cost of intelligence and productivity implications08:00 Real-world examples of AI adoption (customer service, agents)09:00 Is AI underappreciated by markets?11:15 AI as a “space race with multiple moons”13:30 AI as the dominant driver of markets today15:00 AI’s impact on jobs, productivity, and the economy18:30 Creativity, judgment, and the future of work20:45 Physical AI and robotics opportunity set22:30 AI CapEx debate vs the dot-com era25:30 Semiconductors vs software in the AI stack28:15 AI disruption risk for software companies31:00 Cyclicality in semiconductors and how AI changes it33:30 The evolving role of the Mag 7 in AI36:30 Competition, startups, and AI democratization38:00 Where we are in the AI cycle today40:00 Idea generation and S-curve adoption framework42:30 Case study: memory and AI bottlenecks44:45 Example position: optical networking and infrastructure46:40 Portfolio construction and position sizing49:00 Sell discipline and managing valuation risk