Excess Returns· Staffel 1· Folge 435

The Inevitability No One Sees | $11 Billion Tech Manager on What Investors Miss About AI

Montag, 6. April 2026 · 1 h 03

MP3

Shownotes

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 Fund
troweprice.com/financial-intermediary/us/en/in… Covered
• What it means to invest in “inevitabilities” and separating signal from noise in markets

• Why AI and compute demand represent a structural shift similar to past tech waves

• The rise of agentic AI and how it could transform software and productivity

• Whether AI is underappreciated or already priced into markets

• The “multiple moons” idea and why AI may not be a winner-take-all market

• How AI could reshape the labor market, productivity, and economic growth

• The AI CapEx debate and why this cycle may differ from the dot-com buildout

• Where we are in the AI cycle: training vs inferencing and deployment phase

• The impact of AI on software companies and the innovator’s dilemma

• How semiconductors, memory, and infrastructure remain key bottlenecks

• The changing nature of the Mag 7 and capital intensity in AI

• Tony’s portfolio construction framework across compounders, emerging tech, and value

• How he generates ideas using S-curve adoption and economic bottlenecks

• Position sizing, risk management, and balancing growth with drawdown control

• Sell discipline: valuation, fundamentals, and market signals

Timestamps
Introduction and Tony Wang overview
Investing in inevitabilities and long-term thinking
Differentiating inevitability from hype and consensus
AI inevitability and the rise of agentic systems
Cost of intelligence and productivity implications
Real-world examples of AI adoption (customer service, agents)
Is AI underappreciated by markets?
AI as a “space race with multiple moons”
AI as the dominant driver of markets today
AI’s impact on jobs, productivity, and the economy
Creativity, judgment, and the future of work
Physical AI and robotics opportunity set
AI CapEx debate vs the dot-com era
Semiconductors vs software in the AI stack
AI disruption risk for software companies
Cyclicality in semiconductors and how AI changes it
The evolving role of the Mag 7 in AI
Competition, startups, and AI democratization
Where we are in the AI cycle today
Idea generation and S-curve adoption framework
Case study: memory and AI bottlenecks
Example position: optical networking and infrastructure
Portfolio construction and position sizing
Sell discipline and managing valuation risk

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