T. Rowe Price's Tony Wang talks how T. Rowe price is playing volatile Big Tech stocks

Key Concepts

• Agentic AI: AI systems capable of autonomous action and decision-making, representing a key driver of future value.
• ROIC (Return on Invested Capital): A key metric for evaluating the profitability and efficiency of investments, expected to gain clarity in 2026.
• Cloud Code/Natural Language Coding: Utilizing natural language (like English) to write code, democratizing software development and boosting productivity.
• Platform vs. Feature: Distinguishing between companies providing foundational AI platforms versus those offering AI-powered features, with platforms being more resilient to disruption.
• Semiconductor Supply Chain Bottlenecks: Identifying areas within the semiconductor industry experiencing constraints that present investment opportunities.
• Custom ASIC Competition: Competition in the development of Application-Specific Integrated Circuits (ASICs) tailored for AI workloads, impacting NVIDIA’s margins.

AI Investment Outlook & Portfolio Strategy – T. Rowe Price Science & Technology Fund

Introduction

This discussion features Tony Wong, manager of the T. Rowe Price Science & Technology Fund, analyzing the current state of the AI investment landscape. The fund’s top holdings include NVIDIA, Microsoft, Broadcom, Alphabet, and Apple, with a significant 25% allocation to software companies. The conversation centers on the recent underperformance of some key holdings, the future of the AI trade, and the importance of identifying companies positioned to benefit from the continued adoption of AI, particularly “agentic AI.”

I. The AI Trade & Agentic AI

Wong believes the crucial factor for continued success in the AI sector is the “continuation of adoption,” specifically focusing on agentic AI. He defines this as the ability to leverage “digital labor” to automate tasks, ultimately benefiting companies currently held in the fund. However, he anticipates potential new leaders emerging, particularly in the semiconductor supply chain, where bottlenecks are creating opportunities for value capture. He notes that while current leaders may face challenges, the overall trend of AI adoption remains strong.

II. NVIDIA’s Valuation & Competitive Landscape

The discussion addresses NVIDIA’s recent trading range and valuation. Despite strong earnings growth (50% expected growth in earnings and sales) and potentially improving margins, the stock has struggled to maintain upward momentum. Wong argues that NVIDIA is “relatively inexpensive” given its earnings growth, but acknowledges market concerns regarding gross margin sustainability and custom ASIC competition.

He explains that the market is currently “recalibrating” capital allocation within the semiconductor sector, shifting focus to areas experiencing more immediate bottlenecks and growth. He believes NVIDIA’s valuation will become “really interesting” as these factors resolve, and remains optimistic about the company’s long-term prospects, particularly with new generations of technology.

III. Return on Invested Capital (ROIC) & Productivity Gains

Wong predicts that clarity regarding Return on Invested Capital (ROIC) will emerge in 2026, but acknowledges it will be unevenly distributed. He highlights the transformative potential of Cloud Code, describing English as “the new coding language.” This shift is expected to dramatically alter work processes, application development, and overall productivity, effectively “uncapping labor.”

He points to increased usage of tools like ChatGPT as evidence of rising intelligence and the democratization of technology, contributing to observable increases in GDP. He states, “I think a lot of that is due to AI productivity.”

IV. Software Disruption & Platform Strategy

The conversation addresses concerns about AI potentially replacing software and impacting software company valuations. Despite a 25% portfolio allocation to software, Wong emphasizes the importance of investing in companies that serve as the “ultimate platform” for agentic AI.

He argues that companies offering merely AI-powered features are vulnerable to disruption by platforms or new entrants. He notes that the cost of software development has “gone down tremendously” due to generative AI and coding agents like ChatGPT, making it easier to build software on top of robust platforms.

V. Semiconductor Supply Chain & Bottlenecks

Wong identifies bottlenecks within the semiconductor supply chain as key areas for investment. He believes that companies addressing these constraints will capture significant value as AI adoption increases. This suggests a potential shift in investment focus beyond the established leaders like NVIDIA, towards companies enabling the broader AI ecosystem.

Notable Quotes

• “I think that what really matters in AI is the continuation of adoption and specifically agentic AI.” – Tony Wong
• “English is kind of the new coding language.” – Tony Wong, highlighting the impact of Cloud Code.
• “If you’re a feature, it’s super easy for you to be disrupted by the platform.” – Tony Wong, emphasizing the importance of platform companies.

Conclusion

Tony Wong presents a nuanced view of the AI investment landscape. While acknowledging short-term underperformance in some key holdings, he remains optimistic about the long-term potential of AI, particularly agentic AI. His strategy focuses on identifying companies positioned to benefit from continued adoption, emphasizing the importance of platform businesses, and recognizing emerging opportunities within the semiconductor supply chain. He anticipates increased clarity on ROIC in 2026 and believes AI-driven productivity gains are already contributing to economic growth. The key takeaway is a shift towards identifying foundational AI platforms and companies addressing critical bottlenecks in the AI ecosystem.