When evaluating AI startups, don't just consider the current product landscape. Instead, visualize the future state of giants like OpenAI as multi-trillion dollar companies. Their "sphere of influence" will be vast. The best opportunities are "second-order" companies operating in niches these giants are unlikely to touch.

The AI boom creates a cascading investment thesis. As component makers (e.g., memory stocks) see valuations soar, they will use their enriched stock as currency to invest heavily in their own supply bottlenecks, which are fundamental raw materials like rare metals and chemicals.

During the dot-com crash, application-layer companies like Pets.com went to zero, while infrastructure providers like Intel and Cisco survived. The lesson for AI investors is to focus on the underlying "picks and shovels"—compute, chips, and data centers—rather than consumer-facing apps that may become obsolete.

When a new technology stack like AI emerges, the infrastructure layer (chips, networking) inflects first and has the most identifiable winners. Sacerdote argues the application and model layers are riskier and less predictable, similar to the early, chaotic days of internet search engines before Google's dominance.

Instead of betting on which AI models or applications will win, Karmel Capital focuses on the infrastructure layer (neocloud companies). This "pick and shovel" strategy provides exposure to the entire ecosystem's growth with lower valuations and less risk, as infrastructure is essential regardless of who wins at the top layers.

Before AI delivers long-term deflationary productivity, it requires a massive, inflationary build-out of physical infrastructure. This makes sectors like utilities, pipelines, and energy infrastructure a timely hedge against inflation and a diversifier away from concentrated tech bets.

In 2026, the AI investment narrative will expand from foundational model creators to companies building applications and services. It also includes sectors enabling AI growth, such as energy generation and data centers, offering a wider range of investment opportunities beyond the initial tech giants.

Instead of chasing high-valuation, first-order AI players like GPU makers, THL focuses its investment thesis on second or third-degree beneficiaries. These companies provide critical, capital-light IP or embedded software that endures through tech cycles, offering better long-term value for middle-market investors.

Concerned about AI's potential to displace white-collar jobs, Wilkinson views investing in the underlying infrastructure as a key strategy. He specifically invested in a Bitcoin mining company pivoting to AI data centers, effectively buying into the "toll bridge" of the future to protect his capital.