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Built Different.



The AI Value Chain Strategy is built around a simple premise: not every company participating in artificial intelligence will benefit equally.

Rather than relying on market-cap weighting or broad sector classifications, the portfolio evaluates businesses according to the role they play within the broader AI ecosystem. Our research focuses on where adoption is occurring, where capital is being deployed, and where economic value may accrue as artificial intelligence becomes more deeply integrated into the economy.

ARCHITECTURE The AI Value Chain Exposure across multiple layers of the AI economy. FOUNDATION MONETIZATION Applications Software, cybersecurity, automation, and enterprise solutions. Compute & Networking Data centers, networking, storage, and supporting infrastructure. Semiconductors Chip makers, equipment suppliers, foundries, and memory producers. Infrastructure Power systems, energy equipment, and supporting physical assets. Each layer builds on the one beneath it — from the power AI runs on to the software that monetizes it. MILLENNIUM CAPITAL MANAGEMENT

Full-Stack Coverage - Targeted Exposure

Artificial intelligence depends on more than software applications. The strategy is not built around predicting which AI application, model, or technology will attract the most attention. Instead, it focuses on understanding the economic structure beneath the technology itself. Our research examines where capital is being deployed, which businesses are enabling adoption, and where economic value may accrue. The goal is not to chase headlines. It is to identify businesses positioned to benefit from long-term adoption.

The strategy seeks exposure across multiple layers of the AI value chain:

Infrastructure

Power systems, energy equipment, and supporting physical assets. These often become critical constraints as AI adoption expands, creating demand before benefits are visible elsewhere in the ecosystem.

Semiconductors

Chip manufacturers, equipment suppliers, foundries, and memory producers that enable the computing capacity required for AI workloads.

Compute & Networking

Data centers, networking systems, storage platforms, and supporting infrastructure that allow AI systems to operate reliably and at scale.

Applications

Software platforms, cybersecurity providers, automation tools, and enterprise solutions where AI adoption may ultimately translate into productivity gains, revenue growth, and profitability. By maintaining exposure across multiple layers of the ecosystem, the portfolio seeks to participate in broader AI adoption rather than relying on a single technology, application, or company.


Research & Portfolio Construction

Inclusion in the portfolio requires more than thematic relevance. Each holding is evaluated based on its role within the AI ecosystem, business quality, financial strength, growth potential, competitive positioning, and valuation.

The strategy is actively managed, and allocations are adjusted as industry conditions, valuations, and capital flows evolve. The objective is not broad exposure to every aspect of artificial intelligence, but selective exposure to businesses we believe are positioned to benefit from its long-term adoption.

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