When BestBrokers classified all 503 constituents of the S&P 500 by their role in the AI value chain, the result mapped a technology shift that has reached well beyond chipmakers and software developers. From power utilities to optical component suppliers, AI infrastructure now runs through industries once considered insulated from the technology sector.
The analysis places 218 companies inside the AI economy as of July 2026, a 474% increase from the 38 considered AI-linked in 2024. Together they carry a market capitalisation of $42.39 trillion, accounting for 62.04% of the entire index's value. A tighter core of 58 companies, those building AI chips, models, software, and security, are alone worth $32.2 trillion and represent 47.13% of index weight.
By category, AI Chips and Hardware Suppliers form the largest group by market value. The 28 companies in this segment, including Nvidia, Broadcom, Micron Technology, and AMD, are collectively worth $12.39 trillion, or 18.14% of the index. AI Cloud and Model Providers, comprising five hyperscalers, Amazon, Microsoft, Oracle, Meta, and Google, account for a further $11.74 trillion at 17.18% combined weight.
AI Energy and Power Infrastructure has become the largest category by company count, with 58 businesses now classified within it. AI data centre electricity demand has drawn in utility and industrial companies that would not have appeared in any technology basket two years ago; their combined market value of $4.11 trillion, roughly 6% of the index, reflects the sector's lower margins relative to software and chips despite its scale.
The top performing AI-linked stocks over the past two years span the full infrastructure stack rather than concentrating in frontier model developers: Lumentum Holdings gained 1,194.6%, Western Digital 788.7%, Seagate 668.4%, Micron 615.3%, and AppLovin 524.8%.
BestBrokers notes in its methodology that the 218 companies are those where AI represents a material part of their products, infrastructure role, business strategy, or investment thesis, rather than simply firms that have adopted AI tools internally. The distinction matters because most large businesses now deploy AI in some operational capacity.
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