AI Adoption: The Macro Shock of the Decade

In a short period, AI has advanced from novelty to an integral part of workflows, often matching or surpassing human performance in areas such as image classification, algorithm design, and data analysis.

Rapid Adoption Drives Infrastructure Demand

The rapid uptake and deployment of the technology require substantial infrastructure investment, including the construction of data centers, semiconductor facilities, and an energy grid capable of supporting AI’s significant computational demands. These prerequisites have created a geopolitical race to accelerate AI deployment in pursuit of potential growth opportunities. U.S. private-sector capital expenditures have exceeded $1 trillion on a trailing 12-month basis, the most pronounced post-pandemic investment surge among major economies. This positions the U.S. to achieve earlier and potentially more rapid productivity gains.

Productivity Is Not the Only Factor

While productivity gains may be on the horizon, we believe it’s key to look beyond early productivity gains to see which firms and sectors can turn technological advantage into lasting market power. As adoption expands, the impact on productivity and competitive dynamics will become more visible. We expect the market to shift focus from who is building and using AI to who can truly capture value from AI.

AI lowers the cost of accessing and transforming information, reducing the scarcity that underpins information-based competitive advantages. Sectors whose advantages stem from physical assets, regulatory barriers, or network effects may find their advantages preserved, and AI-related productivity gains in these sectors could more likely accrue to shareholders. Sectors that rely heavily on information processing, such as software, search engines, and health care diagnostics, could see competitive dynamics intensify as AI levels the playing field. Several large, public companies have already faced market concerns over how generative AI may negatively affect their existing business models.

Tapping Unmet Demand

AI-driven shifts in profit margins are only part of the story; another part of the story lies in demand. As the price falls, demand for a given good or service typically rises. Even sectors facing margin and price compression due to AI may still see an increase in overall profits — if the rise in demand outweighs the decline in prices.

Over time, as AI boosts productivity and lowers prices, aggregate real incomes could rise — potentially driving further outsized demand in some sectors. Health care, for example, is a sector with significant unmet demand. Most people want good health care, but many can’t afford it. Lower-cost diagnostics and treatments would likely drive volume growth, potentially boosting overall profits.

Dynamics That Determine Durability

The biggest beneficiaries of AI adoption won’t simply be the fastest adopters. Winning firms will likely leverage two advantages: strong productivity gains even after widespread adoption and the ability to capture unmet demand where lower prices translate into higher volumes. Sectors that pair these two dynamics together can become important plays in the AI theme. While information technology remains a favored sector under this framework, it also faces significant disruption with wide dispersion between winners and laggards.

FOR INSTITUTIONAL, PROFESSIONAL, QUALIFIED INVESTORS AND QUALIFIED CLIENTS ONLY.

CAPITAL MARKET ASSUMPTIONS

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GU-793 - 15 February 2027