Similar to the early days of past technological revolutions, market performance has so far centered on the builders and enablers of the innovation. But as adoption expands, the technology’s impact on productivity and competitive dynamics will become more visible. We expect the market to shift focus from who is using AI to who can truly capture value from AI.
A common assumption is that companies and sectors benefiting from AI-driven productivity gains will see the greatest increase in profits. The logic is straightforward: As productivity rises, costs fall, and corporate profits should rise accordingly.
Productivity gains are a useful starting point, but higher productivity growth alone is rarely enough to deliver sustained increases in profitability. For many sectors, competition often turns productivity gains into lower prices and/or higher wages. Capacity expansion and new entrants to highly profitable areas also tend to erode returns on capital. The ability of a firm to capture AI-driven productivity gains will depend in large part on its market power. Companies in less competitive markets are the ones most likely to keep a meaningful share of productivity gains as profits.
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 healthcare 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.
AI-driven shifts in profit margins are only part of the story; another part of the story lies in demand. As prices fall, demand for a given good or service typically rises. This can often unlock new markets and bring previously out-of-reach products or services within reach of more consumers.
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. Healthcare, for example, is a sector with significant unmet demand. Most people want good healthcare, but many can’t afford it. Lower-cost diagnostics and treatments would likely drive volume growth, potentially boosting overall profits.
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, making careful selection essential.
Head of Economic Research
BNY Investment Institute
Definitions:
Artificial intelligence (AI) refers to computer systems that can perform tasks typically requiring human intelligence, such as visual perception, speech recognition, decision-making, and language translation.
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