The evolving landscape of artificial intelligence (AI) is prompting investors to reconsider where value and opportunity will ultimately reside within the sector. While the AI revolution itself is broadly recognized as real, questions remain about which players will reap substantial returns amid the high costs of development and deployment.
Historically, major technological advances—from railways and electricity to the internet—have followed a distinct three-phase progression. Initially, innovation introduces a breakthrough technology. Next, infrastructure is developed to deliver that technology at scale. Only after these stages do the broad economic benefits shift to end-users who harness the new capabilities to transform industries and consumer experiences.
Railways initially rewarded promoters and operators who built the networks, but the largest economic gains were eventually realized by manufacturers, farmers, and retailers who accessed wider markets. Electricity, a classic example of a general-purpose technology, delivered its greatest productivity gains not through simply replacing steam engines, but by enabling fundamental redesigns of manufacturing processes around small electric motors. This transformation took decades to permeate the economy.
By analogy, AI’s full transformative impact may only emerge once it becomes ubiquitous and affordable—when tools like Claude or Perplexity are integrated into daily computing worldwide. At that point, while the chip manufacturers and data center operators will continue to benefit, greater value is expected to accrue to businesses and individuals leveraging AI to unlock new efficiencies and innovations.
The internal combustion engine illustrates how technological ripple effects can be unpredictable. Early beneficiaries included carmakers and related industries, but broader societal changes—such as suburbanization, shifts in shopping patterns, and growth in leisure sectors—ultimately reshaped entire economies. The internet revolution similarly followed this progression: initial returns favored infrastructure providers, but the real economic value migrated to users who deployed cheap bandwidth and computing power to create new services and markets. Companies like Amazon, Google, and Meta exemplify this shift, as do unexpected success stories like Domino’s, which transformed itself into a digital logistics leader.
GPS offers another instructive precedent. Once a scarce military technology, GPS became a widely accessible utility embedded in smartphones, enabling companies like Uber, Deliveroo, and Google Maps to capitalize on location intelligence—not the original equipment makers.
Applying these lessons to AI, investment opportunities can be viewed along three layers: innovators creating foundational technology, enablers providing infrastructure and tools, and adopters integrating AI into their operations. Exchange-traded funds (ETFs) now offer thematic exposure across these segments, with valuation multiples tending to decrease from innovators to adopters.
According to Tom Stevenson, an investment director at Fidelity International, a portfolio weighted toward adopters—companies effectively deploying AI—is likely to offer more sustainable value and a better entry point. These end-users stand to gain by combining abundant AI-generated intelligence with scarce competitive advantages such as proprietary data, trusted brands, customer relationships, human judgment, or unique physical assets that AI cannot easily replicate.
As AI matures from an emerging technology into a pervasive utility, investors and businesses alike face critical questions about how to capture value in an increasingly abundant intelligence economy.