Where AI Will Create Value—And Where It Won’t

Why It Matters

The insight redirects capital from short‑term efficiency projects toward long‑term strategic innovation, a shift that will determine winners in AI‑driven markets. Companies that master differentiation and transaction‑cost reduction will capture expanding profit pools while others risk commoditization.

Key Takeaways

• 90% of firms use AI, but 94% see no significant value.
• Productivity gains reset cost baselines but rarely expand profit pools.
• AI‑driven differentiation hinges on data, network effects, and new business models.
• Reducing transaction costs can dismantle intermediaries and favor modular ecosystems.
• Early AI adopters can lock in lower‑cost positions before rivals catch up.

Pulse Analysis

The AI productivity paradox mirrors the classic Solow paradox: widespread adoption without a clear lift in output. By the end of 2025, surveys show almost nine‑in‑ten companies have AI in at least one function, yet 94 percent see no "significant" return. Early adopters that embed AI across whole processes—such as Siemens’ predictive‑maintenance platform or Amazon’s robot‑fleet orchestration—can temporarily reset industry cost baselines. However, these gains are defensive; as rivals catch up, the cost advantage erodes, leaving little room for durable profit expansion.

True competitive moats will emerge from AI‑enabled differentiation rather than efficiency alone. Companies that embed large‑language models into core offerings—think Uber’s dynamic dispatch, legal‑tech firm Harvey’s AI‑augmented counsel, or Khanmigo’s personalized tutoring—create new value propositions that reshape customer economics. Proprietary data, network effects, and rapid iteration cycles become the new sources of advantage, allowing firms to expand profit pools through novel products, services, and platform ecosystems. Early movers that lock in these capabilities can command higher margins and build barriers that persist even as the underlying AI technology commoditizes.

The most disruptive wave lies in transaction‑cost reduction, a concept McKinsey dubs the "Coasean singularity." AI agents can automate search, negotiation, coordination and enforcement at near‑zero marginal cost, undermining traditional intermediaries and the scale advantages they once provided. As friction disappears, markets may fragment into modular networks where specialized firms compete on niche expertise rather than size. Companies that position themselves at the new control points—owning the customer interface, data pipelines, or AI orchestration layer—stand to capture the reallocated value. Strategists must therefore map where AI will slash transaction costs and redesign their operating models to occupy those emerging hubs of influence.