TL;DR

PwC’s 2026 AI Performance study reveals that nearly three-quarters of AI’s economic value is captured by just one-fifth of organisations. The research, based on interviews with 1,217 senior executives across 25 sectors, finds that leaders are using AI for business reinvention rather than just cost reduction — and the gap is widening.

What separates AI leaders from the rest

The top-performing companies in PwC’s study are not simply deploying more AI tools. They are using AI as a catalyst for growth and business model reinvention, particularly by pursuing revenue opportunities created as industries converge.

The research identifies industry convergence — using AI to expand beyond traditional sector boundaries — as the single strongest factor influencing AI-driven financial performance, ahead of efficiency gains alone. Leaders report being nearly twice as likely to use AI in advanced ways: executing multiple tasks within guardrails (1.8 times more likely) or operating in autonomous, self-optimising modes (1.9 times).

Automation and trust

AI leaders are increasing the number of decisions made without human intervention at almost three times the rate of their peers. This automation is enabled by what PwC calls “trust at scale” — structured frameworks including responsible AI governance boards (1.5 times more likely) and formal responsible AI frameworks (1.7 times).

The payoff is measurable: employees at leading companies are twice as likely to trust AI outputs, creating a virtuous cycle where trust enables automation, which enables further scaling.

The pilot trap

The study’s sharpest finding is about the majority. Many companies are busy rolling out AI pilots but failing to convert activity into measurable financial returns. Without a shift in approach — from cost reduction to growth, from experimentation to scaled deployment — the performance gap between leaders and laggards will continue widening.

Looking forward

For UK businesses assessing their AI strategy, PwC’s research provides a clear diagnostic: are you pointing AI at growth or just efficiency? The 74/20 split suggests that incremental AI adoption without business model ambition may not be enough to remain competitive as the leaders pull further ahead.