AI Performance survey April 2026

The global study interviewed 1,217 senior executives around the world including in Ireland, primarily at large, publicly listed companies across 25 sectors, asking them about the revenue and efficiency gains they are seeing from AI today, alongside questions about how they deploy the technology.

It finds that nearly three‑quarters (74%) of AI’s economic value is captured by just one‑fifth (20%) of organisations, revealing a stark and widening divide between a small group of AI leaders and the majority of businesses still stuck in pilot mode.

The research shows that these top‑performing companies are not simply deploying more AI tools. Instead, they are using AI as a catalyst for growth and business reinvention, particularly by pursuing new revenue opportunities created as industries converge, while building strong foundations around data, governance and trust.  AI leaders invest two and a half times more than all others and are far more likely to manage that investment nimbly.

Growth, not just productivity, separates AI leaders

Organisations with the strongest AI performance treat the technology as a reinvention engine, using it to reshape business models and expand beyond traditional industry boundaries. Companies leading on AI report:

• 2.6 times as likely as peers to report AI improves their ability to reinvent their business model;
• Two to three times as likely as others to say they use AI to identify and pursue growth opportunities arising from industry convergence, such as collaborating with partners outside their core sector.

PwC’s analysis shows that capturing growth opportunities from industry convergence is the single strongest factor influencing AI‑driven financial performance, ahead of efficiency gains alone.

Trust and automation combine to delivering outcomes

The research also highlights significant differences in how leading companies deploy AI inside the enterprise. Companies with the best AI-driven financial outcomes are nearly twice as likely as other companies to say they’re using AI in advanced ways: executing multiple tasks within guardrails (1.8x) or operating in autonomous, self-optimising ways (1.9x).

AI leaders are increasing the number of decisions made without human intervention at almost three times (2.8x) the rate of peers.

This automation is enabled by a focus on ‘trust at scale’. AI leaders are more likely than other companies to have mechanisms such as a Responsible AI framework (1.7x as likely as other companies) and a cross-functional AI governance board (1.5x). As a result of their efforts, their employees are twice as likely to trust AI outputs.

A widening gap

Without a shift in approach, the performance gap between AI leaders and laggards is likely to widen further as leading companies continue to learn faster, scale proven use cases and automate decisions safely at scale.