Three-quarters of AI’s economic gains are being captured by just 20% of companies – with the leading companies focused on growth, not just productivity: PwC

• The leading companies are approximately two to three times more likely to use AI to identify and pursue growth opportunities and reinvent their business model.
• They are twice as likely to redesign workflows to incorporate AI rather than simply adding AI tools. 
• They are three times more likely to have increased the number of decisions made without human intervention, while also going further on AI governance.

Jakarta, 11 May 2026 – Twenty percent of companies are pulling sharply ahead in the race to generate real financial returns from artificial intelligence, according to PwC’s new AI Performance Study. The global study interviewed 1,217 senior executives, 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 74% of AI’s economic value is captured by just 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, while building strong foundations around data, governance, and trust.

Joe Atkinson, Global Chief AI Officer, PwC, said, “Many companies are busy rolling out AI pilots, but only a minority are converting that activity into measurable financial returns. The leaders stand out because they point AI at growth, not just cost reduction, and back that ambition with the foundations that make AI scalable and reliable.”

Reflecting these global findings, PwC Indonesia highlights the importance of clear strategic intent and disciplined execution in AI adoption.

Subianto, PwC Indonesia Digital and Technology Leader, said, “The key message for organisations is that AI needs direction. Leaders must be clear about where AI is expected to drive growth, which decisions they are willing to automate, and how success will be measured. Without that focus, AI investment risks remaining fragmented and failing to deliver meaningful financial impact.”

These priorities are reflected in the research findings, which show that leading organisations drive growth by capturing revenue from industry convergence and strengthening their foundations in data, governance, and trust.

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 peers 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. This finding underscores the importance of looking beyond productivity gains when shaping AI strategies at a local level.

Eddy Rintis, PwC Indonesia Territory Senior Partner, added, “To close the performance gap, leaders need to look beyond efficiency and consider how AI can help the organisation move into new value pools. That means using AI to anticipate changing customer needs, rethink products and services, and collaborate across traditional industry boundaries—not simply optimising existing operations.”

Trust and automation combine to deliver outcomes

The research highlights significant differences in how leading companies deploy AI within the enterprise. Companies with the strongest AI‑driven financial outcomes are nearly twice as likely as their peers to use AI in more advanced ways, supported by clear guardrails and governance—ranging from executing multiple tasks within defined parameters (1.8x) to operating in autonomous, self‑optimising ways (1.9x).

Subianto, PwC Indonesia Digital and Technology Leader, said, “Automation at scale only delivers value when trust is built into the system. Organisations should invest early in strong governance, clear accountability, and Responsible AI practices, so that teams can rely on AI with confidence. These foundations are critical to turning faster decision‑making into sustained performance gains.”

This focus on trust enables organisations to scale automation safely. AI leaders are increasing the number of decisions made without human intervention at almost three times the rate of their peers. They are also more likely to have mechanisms such as Responsible AI frameworks and cross‑functional AI governance boards in place. As a result, employees in these organisations are twice as likely to trust AI‑generated outputs.

A widening gap

Without a shift in approach, the performance gap between AI leaders and slow adopters is likely to widen further, as leading companies continue to learn faster, scale proven use cases, and automate decisions safely at scale—supported by stronger foundations, clearer governance, and higher levels of trust.