How leading companies generate ROI from AI

As companies accelerate their AI investments, they often find that activity doesn’t always lead to better outcomes. New PwC analysis shows that AI value is currently concentrated in a small cohort of companies. Of 1,217 organisations we surveyed, spanning regions around the world and 25 sectors, the top 20% capture 74% of AI-driven returns.

To understand what separates these top performers, we benchmarked companies’ AI-driven financial performance, defined as the revenue and efficiency gains derived from AI, adjusted so each company could be compared against its sector’s median. We also asked senior executives at these companies about their AI management and investment practices. Last, we grouped those practices into nine categories, such as the breadth and depth of AI implementations, data and technology, and governance and risk. Collectively, those categories make up our AI fitness index.

The results show just how concentrated the gains from AI really are. The most AI-fit companies in our research deliver AI-driven revenues and efficiencies that are 7.2 times as high as those of other companies. Because these companies have the right foundations in place, they’re better at converting AI activity into measurable outcomes.

In fact, these companies see nearly twice the gains in AI-driven performance as those that have weaker foundations. They aren’t simply “doing more AI.” They’re building the capabilities that make AI scalable and reliable and then choosing where to apply that scale for maximum financial leverage.

Here’s how other companies can follow their lead:

Aim AI at growth and reinvention. The AI leaders we studied use AI for efficiency, but they don’t stop there. These companies treat AI like a top-line-boosting reinvention engine—one that helps them create fresh offerings and reshape their business models to move into promising new markets. Our study shows that leading companies are 2.6 times as likely as others to report that AI has improved their ability to reinvent their business model.

Build focused AI foundations. Foundations change the economics of AI. They reduce friction, rework, and ‘one-off’ builds, so that each new deployment gets faster, cheaper, and more reliable. For example, leaders in our analysis were 1.5 times more likely as other companies to provide tech infrastructure to support AI experimentation, like sandbox environments where developers can safely try new AI solutions. Similarly, investments in workforce trust mean that employees are 2.1 times more likely to trust AI-generated insights and act on them in day-to-day work.

Embed AI across the enterprise. Once executives at leading companies define the objectives they hope to achieve with AI, they make sure AI solutions get implemented everywhere in the enterprise so that they can make a difference. They also infuse AI into core workflows and systems so it can enhance the execution of tasks, and they apply AI in sophisticated ways, moving from assistance to automation.