The rise and ROI of the chief AI officer

Companies with a CAIO see better results. Leaders from Heineken, Schneider Electric and IBM explain how they did it.

The chief AI officer may be the fastest growing role in business. In a forthcoming CEO report from IBM’s Institute for Business Value (IBV), set to debut at IBM’sThink 2026 event, 76% of surveyed organizations said they have a CAIO in 2026, up from just 26% in 2025. And that’s not just at tech companies like Meta and Salesforce, but also at enterprises like Heineken, WPP, Nike and CVS Health. That kind of growth can look like froth. But the IBV found that companies with a chief AI officer had a 5% higher return on their AI investments. How did that happen?Just like the technology that drove it, the CAIO role has matured over the past few years. “It used to be that chief AI officers were more figureheads—AI evangelists promoting AI,” said Jacob Dencik, Research Director at IBV in an interview with IBM Think. “But now they’re actually driving real transformation with AI and helping enterprises move from pilots to wide-scale implementation.”Schneider Electric is a clear example of the focus on implementation. The global energy technology company created its chief AI officer role in 2021, well before generative AI forced the issue for much of the corporate world. From the outset, Schneider’s mandate for AI leadership was less about experimentation for its own sake and more about operational impact. As Philippe Rambach, the company’s Chief AI Officer, emphasized in his conversation withIBM Think, AI at Schneider “always starts with a business need, not the technology.”Still, not everyone is convinced companies need the role. Tim Crawford, Founder and CIO Strategic Advisor at research firmAVOA, sees the CAIO moment as familiar. He compares it to the rise of the chief digital officer a decade ago—a role that often emerged quickly at companies, with mixed results, especially when organizations rushed to bring in external CDOs, he noted. These leaders sometimes struggled because they “weren’t as in tune with the business”; meanwhile, the core responsibility of digital transformation often fell back on the CIO.

On paper, the rise of the chief AI officer can seem redundant. Many companies have added AI to the remit of CIOs, CTOs, chief data officers and chief digital officers. But as organizations have discovered over the past two years, AI doesn’t behave like earlier technologies. Its reach is broader, its pace faster and the expectations around it far higher.“AI is crossing the entire enterprise in a way that most other technologies haven’t,” said Dencik. Unlike cloud computing or enterprise software, which largely lived inside IT, AI is something “every C-suite member and every employee potentially has an expectation about,” he said, including “what it should be doing and how fast it should be delivering value.”At Schneider Electric, that breadth helped shape the role early on. Rather than positioning AI as a standalone technical function, the company organized its efforts around a hub-and-spoke model: a central AI team responsible for strategy, standards and tooling, paired with execution embedded in business units. The approach, Rambach said, helps keep AI close to real operational problems while avoiding fragmentation and duplicated effort.Crawford agreed that AI fragmentation is a top challenge for leaders, but he cautioned against assuming every organization needs a standalone CAIO to address this challenge. In some cases, he said, the responsibility for AI can sit with the CIO or even the CEO, provided there is clear accountability and strong cross-functional coordination. Other companies, from SAP to Nike, have combined the CAIO role with another C-suite title. Philip Herzig at SAP, for example, is both CAIO and CTO, and Alan John at Nike is Global Head of Data and AI. The larger issue, said Crawford, is not which executive owns AI, but whether an organization has the leadership structures needed to guide it responsibly as it spreads across the business.Furthermore, Dencik pointed to a growing gap between ambition and reality: companies are investing heavily in AI, yet sometimes struggling to move beyond pilots or measure impact. The result, he said, is pressure to create “a dedicated capability in the organization that can actually convert AI into business value,” rather than letting initiatives sprawl across departments without coordination. Hence, they hire a CAIO.