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IBM’s study finds about one-quarter of the organizations surveyed reported having a CAIO, up from 11% in 2023 and are seeing an average of 10% greater return on investment in AI spending and 24% greater innovation compared to their peers

August 4, 2025 //  by Finnovate

A growing number of organizations are appointing chief AI officers and seeing an average of 10% greater return on investment in AI spending and 24% greater innovation compared to their peers — but most organizations remain stuck in pilot mode and struggle to scale AI initiatives more broadly. Those are among the findings of a new study by the IBM Institute for Business Value with the Dubai Future Foundation and Oxford Economics. The survey reveals that organizations with CAIOs see positive returns but face strategic, technical and organizational obstacles to optimizing the role’s value. Improved metrics, teamwork and cultural modifications are needed. About one-quarter of the organizations surveyed reported having a CAIO, up from 11% in 2023. Two-thirds of respondents expect most organizations will have a CAIO within the next two years. Organizations that have appointed CAIOs say the primary drivers are to accelerate AI strategy and adoption. AI spending increased 62% as a share of information technology budgets over the past three years, and CEOs expect 31% annual increases through 2027. Nevertheless, 60% of organizations are still investing primarily in pilots, and only 25% of AI initiatives have delivered the expected ROI since 2023. The report delineates a clear shift in operating models as AI projects scale. Initial efforts tend to be decentralized, but advanced organizations shift to centralized hub‑and‑spoke models. That approach moves twice as many pilots into production compared to a decentralized structure and realizes 36% higher ROI. That’s because centralization provides clearer ownership, according to Mohammed Al Mudharreb, CAIO of Dubai’s Road and Transport Authority.  The study found that the factors that separate high-performing CAIOs from their peers are measurement, teamwork and authority. Successful projects address high-impact areas like revenue growth, profit, customer satisfaction and employee productivity. The most effective teams combine AI specialists, machine‑learning engineers and business strategists, with AI experts embedded across functions to avoid the emergence of shadow AI operations.

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