IBM Study: Chief Data Officers Redefine Strategies as AI Ambitions Outpace Readiness
30th article in the last 90 days, one of 64 articles referencing IBM. Previous coverage: Weekly Intelligence Brief on Silicon - Week of November 10, 2025 (Nov 2025).
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A recent global survey by the IBM Institute for Business Value highlighted a critical trend among Chief Data Officers (CDOs), revealing that 81% prioritize investments in Artificial Intelligence (AI) capabilities. Despite these ambitions, only 26% of CDOs expressed confidence in their data's readiness to support newly envisioned AI-driven revenue streams.
The survey, which garnered insights from 1,700 CDOs worldwide, indicated that while data strategies are increasingly aligned with technology roadmaps—growing from 52% in 2023 to 81%—barriers such as data accessibility and integrity continue to hinder effective AI deployment.
Ed Lovely, VP and Chief Data Officer at IBM, noted, “Enterprise AI at scale is within reach, but success depends on organizations powering it with the right data.” The need for a well-integrated enterprise data architecture is deemed essential for maximizing AI potential and enhancing overall operational efficiency.
The evolving role of the CDO is becoming more strategic, with 92% emphasizing the need to focus on business outcomes. Nevertheless, only a third feel equipped to clearly demonstrate how data contributes to business results. As a result, deploying data for a competitive edge has emerged as a primary responsibility for CDOs.
With AI ambitions high, 81% of CDOs are working towards enhancing their AI capabilities. Yet, the gap in data readiness persists, with a significant portion admitting early stages in scaling and governing their AI datasets. Despite these challenges, a majority remain optimistic about the benefits associated with AI deployment.
Lastly, fostering a data-driven culture remains a significant challenge, exacerbated by talent shortages. With nearly half of CDOs citing difficulty in recruiting advanced data skills, organizations must navigate this landscape to ensure effective data utilization in AI processes.
Press release, provided by Cision on behalf of IBM. Read the original.