Open Data Infrastructure emerges as AI investment outpaces data foundations

AI investment is rising quickly, but many organizations are finding that weak data foundations limit its impact. Gartner says over 90 percent of CIOs globally are increasing AI funding, while enterprises now spend an average of $29.3 million per year on data programs.

Higher budgets have not solved reliability problems. Organizations with successful AI initiatives invest up to four times more in data and analytics foundations, yet 73 percent say their data initiatives fall short of expectations. Nearly 62 percent report low data maturity.

The operational costs are also significant. In large organizations, data-pipeline failures cause more than 60 hours of downtime each month, with an estimated business impact of £50,000 per hour. Data teams spend over half of their engineering capacity maintaining pipelines instead of developing new use cases.

Open Data Infrastructure (ODI) is emerging as an architectural response. It uses shared, open standards and a modular design that separates storage from compute, allowing tools and platforms to work together while reducing dependence on proprietary systems.

The need for a shared data foundation is growing as non-human entities appear in enterprises at a ratio of 82:1 compared with humans. Research indicates that organizations with modern, managed and open data foundations are nearly twice as likely to exceed their ROI targets as organizations using legacy systems.