What Enterprises Are Getting Wrong About AI Data Readiness
TechTarget, Thursday, July 9th, 2026
Rising AI project failures stem from poor data readiness, not technology limits.
The article reports AI project failures jumped from 17% to 42% between 2024 and 2025, with up to 72% of businesses potentially abandoning pilots due to inadequate data preparation rather than technology. Enterprises wrongly prioritize data volume over accuracy, when the real need is data that is accessible, understandable, and trustworthy.
Governance is often treated as compliance rather than an enabler, risking privacy breaches, bias, and violations, while rushing deployment creates technical debt and silos block consistency. Human readiness, data literacy, and change management are equally critical.
It recommends data audits, governance frameworks, infrastructure modernization, upskilling, and continuous quality monitoring before deployment.