The data crisis: why the future of AI depends on fixing the foundations (www.techradar.com)

AI’s next frontier isn’t just smarter models but sturdier foundations: the industry must fix data quality, governance and infrastructure or risk costly, unsafe outcomes. The piece warns that incomplete, fragmented or low-quality data undermines model performance and business decisions — with 38% of IT leaders naming data quality as the top driver of AI success while many still test models in production (74%). Beyond operational fallout and reputational harm, poor data practices raise legal exposure in high‑risk domains as regulations like the EU AI Act, GDPR and DORA demand traceability, auditability and accountability for data-driven decisions. Energy and scale also matter: IEA forecasts data‑center electricity demand more than doubling by 2030, with AI‑optimized centers’ consumption projected to quadruple within five years, amplifying the need for efficient, scalable systems. The answer is infrastructure‑first: standardized, secure, and well-governed data pipelines feeding models from centralized or hybrid cloud platforms that enable high throughput, compliance by design, and end‑to‑end audit trails. Practical steps include hybrid cloud integration, automated compliance tooling, robust data lineage and governance, and secure pipelines that protect privacy while enabling scale. Investing in these foundations de‑risks AI, improves generalization and trustworthiness, and ensures AI delivers dependable, compliant real‑world value rather than unpredictable decisions.