Why AI Projects Fail: The Governance Deficit
According to past research (by Gartner, VentureBeat, etc.), nearly 80% of AI projects fail. For an executive, this number isn’t just a statistic. It represents wasted budget and lost opportunities.
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According to past research (by Gartner, VentureBeat, etc.), nearly 80% of AI projects fail. For an executive, this number isn’t just a statistic. It represents wasted budget and lost opportunities.
Everyone wants an “AI Transformation,” but nobody wants to clean their warehouse.
As we proceed toward the August 2026 milestone (official enforcement date for universal transparency obligations and strict controls on High-Risk AI) I see more and more C-level executives treating the EU AI Act as just another legal checkbox (like GDPR) or a purely technical task for the IT department.
As AI automates code generation, dashboards, and data pipelines, technical execution is no longer the bottleneck.
Stop looking for a better AI model and start looking at your Data Governance.
In the rush toward Generative AI, organizations are racing to showcase innovation. Pilots are launched. Chatbots are deployed. Strategy decks are updated.