AI Governance news

30% of AI Projects Will Shut Down by 2027

According to Gartner, nearly one-third of enterprise AI projects will be shut down by 2027—not because of bad models, but because of bad data. The core issue? Poor data quality, lack of governance, and failure to meet evolving compliance demands.

Meanwhile, 2025 is shaping up to be the most consequential year for AI regulation.

• The EU AI Act’s enforcement timeline is accelerating, with key provisions taking effect throughout 2025
• Fines of up to €35 million or 7% of global annual turnover for non-compliance create existential business risks
• The UK’s AI governance framework is simultaneously creating different compliance requirements for global organizations

This means enterprises must now contend with global legal complexity while trying to scale up AI.

Yet most enterprise AI initiatives today still run without centralized oversight, enforceable access controls, or data governance baked into their development workflows.

The result is a dangerous spiral:

• No data quality → No business value → No justification to govern → No compliance → No AI readiness

What’s driving the urgency?

• Regulatory pressure is rising
• AI is outpacing traditional governance frameworks
• Innovation is being slowed—or worse, exposed
• Security and reputational risks are escalating

The companies that will thrive aren’t treating compliance as a checkbox. They’re embedding governance into the very fabric of their AI pipelines—from data retention and search access to traceability and risk scoring.

At Platform 3, we’re helping organizations modernize their data infrastructure for this shift—with archival and governance that’s built not just for compliance, but for AI-readiness.

👉 Learn how Archon makes enterprise AI safer and smarter → Book a call here.