Scaling AI isn’t just a technical challenge—it’s a governance challenge. That’s the message at the heart of our 2024 AI Governance Benchmark Report, recently featured in The AI Journal. As enterprise adoption of AI accelerates, gaps in oversight, ownership, and operationalization are becoming increasingly urgent—and increasingly visible.
ModelOp’s benchmark study, based on responses from AI and data leaders across industries, surfaces some of the most pressing roadblocks to enterprise-scale AI. Among the most striking:
- 42% of leaders cited unclear ownership as the top barrier to AI governance.
- Training and awareness are sorely lacking—most teams report little to no education on governance principles.
- AI initiatives stall without structure, often failing to move beyond the pilot phase due to missing controls and inconsistent oversight.
These aren’t just operational hiccups—they’re systemic issues that put both innovation and compliance at risk.
As new regulations take hold and GenAI becomes a fixture of enterprise strategy, governance must become a first-class priority. The Benchmark Report provides not only visibility into the current state of enterprise AI governance, but also a path forward—with concrete recommendations for gaining control and scaling responsibly. At ModelOp, we help enterprises take that path through software built specifically for the governance and oversight of production AI systems.
We’re honored that The AI Journal has featured these findings. Their article offers a sharp, accessible summary of the report’s core insights—and why governance gaps are proving so difficult to close.
