AI governance challenges: How to support safe, scalable AI adoption

AI governance is crucial for safely and effectively scaling AI adoption within enterprises, but challenges arise when the governance framework does not keep pace with expanding AI use. As AI applications move beyond controlled pilots to broader business contexts, mismatches can occur between initial governance controls and the evolving use cases, leading to risks such as unmonitored AI usage, unclear ownership, and inadequate risk-based controls. Effective governance requires maintaining visibility over AI use, defining clear ownership and escalation paths, and applying appropriate controls based on the risk profile of each use case. Continuous monitoring and updating of governance practices are essential to adapt to changes in AI usage and technology. Cohere emphasizes robust governance practices in its model development and deployment to support responsible AI use among its enterprise customers.

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