Generative AI is increasingly integrated into production pipelines, prompting a significant growth in adoption among organizations. However, AI governance is lagging, with discrepancies especially evident between large and small organizations. Despite 75% of respondents having AI usage policies, only 60% have designated governance roles. In smaller firms, these numbers drop significantly, revealing a disconnect between established policies and practical governance implementation. Effective AI impact hinges on not just adopting technology, but also embedding proactive governance into daily operations.
Organizations implementing generative AI models are seeing gaps in AI governance, with a disconnect between rapid adoption and the maturity of governance measures.
The governance landscape shows just 60% of organizations designated governance roles, with even fewer having established frameworks for managing AI risks like bias and data misuse.
While 75% of organizations claim to have an AI usage policy, the real challenge lies in embedding this governance into daily operations effectively.
The data reveals that small firms particularly struggle with governance roles and training, highlighting a significant policy-practice gap that needs urgent attention.
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