What you need to know:

• AI is embedded in everyday work, and governance must extend beyond specialist teams.
• Effective AI governance blends centralized policy with workflow-level accountability.
• The right tools help turn AI governance from enforcement into enablement.

While generative AI use touches nearly every part of business operations, AI governance is often anchored in specialist functions. Policies are commonly defined by IT, Legal, or risk management teams for others to follow and who serve as default checkpoints for AI output.

What’s becoming increasingly clear, however, is that AI doesn’t live in one function’s remit. It lives in the daily decisions made by every department that uses it; supporting marketing teams creating content, analysts synthesizing information, leaders shaping strategy, and employees streamlining everyday work.

Because AI is used across functions, the risks—and the responsibility for managing them—are shared too. AI governance is naturally becoming an organization-wide consideration rather than a responsibility owned by a single team.

The focus must turn to mechanisms that can uphold centralized AI policies while reinforcing accountability in real time across departments, at the speed AI demands.

Want to read the rest of the article? Check out the Turnitin blog here: https://www.turnitin.com/blog/why-every-department-owns-ai-governance