With systems using AI – whether generative or more traditional approaches – already in use inside organisations and in customer facing tools, AI governance needs to move from data science teams (who rarely have expertise in either ethics or business risk) to CIOs who can tackle AI ethics in a practical rather than theoretical way, covering risk tolerance, regulatory requirements and possible changes to business operations.
Tools are emerging for real-world AI systems that focus more on responsible adoption, deployment and governance, rather than academic and philosophical questions about speculative risks