Generative AI governance is the framework of policies, roles and controls an organization uses to manage how generative AI tools are adopted and used. It covers acceptable use, data protection, model and vendor approval, output review, accountability, and compliance with regulations.
Most frameworks address four questions: which tools are approved, what data can be shared with them, who is accountable for their output, and how that output is checked before it’s used.
For engineering teams, the last question is the hardest to answer with a policy document alone. AI-generated code needs automated checks in the delivery pipeline. For Ansible and Terraform code, Steampunk Spotter provides that control: a deterministic gate before execution, with a record of what passed and when.
A generative AI governance framework typically includes an acceptable use policy, an approved tools list, data classification rules, human and automated review requirements for AI output, incident handling, and regular audits.
