AI agent governance patterns as executable decision tables (MIT license) (github.com)

Three new AI agent governance patterns have been released as free and open-source resources, specifically aimed at enhancing decision-making processes within AI infrastructures. These patterns, which include an executable decision table, a comprehensive worked example, and a Microsoft Agent 365 template, address critical governance issues that existing infrastructure and documentation often overlook. They focus on agent identity ownership, budget management, and inventory reconciliation, helping organizations ensure their AI agents operate efficiently and within compliance. These governance patterns are significant for the AI/ML community as they introduce actionable frameworks that can be seamlessly integrated into existing governance structures without the need for extensive modifications. By providing executable decision logic, these resources enable organizations to automate checks that confirm identity ownership, set spending limits, and maintain an up-to-date inventory of AI agents. This not only streamlines operations but also mitigates risks associated with agent misuse and uncontrolled expenditure, making it a vital contribution to responsible AI governance. The project is licensed under MIT, promoting further adaptation and development by the community.