Agentic Workforce Framework, an operating model for autonomous agent teams (github.com)

The Agentic Workforce Framework has been introduced as a comprehensive model for managing autonomous AI agents in enterprise environments. This framework establishes a structured operating model that defines agent roles, task assignments, trust metrics, and approval processes, significantly advancing the way organizations can incorporate AI agents as accountable digital workers. Rather than merely focusing on task execution, this framework addresses critical issues of identity, behavioral trust, and scalability across departments, which are essential as AI agents become integral to complex workflows. One of the key innovations is the governance over agent autonomy and performance, encapsulated in the D1-D4 trust scoring system and a failure memory taxonomy. These features allow enterprises to evaluate agent reliability over time, implementing approval gates that determine when autonomy can be expanded or restricted based on demonstrated performance. With a current single-workspace reference model and a roadmap for multi-team implementations, the framework reflects a shift in the AI/ML conversation from merely asking if agents can produce correct outputs to understanding how to effectively manage and trust autonomous agent teams within an organizational context.