Autonomous AI agents are now a core part of the enterprise workforce, taking actions and making decisions without human involvement in each transaction. No management discipline exists for governing them. This paper introduces Agentic Workforce Management™ (AWM™), a formal framework for acquiring, onboarding, managing, and offboarding AI agents before ungoverned deployments become an operational and regulatory liability.
AI agents are no longer a future consideration. They are operating inside enterprise environments today, taking actions, making decisions, and triggering workflows without human involvement in each transaction. Yet the governance frameworks organizations rely on were built for human workers and have four critical gaps when applied to autonomous agents: no orchestration governance, no accountability mechanisms, a latency problem in human oversight, and no agent identity standard.
This paper introduces Agentic Workforce Management™ (AWM™), a formal framework for acquiring, onboarding, managing, and offboarding AI agents across their full operational lifecycle. Drawing on the evolution of contingent workforce management, AWM™ gives HR, IT, and operations leaders a structured approach to governing the agent workforce with the same rigor they apply to human and extended workforces.
The paper covers the AWM™ lifecycle in detail, maps the framework to EU AI Act compliance requirements ahead of the August 2026 enforcement deadline, and includes a maturity self-assessment organizations can use to benchmark their current state and prioritize implementation.
Download the full white paper here: Agentic Workforce Management™ - A Framework for Acquiring, Onboarding, Managing, and Offboarding AI Agents in the Enterprise