AI workforce
The collective fleet of AI agents and digital workers an organization runs — managed as a unit with shared governance, shared identity, shared observability, and a unified cost model.
Once an org has more than a handful of agents in production, it needs workforce-level controls — who can spin up agents, what tools they can access, how spend is budgeted, who is on-call when one breaks. This is the AI workforce layer.
In 2026, AI workforce platforms (Sierra, Glean, Moveworks at the enterprise end; Lindy, Relay at the SMB end) treat agents like teams: each agent has an identity, scoped permissions, a manager, and an audit trail. Most large enterprises have a Head of AI Workforce by 2026 — distinct from the CIO and the CTO.
The discipline matters because ungoverned agent sprawl is the new shadow IT. Without workforce-level controls, agents end up with stale credentials, dormant tool access, and unaccounted spend.
Frequently asked
When do I need AI workforce tooling?+
When you have 5+ production agents across multiple teams. Below that, you can manage agents like individual SaaS subscriptions. Above that, you need workforce-level identity, observability, and governance.
