How AI Teams Work
An AI Team is a managed workforce of specialized Digital Employees organized around a defined business function.
A Digital Employee is a logical job, not necessarily a separate model instance. The same capable model can perform several jobs while each job retains its own responsibilities, skills, boundaries, outputs, and evaluation criteria.
From goal to work
A human manager or subject matter expert provides a goal. Orchestration determines the workflow state and routes the next job to the responsible Digital Employee.
The Digital Employee loads the skill required for that job, retrieves only the authorized context needed, invokes approved tools when necessary, and produces a structured work product.
The orchestrator validates the result against the stage exit condition before advancing the workflow or requesting human review.
Separation of responsibilities
- Digital Employee: who owns the job.
- Skill: how specialized work is performed.
- Orchestrator: when work runs, what state it is in, and what happens next.
- Execution layer: where and how the work executes.
- Model/runtime: reasoning and generation capability used to perform the work.
- Customer AI Control Plane: what organizational context is available and what humans and Digital Employees may access or do.
- Tools: approved capabilities for retrieving information or taking action.
Why the separation matters
Models will continue to become more capable. A stronger runtime may collapse several technical calls into one execution session, but the organization still needs to know who owns a job, which method applies, what evidence was used, what permissions apply, what output is expected, and whether a human must approve the next action.
The architecture preserves those management boundaries while allowing the execution technology underneath them to change.