Evaluate employee training in an AI agency proposal

Define the employee roles

Identify who initiates requests, checks results, approves actions, and supports colleagues. Those roles may need different training. A Nashville or regional Tennessee team can include occasional users as well as daily operators, so avoid assuming one session meets every need. Ask the agency to describe the behavior each group should be able to demonstrate at the end of the training.

Practice normal and difficult cases

Use approved examples that resemble the work employees encounter. Include incomplete source information, an uncertain result, and a case that should be handled manually. Teach people how to inspect supporting evidence and understand whether an action has actually completed. A demonstration by the trainer is useful, but employees should also perform the task themselves so confusing steps become visible before launch.

Make feedback actionable

Give staff a clear way to report an incorrect result or an awkward handoff without sending unnecessary sensitive information. Identify who triages feedback and distinguishes training needs from product defects. NIST’s AI risk framework is a reference for considering people and context; our recommendation is to use observed employee behavior as implementation evidence rather than treating attendance at a session as proof of adoption.

Reference: NIST: AI Risk Management Framework

Connect training to continuing ownership

Request concise job aids and a process for updating guidance when the workflow changes. Agentix offers team training alongside implementation and managed support. In a proposal, clarify which materials, practice sessions, and follow-up responsibilities are included. The objective is a team that knows how to use the system and when to seek help, with new employees able to learn the same accepted process after the original project ends.

Reference: Agentix (publisher): Agentix services

Common questions