A custom AI employee starts with a defined job

Turn the role into specific work

A custom AI employee is a configured workflow with defined responsibilities, information and permitted actions. Break a broad role into observable tasks. Reading a record, preparing a recommendation and changing a business system are different operations and may need different permissions or review.

Agree the custom workflow deliverables

A useful proposal makes the first release concrete.

• A workflow map with triggers, inputs, decisions and expected outputs.
• A source-system and permission map, including owners and excluded actions.
• Approved knowledge, action rules and human approval checkpoints.
• Exception handling, recovery steps and a way to pause the workflow.
• Acceptance examples, operating documentation and ownership of later changes.

Example: prepare a service request for approval

Illustrative workflow: a new request arrives. The agent checks whether the necessary details are present, asks for missing information and prepares a structured record for the responsible team. It may create or update a task only if the configured integration permits it. A commercial commitment remains with the authorised person. This example describes a possible scope, not a customer deployment.

Choose the smallest useful first release

Select a task that is frequent enough to observe and bounded enough to review. Identify what completion means and what remains manual. A complex process can often be divided into preparation, approval and execution. Keep these states visible so a prepared action is not confused with a completed one.

Confirm permissions and failure recovery

For each connected system, document the record types, access owner, supported operations and approval limits. Decide what happens if information conflicts, credentials expire or an integration is unavailable. Completed actions must not be repeated simply because a later step failed. Keep a record that lets the responsible team determine what actually happened.

Use acceptance checks tied to the job

Agree representative inputs and failure cases before expanding responsibility.

• The workflow returns the expected output for the agreed task.
• Missing information triggers clarification or an assigned exception.
• Actions outside authority wait for approval.
• A failed or repeated request does not silently duplicate completed work.
• The team can inspect, correct and pause the workflow.
• Each unresolved case has an owner and a next action.

Estimate delivery and cost from dependencies

Timing depends on knowledge readiness, access to source systems, integration work and acceptance results. Ask for milestones such as scope agreed, integrations checked, pilot reviewed and release accepted. Separate setup, usage, system charges, maintenance and support costs. Add responsibilities only after reviewing the initial workflow’s failures and useful outcomes.

Questions to settle before launch

Practical guides for this workflow

• How to Write a Project Brief for a Custom AI Employee

  Turn a broad AI employee request into one useful task with clear inputs, permissions, outputs and acceptance criteria.

• How Should a UAE Business Hand AI Enquiries to Its Human Team?

  A practical handoff checklist for AI enquiries: escalation triggers, ownership, conversation context, staffed hours and a clear fallback.