Blog · Ai Agents
AI Agent Implementation: From Discovery to Customer Handoff
Use an implementation checklist for an AI agent: define scope, connect accounts, test failures, agree acceptance and assign ongoing support.
The short answer
Implement one bounded workflow with named owners. Confirm account access and data needs, test both successful and failed actions, verify records in the destination system, then obtain customer acceptance. Launch with monitoring, a human fallback and a written support process; a successful demonstration alone is not a completed implementation.
An AI agent implementation is complete when the customer can use the agreed workflow, its actions are verified in connected systems, and someone owns ongoing support. A demonstration establishes what a workflow can do under the demonstrated conditions. Acceptance establishes whether it meets this customer’s requirements.
Use this checklist to structure an implementation conversation. It is a suggested process, not a promise that every AI Scaling engagement includes every item. Confirm responsibilities in your written scope.
1. Define the workflow before connecting tools
Write down the trigger, eligible requests, information needed, allowed actions, expected destination record and escalation path. Choose one outcome that the customer values and can observe.
For an appointment workflow, distinguish offering a time, reserving an appointment and confirming attendance. Specify what qualifies an inquiry and what should happen if the customer asks for a person. Use the niche library to explore candidate workflows without assuming every proposed workflow is already implemented.
2. Assign an owner to every dependency
Scroll horizontally to compare all columns
| Dependency | Evidence to collect | Responsible party to name |
|---|---|---|
| Business requirements | Approved scope and exclusions | Customer decision-maker |
| Connected accounts | Working access with appropriate permissions | Account owner |
| Source information | Reviewed service details and response boundaries | Customer subject expert |
| Implementation | Configuration and integration record | Delivery owner |
| Acceptance | Test cases and destination-system results | Customer and delivery reviewer |
| Ongoing support | Escalation route, monitoring and change process | Service owner |
Record the actual person or team for your engagement. Do not assume that the software vendor, agency and customer have the same responsibilities.
3. Verify account access and data boundaries
Confirm which accounts the workflow needs and which actions it can perform. Keep production and test records distinguishable. Review what customer information is necessary, where it goes, and who can access it.
An integration appearing connected is only the first check. Verify the intended read or write action in the destination system. For a calendar, inspect availability and the actual appointment record; for a CRM, inspect the correct contact and intended fields. Read our security overview when discussing the implementation’s data boundary.
4. Test failure paths as deliberately as success paths
- Repeat a request to check for duplicate records or appointments.
- Make an unavailable time selection and confirm the recovery path.
- Ask an unsupported question and check the approved fallback.
- Interrupt a connection and inspect what was actually saved.
- Request a human and confirm that the handoff reaches its owner.
- Correct submitted information and confirm the destination reflects the correction.
Use authorized test accounts and label test records. Keep a short failure log with the trigger, expected behavior, observed behavior, fix and retest result.
5. Agree acceptance criteria before launch
Record the scope, testing period, sample size and pass conditions. Identify failures that stop launch, failures that require a fix, and limitations the customer has explicitly accepted.
The AI agent pilot scorecard supplies measurement categories. Your customer and delivery team should choose thresholds for the actual workflow. Passing a handful of examples does not establish a reliable completion rate.
6. Hand over an operating service
Give the customer a concise runbook: what the workflow does, where to view results, how to request a change, how to pause it, and whom to contact when something goes wrong. Name the owner for reviewing failures and checking third-party changes.
Agree a review point after launch. Compare outcomes and support effort with the baseline before expanding channels, permissions or customer volume. For the wider AI Scaling journey, see the first 90 days and how the model works.
What should you bring to a discovery call?
Bring one workflow, its current volume, the systems it touches, a sample of successful and failed cases, the desired business outcome and the person who can approve access. Avoid sharing sensitive customer information until the appropriate handling arrangements are established.
Pair this checklist with the cost planning guide, then discuss your starting point.