AI Chatbot Implementation Checklist: From Pilot to Production
A chatbot launch is a small software rollout, not a copywriting exercise. Production readiness depends on source ownership, behavior boundaries, failure handling, observability, and a team process for improvements.
Before configuration
Choose the initial customer journey, accountable owner, success metric, and escalation channel. Document data that must never enter the system and confirm the retention expectation.
Clean the knowledge sources. Mark current policies, remove duplicates, and keep internal-only material separate from public answers.
- Named product and operations owner
- Defined launch intent and exclusions
- Approved knowledge set
- Privacy and retention decision
- Traffic and usage estimate
Before publication
Test direct, paraphrased, ambiguous, unsupported, and adversarial requests. Exercise every enabled action with valid and invalid input. Confirm that errors produce a useful fallback and an operational record.
Verify mobile layout, keyboard navigation, domain restrictions, rate limits, and the usage-limit experience. Confirm that a person can take over and that the customer understands what happens next.
- Saved regression tests
- Action authorization and validation
- Provider failure behavior
- Lead and handoff delivery
- Analytics without conversation content
After launch
Review provider errors, ingestion failures, unanswered questions, usage spikes, and handoff queues on a schedule. Assign every operational alert an owner and a resolution path.
Measure customer outcomes and maintenance time. Expand only when the initial workflow is reliable and the team can support the additional surface area.
Frequently asked questions
How many tests should a chatbot have before launch?
Use enough tests to cover every major intent, boundary, action, and failure mode. Quality and coverage matter more than an arbitrary count.
Who should own the chatbot?
A business owner should own outcomes and knowledge, while an operational owner monitors failures, usage, and handoffs.
Turn the playbook into a working agent.
Start with your own knowledge, test real customer questions, and publish when the answers are ready.
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