AI Support Risk Register: Template and Examples Before Launch

The useful unit of risk is not AI, policy, or hallucination. It is the customer intent that might be answered incorrectly, incompletely, or without the right handoff. Start from recent tickets, chats, macros, help-center searches, and high-risk edge cases.

Each row should name the intent in support language. A row such as refund risk is too vague. A row such as customer asks for a refund after a delayed shipment but outside the published return window is specific enough to test, source, approve, restrict, or keep human-owned.

A risk register should force evidence into the conversation. If a support team cannot point to a current help article, macro, SOP, policy document, product page, security rule, or approved answer, the intent is not ready for broad automation.

Source conflicts should be treated as launch blockers. AI agents often blend nearby knowledge gracefully, which makes contradictory sources more dangerous. The register should show when the help center, macro, private policy, and recent ticket habit do not agree.

The control column should not be generic. It should describe what must happen before the AI can answer: check plan, region, order status, identity, consent, subscription state, claim status, provider ownership, or document-release approval.

For some rows, the right control is a human handoff. That is not a failure. It is the correct launch boundary when the question involves legal threats, complaints, clinical judgement, regulated advice, account takeover exposure, privacy, fraud, or high-cost exceptions.

A binary pass or fail hides the actual operating decision. Many support intents are answerable only under conditions. Others are valuable automation candidates but need source cleanup first. A smaller set should remain human-owned even when the AI can draft a fluent response.

Use launch states that a vendor admin, support lead, legal reviewer, and knowledge owner can all understand. The output should become the launch boundary, the source-fix backlog, and the retest plan.

Insurance teams should register claims eligibility, complaint language, hardship, fraud, identity change, cancellation, and policy-exception intents. Telehealth teams should register clinical-sounding symptoms, refill eligibility, privacy requests, crisis language, appointment access, and provider handoff.

D2C ecommerce teams should register refund exceptions, damaged orders, subscription timing, allergy or product-fit claims, VIP exceptions, chargebacks, fraud-sensitive orders, and promotion conflicts. SaaS teams should register account access, data retention, downgrade effects, security documents, billing disputes, legal threats, and administrator changes.

The register is not a pre-launch spreadsheet that gets archived. It should be updated when source content changes, a vendor configuration changes, a wrong answer appears, a policy is rewritten, a new regulated workflow launches, or support sees a new pattern in tickets.

The most important operational habit is retesting the same risky intents after change. If the AI passed a refund exception in April, that result should not survive a June policy rewrite without another source and answer review.