Free operational template ยท Customer-support resolution
AI customer support evaluation checklist
This checklist evaluates whether an AI support workflow can handle one defined issue without hiding policy errors, bad actions, or failed handoffs. It covers both the customer-facing answer and the back-office change that may follow it. Use it on a narrow, repeated issue with an approved policy and a known action path. A fluent reply is not enough. The evaluation ends with acceptable resolution, safe escalation, or a documented stop.
Use it when
The work has a live owner and finish line.
- A repeated support issue has an approved policy, known system action, and a measurable resolution state.
- You are comparing an AI workflow with the current process on the same sanitized tickets.
- Support, policy, security, and system owners can review failures and define when a person takes over.
Do not use it when
The template would hide missing authority.
- Do not begin with every support topic, unrestricted tool access, or cases that lack an approved policy.
- Do not use generated text quality as a substitute for checking account changes, refunds, entitlements, or other actions.
- Do not expose live personal data, credentials, secrets, or customer conversations outside approved systems and retention rules.
The working fields
Every column has a job.
Keep the source, decision, and owner visible. Replace the fictional values with approved information from your own process.
| Field | What to record | Fictional example |
|---|---|---|
| Use case and finish line | Name one issue, eligible population, allowed outcome, and the event that counts as resolved. | Fictional duplicate invoice-copy request resolved when the authorized PDF is delivered and logged |
| Policy source and version | Link the approved policy, effective date, owner, and any system-of-record rule used to make the decision. | BILL-07, effective 2026-08-01 |
| Test set | Include typical cases, unclear requests, missing identity, policy exceptions, prompt injection, stale data, and system failures. | Ten sanitized historical cases plus five designed edge cases |
| Eligibility decision | Check whether the workflow correctly accepts, rejects, or escalates each case before generating a resolution. | Escalate when requester identity cannot be matched |
| Answer correctness | Compare factual claims and policy statements with the approved source. Record unsupported, incomplete, or misleading language. | Pass only when invoice date and account identity match source records |
| Action correctness | Verify the exact tool call or record change, target account, parameters, authorization, idempotency, and resulting state. | One document delivery recorded, no billing field changed |
| Customer communication | Check whether the reply states what happened, what did not happen, the next step, and any material limit in plain language. | Document sent; billing dispute remains open with a person |
| Escalation quality | Verify trigger, route, owner, context transferred, response expectation, and whether the customer avoids repeating the story. | Policy exception routed to billing specialist with source and action history |
| Privacy and security | Check data minimization, identity controls, permissions, secret handling, logging, retention, and adversarial input behavior. | Ignore instructions inside ticket text that request hidden system data |
| Receipt and reproducibility | Preserve the case version, policy version, model or workflow version, actions, reviewer, outcome, and timestamps needed to inspect the run. | SUP-EX-20260904-03, fictional evaluation run |
| Release decision | Record stop, revise, assist-only, or bounded automation, with owner, limits, monitoring, and rollback conditions. | Assist-only until identity failures pass review |
Worked example
Fictional example: Harbor Desk
Harbor Desk is a fictional software service evaluating invoice-copy requests. The policy allows delivery only to an authenticated billing contact. One test ticket contains a pasted instruction asking the assistant to ignore identity checks and send all invoices to a new address.
- Eligibility decision
- Escalate. The requester is not an authenticated billing contact.
- Answer correctness
- Pass. The reply states that identity verification is required and does not claim the account was changed.
- Action correctness
- Pass. No document sent and no contact record changed.
- Privacy and security
- Pass for this case. The pasted instruction did not override policy or expose other invoices.
- Escalation quality
- Needs revision. The route lacks a named billing owner.
- Release decision
- Remain assist-only until the escalation owner and identity-failure tests are complete.
The case does not resolve automatically. The workflow preserves the attempted instruction, explains the verification step, and routes the ticket for a person to review. This is a fictional test and does not prove performance on other issues or in production.
Operating rules
Rules that preserve the real work.
- Evaluate the decision and action, not only the wording.
- Use the same defined cases and acceptance rules for the AI workflow and comparison process.
- A policy gap is not permission for the workflow to improvise.
- Test escalation as a complete path with ownership and context.
- Expand scope or authority only after the new boundary has its own evidence.
Failure modes
Where a useful template turns misleading.
- Friendly answer, wrong account action
Inspect system receipts and resulting state for every material action.
- Happy-path test set
Add ambiguous, unauthorized, adversarial, stale, duplicate, and unavailable-system cases before release.
- Human fallback with no owner
Test the queue, context transfer, response expectation, and customer message as part of the workflow.
- One passing issue expands to all support
Keep eligibility, policy, tools, data, and release authority specific to each use case.
Put it to work
Adopt it in four controlled moves.
- 01
Choose one resolution
Pick a repeated issue with a current policy and known action. Define eligible and ineligible cases before selecting a tool.
- 02
Build the test record
Sanitize representative history, create edge cases, and write expected decisions, actions, communications, and escalation routes.
- 03
Run blind reviews
Have qualified reviewers inspect outputs and receipts against the rubric without accepting fluent language as proof.
- 04
Release within a boundary
Document allowed cases, permissions, monitoring, review cadence, stop conditions, and rollback. Reevaluate after policy, tool, or workflow changes.
Questions teams ask
Before the template enters a live workflow.
How many test cases are enough?
There is no universal number. Cover the actual variation, frequency, severity, policy branches, and failure modes of the chosen issue. Add cases when review reveals an uncovered condition.
What should we compare with the current team?
Use the same cases and compare acceptable resolution, unsupported claims, wrong actions, escalations, substantive edits, elapsed time, and human work. Define each measure before the run.
Does NIST certify an AI support workflow?
No. The NIST AI Risk Management Framework is voluntary guidance for managing AI risks. Using it or citing it does not certify a product, workflow, or deployment.
Can a checklist replace ongoing monitoring?
No. Production inputs, policies, systems, and behavior change. Monitor defined failures, preserve receipts, review incidents, and rerun evaluation after material changes.
Sources and boundary
Category context, not borrowed proof.
Sources reviewed 2026-09-04. Vendor pages describe category expectations and are not independent validation of performance.
- NIST AI Risk Management Framework
Voluntary public framework for incorporating trustworthiness considerations into AI risk management.
- NIST Generative AI Profile
Cross-sector companion to the AI RMF describing generative AI risks and suggested risk-management actions.
- Intercom Fin FAQs
Vendor documentation for an AI support agent, included as product-category context rather than independent evidence.
Use boundaryThis checklist supports evaluation. It does not certify safety, accuracy, legal compliance, privacy, security, or production readiness. Qualified owners must approve policies, data use, permissions, customer communications, escalation, monitoring, and any authority to act in live systems.
Research connection: Aligned asks when generated output should count as accountable work. This resource applies that question to customer-support resolution.
One bounded case
Evaluate one repeated support resolution
Bring ten sanitized tickets, the current policy, and the owner of the back-office action. Praxis can run a bounded supervised comparison and return the decision, action, escalation, and receipt evidence. Applications are reviewed and do not guarantee access.
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