# Illustrative AI workflow review: support response drafting

Sample deliverable · TheTechStack · https://www.thetechstack.com/work-with-us

**Status: illustrative only.** This document describes a fictional support-drafting review to show the shape of a possible deliverable. It is not a customer case study, a report from a completed engagement, measured evidence, a security or compliance assessment, or approval to deploy.

## 1. The decision in front of the team

The fictional team is deciding whether to introduce an AI-assisted first draft for a narrow class of support questions. A support specialist would still review and send every response during the initial pilot.

The first release would cover questions that can be answered from a named, approved set of product documentation. It would exclude account changes, refunds, security-sensitive requests, legal or regulatory interpretations, and anything that requires an unapproved action in another system.

The team needs to decide:

- whether the proposed boundary is narrow enough to test safely;
- which existing support and knowledge systems can be used without expanding access unnecessarily;
- what evidence would show that drafting helps without lowering answer quality; and
- what must be fixed before the workflow could be considered for a limited expansion.

## 2. Inputs requested from the team

The review would use non-confidential planning material only:

- a short description of the current support workflow, including review and escalation;
- the names and roles of the systems involved, without credentials or secrets;
- the approved knowledge sources and who owns them;
- the identity and permission boundaries proposed for the AI-assisted workflow;
- the human decisions that remain required before a response is sent;
- known failure cases, such as missing documentation, conflicting sources, or an unavailable dependency; and
- sanitized or synthetic examples that represent ordinary, difficult, and out-of-scope requests.

The review would record references to sensitive material in the team’s approved systems rather than copying customer content into this document.

## 3. Workflow boundary

| Stage | Proposed behavior | Human responsibility |
| --- | --- | --- |
| Request arrives | A support specialist classifies the request and decides whether it is in scope. | Confirm the request is eligible for drafting. |
| Sources are selected | The workflow retrieves from the named approved knowledge sources. | Check that the sources are current and appropriate. |
| Draft is produced | The system proposes an answer with source references where available. | Check accuracy, completeness, tone, and whether the answer stays within the allowed boundary. |
| Response is sent | The specialist edits or rejects the draft and sends the final response through the existing process. | Remain accountable for the sent response. |
| Request is out of scope | The workflow declines to draft or routes the request to the existing escalation path. | Handle the request using the approved manual process. |

This boundary leaves sending, account changes, refunds, and other consequential actions with an authorized person. A successful draft is not evidence that those actions should be automated.

## 4. Options to compare

The review would compare the following paths against the actual workflow requirements:

| Path | What to inspect | Questions to answer |
| --- | --- | --- |
| Improve the current process | Knowledge ownership, templates, search, and review routing. | Could the team address the bottleneck without adding an AI dependency? |
| Extend the existing support platform | Available drafting, source controls, identity, logging, and escalation settings. | Can it meet the required boundary and leave enough evidence for review? |
| Buy a specialist capability | Source controls, integrations, data handling, action permissions, and exit path. | What new dependency and operating work would the product introduce? |
| Build a narrow workflow | Retrieval, model access, evaluation, monitoring, support, and rollback ownership. | Does the additional control justify the maintenance and failure surface? |

The recommendation would remain conditional until the team checks the current product configuration, contractual requirements, access model, and test results.

## 5. Proposed pilot tests

These are proposed tests, not completed results:

1. **In-scope answer:** the draft uses the approved source and meets the agreed quality standard after review.
2. **Missing source:** the workflow says it cannot answer or routes to a person instead of inventing a response.
3. **Conflicting source:** the workflow surfaces the conflict and does not silently choose an unsupported answer.
4. **Out-of-scope request:** the workflow declines drafting and preserves the existing escalation path.
5. **Permission boundary:** a test identity cannot retrieve or act on information outside its approved scope.
6. **Unavailable dependency:** the team can identify the failure and continue with a usable manual process.
7. **Reviewer correction:** the team records the edits required before sending and keeps the failed attempt visible.

For each case, the team would agree on the expected behavior, reviewer, evidence reference, and stop condition before looking at outcomes. The [blank pilot evaluation worksheet](https://www.thetechstack.com/resources/ai-pilot-evaluation.md) can hold the plan and observations.

## 6. Deliverable and open decisions

A completed review would return:

- the agreed workflow boundary and accountable human decisions;
- a comparison of the implementation paths against that boundary;
- dependencies and risks grouped by knowledge, identity, permissions, actions, handoff, and operations;
- the pilot cases, acceptance criteria, and evidence references to collect;
- unresolved questions with an owner for each; and
- a bounded recommendation such as continue planning, fix and retest, stop, or propose a limited expansion.

The decision would stay open where evidence is missing. This sample does not assign a readiness score or claim that the fictional workflow is safe, effective, or ready for production.