You have decided that outside help may fit one AI workflow. Now you must determine what each consultant is proposing and what evidence supports it. Before you approve discovery or a pilot, ask for details you can inspect. These details include the delivery team, workflow boundary, deliverables, exclusions, acceptance evidence, access, ongoing costs, ownership, and handoff.
If you are still deciding between a self-serve tool, an internal build, a contractor, or an implementation partner, use the AI implementation path decision matrix first. This guide starts after you decide to interview a consultant or implementation partner. It helps you compare candidates without treating company size, technical vocabulary, or a polished demonstration as proof.
Ask who will do the work and what each person owns
Ask: “Who will do the work, and what does each person own?”
A useful answer separates the sales conversation from delivery. It names the delivery lead, the people who will design or build the work, any subcontractors, and the client roles needed for decisions and review. It also explains who can approve a scope change, who handles a technical or security question, and who remains responsible after launch.
Ask to see this information in the proposal or scope of work. The document should identify each role, its responsibilities, the expected participation, and the contact for escalation. If a named person can change before work begins, the proposal should explain how the consultant will report and approve that change.
A long list of skills does not answer the question. You need to know who will make the decisions, who will do the work, and who will be available when the workflow reaches an exception.
Ask for one named workflow and a written definition of complete
Ask: “Which workflow are we approving, what is included, and what evidence will mark the work complete?”
The answer should name one workflow in plain language. It should show what starts the work and which systems and data are involved. It should also name the current owner, the actions that stay with a person, and the outcome that ends the workflow. A broad goal such as “use AI in customer operations” is too wide for an estimate or acceptance decision.
The proposal should then list deliverables, exclusions, dependencies, and buyer responsibilities. Dependencies can include representative examples, access to systems, reviewer time, source cleanup, or a decision from a security or legal owner. An exclusion is useful because it prevents a pilot result from being treated as proof for work that the team did not test.
Acceptance must also be visible before the work starts. Ask for the test cases, required behavior, unacceptable failures, reviewer, and record that the parties will use to accept, revise, or stop the work. The acceptance evidence can vary by workflow. It can include reviewer decisions, source checks, exception handling, a controlled sample of cycle time, or proof that a system handoff completed as agreed.
A discovery and a pilot produce different evidence. Discovery should end with a recommendation and a bounded scope. A pilot runs the agreed test and should show what passed, what needed correction, what failed, what stayed manual, and what the team can decide next. Confirm which stage the proposal covers before you compare prices or schedules.
Ask for proof that matches the constraint in your workflow
Ask: “Which prior work is relevant to this workflow, and what can we inspect?”
Relevant proof does not have to duplicate your project. It should make the comparison clear. A candidate might show evidence from a similar system integration, data boundary, review step, action risk, or handoff requirement. The candidate should also state what that example does not prove about your workflow.
Ask for the artifact that supports the claim when the client has approved its release. This can be a published case study, a working product, a sample deliverable, a technical note, or another item you can inspect. Confidential work can remain confidential. In that case, the consultant should describe the comparable constraint and the limit on what can be shared without turning private work into an unverifiable promise.
Use published case studies as one source of evidence, not as a guarantee. Read the constraint, what was delivered, and the stated result. Then identify the work that your proposal still needs to test. A successful project for another client does not set your acceptance criteria.
Inspect the access plan before anyone shares credentials
Ask: “What data, accounts, credentials, and permissions will you need, and how will access be removed?”
The written access plan should list each system, the required data or fields, the permission level, and the account owner. It should name each third-party service that can receive project data and the applicable storage or retention settings. It should also state which logs the workflow creates and who approves risky actions.
Use least privilege for each person and system. Least privilege means that each account gets only the access required for its current task. Prefer client-owned accounts and temporary access when they fit the work. Do not share production credentials only because a demonstration needs more convenient access.
The exit path belongs in the same plan. Record who will revoke vendor access, rotate or remove credentials, transfer client-owned accounts, export client material, delete temporary copies, and retain any required logs or project records. The AI workflow data security guide provides a fuller set of fields for sensitive workflows. It does not replace review by your legal, privacy, security, or compliance owners when the workflow requires them.
Read the estimate as a boundary around the work
Ask: “What does the estimate include, which costs continue, and how are changes approved?”
A fixed price, time-and-materials estimate, staged engagement, or retainer can each fit some work. The useful test is whether the commercial structure makes the boundary visible. The estimate should identify the workflow, deliverables, exclusions, assumptions, dependencies, acceptance evidence, and the conditions that can change time or cost.
Separate the consulting or build cost from the cost to operate the workflow. Provider or model use, hosting, software licenses, monitoring, storage, security services, and support can continue after the first engagement. Ask the estimate to mark each expected item as included, excluded, client-paid, estimated, or unknown. When the information is available, it should also name the provider, charging unit, and billing account owner.
New information can change legitimate work. The proposal should explain how the parties record a change, who can approve it, and how the change affects scope, schedule, and cost before added work begins. The BaristaLabs pricing and engagement guide shows the boundaries BaristaLabs publishes for discovery, pilots, implementation, recurring costs, acceptance, and changes. It is an example of one firm’s approach, not a universal quote or market benchmark.
Define ownership, handoff, and support before the build begins
Ask: “What will we own and receive, and what happens after handoff?”
The agreement should state who owns or can use the code, prompts, configurations, documentation, test cases, accounts, and other project artifacts. It should also list what the client receives. Do not assume that access to a working demonstration includes repository access, deployment notes, configuration details, or the right to move the work to another provider.
A useful handoff can include the repository or exported configuration, deployment instructions, and a list of accounts and dependencies. It can also include test cases, results, known limits, operating notes, and the owner of the next decision. The exact set depends on the work. Name it in the scope so the final review does not depend on what each party thought “documentation” meant.
Support needs a separate boundary. Record who monitors the workflow, who responds when a source or integration changes, which response times apply, which work is maintenance, and which work needs a new estimate. If support is optional or excluded, the handoff should make the client’s maintenance responsibilities clear.
Compare the evidence before you approve the next stage
Use one row per candidate and record where each answer appears. The location can be a proposal, scope of work, agreement, case study, access plan, test plan, or handoff list. Mark an item as unknown when the evidence does not exist yet.
Scroll sideways to see all 2 columns.
| Decision area | Evidence to inspect before approval |
|---|---|
| Delivery team | Named roles, responsibilities, client participants, subcontractors, and escalation owner |
| Workflow and scope | Trigger, owner, systems, inputs, outputs, included work, exclusions, dependencies, and buyer responsibilities |
| Acceptance | Test cases, required behavior, unacceptable failures, reviewer, and acceptance record |
| Relevant proof | Comparable constraint, inspectable artifact, stated result, and limit on what the example proves |
| Access | Systems, data fields, permission level, account owner, third-party exposure, logs, and removal plan |
| Cost and change | Included work, recurring costs, assumptions, change approval, and effect on schedule and cost |
| Ownership and handoff | Ownership terms, materials delivered, operating notes, known limits, support boundary, and maintenance owner |
Compare the records, not the confidence of the presentation. A candidate can give a careful answer that includes unknowns. That is more useful than a precise promise that has no workflow boundary or acceptance method.
The evidence should lead to a specific next decision. Approve scoped discovery when the main unknown is which workflow or boundary deserves a test. Approve a pilot when the workflow, access, test cases, reviewers, dependencies, exclusions, and acceptance evidence are clear enough to run one. Ask for a revision when a material term is missing, and stop when the proposed evidence cannot support the decision you need to make.
Choose the next action from the evidence you have
If you have not selected an implementation path, complete the implementation path decision matrix before you compare consultants. It will help you decide whether the workflow fits a tool, internal work, a contractor, or an implementation partner.
If you can name one candidate workflow but still need help defining its boundary or first test, review BaristaLabs AI consulting. Bring the current owner, systems, data involved, review point, consequence of a bad result, and the decision you need the work to support. The first conversation should determine whether discovery, a pilot, more preparation, another path, or no build is the useful next step.
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