The AI Agent Pilot That Survives Procurement

A procurement team needs to know what it is buying, which systems the agent can change, and what evidence will justify continuing. A polished demonstration cannot answer those questions on its own. Put the answers into a short pilot agreement before granting production access.

Start with one workflow. For example: classify incoming billing tickets and send uncertain cases to the billing team. That is a different scope from issuing refunds. Name the trigger, allowed actions, excluded actions and person responsible for exceptions.

The five documents to agree before building

The workflow owner should review the examples and results. Security and legal reviewers need the data and access map before sensitive data is connected. Name a delivery owner on the vendor’s side too, so that an unresolved question has somewhere to go.

Make the success metric difficult to game

For the billing example, “tickets handled automatically” is incomplete. Define it as eligible tickets assigned to the correct queue without a human correction, divided by all eligible tickets received during the agreed period. Record exclusions in advance. Otherwise, removing difficult tickets can make the score improve while the team’s work stays the same.

Keep a separate count of missed escalations and prohibited actions. A high average routing score cannot compensate for an unauthorized refund. If the business case is time saved, subtract review, correction and exception handling from the old handling time. Compare a similar mix of tickets and record changes in volume or staffing.

Use historical cases for development and retain unseen cases for acceptance. Include ambiguous messages, duplicate events, missing records and unavailable integrations. Our guide to what an AI evaluation measures explains how to define correct answers and choose a sample that can support the decision.

There is no universal rule that a stop threshold should be half the target. Set the minimum useful result from your economics and required quality. Write down who can suspend the system, how work returns to the existing process, and what evidence permits a restart. A serious failure needs a response immediately, rather than at the next commercial review.

Advance when the evidence is ready

Our published pilot offer runs for 30 to 90 days. That range describes our delivery scope and makes no research claim about how long every project needs. A low-volume workflow may need more time to produce representative evidence.

1. Establish the baseline and access. Approve the scope, data handling, budget and test plan. Confirm that access can be revoked and that somebody owns the existing process.
2. Build and test without live effects. Replay permitted historical cases or run alongside the existing process without sending messages or changing business records. Review disagreements and test recovery after a tool failure. Keep acceptance cases out of tuning.
3. Introduce bounded live operation. The agent acts on its own within agreed limits, checks the result, and sends exceptions to a person. Expand those limits only after testing the relevant failure cases. A high approval rate alone does not establish that broader autonomy is safe.
4. Decide on the agreed date. Continue within the accepted scope, propose a separately scoped expansion, extend once with a specific fix and budget, or stop and hand over. An inconclusive sample is an inconclusive result, not a pass.

If you compare two vendors, give them equivalent permitted test cases and the same scoring rules. Keep their production writes isolated so they cannot change one another’s inputs. A controlled comparison can be useful; running two systems against the same live records without isolation is a different experiment.

Close the security questions before connecting data

Request the actual provider terms and configuration for training use, retention and deletion. “Not used for training” does not mean “never stored.” Include logs, backups and any human access in the review. Ask which party handles an incident, removes access and confirms deletion at the end.

Check disclosure and other legal requirements for the actual use case and jurisdictions with your legal reviewer. A general statement that a vendor is “AI compliant” cannot establish that your deployment is acceptable.

Our trust page documents our controls and subprocessors, with a data processing agreement available on request. It also states that we do not have a SOC 2 report. If a report is a mandatory procurement requirement, resolve that fit before starting the pilot.

Put the full cost beside the result

We agree a fixed fee for the defined pilot scope. Confirm model usage, platform subscriptions, internal staff time and ongoing support separately in the written proposal. Confirm whether model usage, platform subscriptions, internal staff time and ongoing support sit inside or outside the quote. Use the AI agent cost guide to compare the first year, rather than the build fee alone.

A paid pilot can fund defined delivery work. Payment itself does not prove quality, and a free technical test can answer a narrow feasibility question. In either case, agree the staff commitment, evidence, access limits and next decision. Future workflows need their own scope; settle the method for pricing changes before committing to them.

Gartner’s June 2025 forecast of agentic AI cancellations by the end of 2027 identified cost, unclear value and weak controls as risks. It is a forecast. It neither reports an observed failure rate nor proves that this pilot design guarantees success. The evidence that matters for your purchase is the result on your workflow.

Compare implementation and handover responsibilities with the scope of our AI agent development service. Bring the scope and acceptance plan to the vendor conversation. Our 24 vendor questions help test the answers; the pilot offer sets out our published engagement.