An AI-agent RFP should ask a vendor to prove how one defined business workflow will work in your environment. It should not ask for a catalogue of features or accept a generic demo as evidence of readiness.

That is the executive test. A convincing demo can show that a model produces fluent answers. It cannot, by itself, establish that the system will use the right records, respect the right boundary, reveal uncertainty, or leave an accountable person in control when the consequence is material.

For a CEO, CIO, CFO, COO, or commercial leader, the goal is not to select the most impressive agent. It is to decide whether a supplier can support a specific business job without creating an unowned layer of data access and decision risk.

Its practical output is a short, evidence-led procurement packet that lets an executive sponsor compare vendors on a real workflow.

Start with a decision, not an agent category

“We need an AI agent platform” is not an evaluable requirement. It bundles very different jobs: preparing a pipeline-risk review, reconciling an exception queue, drafting a board-reporting packet, or routing a customer issue for human review. Each has different sources, permissions, failure costs, and owners.

Write the RFP around one recurring decision. For example:

Before the weekly forecast meeting, prepare a reviewable list of opportunities whose forecast requires executive attention. Use only approved CRM, activity, support, and delivery records. Show the supporting evidence and unresolved conflicts. Do not change forecasts, contact customers, or send messages.

This is deliberately narrower than “improve forecasting.” It gives every vendor the same job, creates a fair basis for comparison, and makes it possible to reject an answer that sounds capable but fails the actual workflow.

The guide to evaluating an AI agent for business data explains how to turn that job into realistic test cases. An RFP comes before a pilot; it should make clear what the pilot must demonstrate.

Ask for evidence in the response format

For every question below, require four things: a direct answer, the product or operating evidence behind it, the limitation or exception, and the person accountable for it. “Supported” is not an answer if a capability depends on custom work, a particular deployment model, a customer-owned control, or a later roadmap decision.

The questions are grouped by the decisions an executive team actually needs to make.

1. What job will the agent own—and what is out of bounds?

  1. Which recurring business decision does the proposed workflow prepare, and who owns that decision? Ask for a one-sentence job statement and a named operating role, not a broad promise of productivity.
  2. What may the agent do, recommend, and never do in this workflow? Separate retrieval, analysis, drafting, routing, and external or system-changing action.
  3. What conditions cause the workflow to stop, escalate, or ask for clarification? A vendor should be able to name missing evidence, conflicting records, ambiguous instructions, and material-risk thresholds.

These questions prevent the RFP from quietly turning an investigation assistant into a decision-maker. They also make the proposed scope comparable to the company’s own risk tolerance.

2. What records will it see, and why?

  1. Which exact sources, objects, and fields are needed for the first workflow? Require the smallest viable source set, including freshness expectations and source owners.
  2. How does access reflect the requesting user’s identity and each source’s authorization? Do not accept a vague assurance that the vendor has role-based access control. Ask how user identity, tool permission, record-level access, and service credentials work together.
  3. How will the response show its evidence and its limits? The reviewer should be able to see the relevant source record or citation, the time boundary, and material uncertainty without reconstructing the answer from scratch.

That distinction matters because an agent can be technically able to retrieve data and still be wrong to reveal it. The AI-agent permissions guide is useful for separating identity, tool scope, data authorization, and human approval into distinct controls.

3. How will the organization verify the answer before it matters?

  1. What does a good answer look like for this job, and how will it be measured? Require task-specific acceptance criteria for evidence, correctness, usefulness, and safe handling of exceptions.
  2. What test set will the vendor run before production? It should include representative records, ordinary cases, conflicts, stale inputs, missing permissions, and known hard cases from the business.
  3. How will the vendor demonstrate failure recovery? Ask to see the output when a source is unavailable, two systems disagree, or the workflow cannot determine an answer.

NIST’s Generative AI Profile frames generative-AI risk management around governing, mapping, measuring, and managing risk. For an RFP, that is a useful discipline: define the context, test the use case rather than an abstract model, and decide what evidence warrants continued use.

4. Where does human authority remain?

  1. Which recommendations require review, approval, or a second source before they can affect a customer, employee, financial record, contract, or external communication? The response should name the reviewer and what they will see.
  2. Can a reviewer correct an answer, reject a recommendation, and record why? A usable control is not an “approve” button. The person needs the proposed action, evidence, uncertainty, and consequence of proceeding.
  3. What is the complete audit trail for one run? Ask the vendor to show the request, identity context, sources consulted, tools used, output, human intervention, and resulting action or non-action.

The security posture should match the authority granted to the workflow. The OWASP Top 10 for Agentic Applications is a useful current prompt for the security review because it focuses on risks in systems that plan, act, and make decisions across workflows. It is not a certification checklist; your security, legal, and risk teams should decide which controls fit the proposed use.

5. Can the vendor operate the workflow after the demo?

  1. What changes when a source schema, business definition, model, connector, or permission policy changes? Require the owner, test process, communication path, and rollback or stop behavior.
  2. What will the executive sponsor receive during the pilot and after launch? Good answers include adoption, exception patterns, evidence quality, access failures, unresolved corrections, and the business outcome the workflow was meant to improve—not just usage counts.
  3. What is the 30-day pilot plan, including a go, revise, or stop decision? Ask for a limited user group, a shadow or review-first phase where appropriate, a test schedule, and named decision rights.

This is where many evaluations become more than a scorecard. A pilot should expose whether the vendor and internal owners can run the workflow together. The 30-day AI-agent pilot plan provides a practical sequence for keeping that first test bounded.

Score vendors on proof, not confidence

Use a simple scoring sheet, but do not reduce every question to a yes-or-no feature check. Score the evidence supplied for the workflow you defined.

Evaluation dimensionWhat a strong response demonstratesExecutive red flag
Workflow fitA specific job, source boundary, decision owner, and out-of-scope listA broad claim that the platform “handles any process”
Data and accessNamed sources, permission model, access limitations, and data ownersA promise to connect everything first and govern later
Evidence and evaluationA test plan with source-backed outputs, edge cases, and acceptance gatesA benchmark, generic accuracy claim, or scripted demo as the only proof
Human controlClear approval points, escalation behavior, and a usable review recordA reviewer who receives a recommendation without evidence or consequences
OperationsChange management, support boundaries, monitoring, and stop criteriaNo answer for what happens when a source, definition, or policy changes
Pilot readinessA limited test with a baseline, owner, review cadence, and go-or-stop gateAn open-ended proof of concept with no decision date

Weight the dimensions according to the job’s consequence. A workflow that prepares a meeting brief may need a different threshold from one that informs payment, pricing, customer commitments, or employment decisions. Procurement can keep the scoring process consistent; the executive sponsor should retain responsibility for the risk trade-off.

Run one comparable vendor exercise

Do not ask every vendor to invent its own success case. Give each finalist the same small, representative exercise and the same permitted evidence. For a pipeline-review workflow, that might include several ordinary opportunities, one record with conflicting information, one account with restricted context, and one case in which the correct output is “insufficient evidence.”

Then have the people who will own the business decision review the result with security, data, and operational stakeholders. The questions are straightforward:

  • Did the result help the owner make the stated decision?
  • Could the reviewer trace the important conclusion to approved records?
  • Did the workflow respect the stated exclusions and permissions?
  • Did it surface uncertainty instead of smoothing it over?
  • Could the team explain what would happen after a correction or source change?

This exercise also makes the build-versus-buy choice clearer. A vendor’s capability matters, but so do the recurring responsibilities your organization would assume if it built and operated the workflow itself. Use the build-versus-buy framework for AI agents to make those operating costs and control obligations explicit.

Treat the RFP as the first operating contract

The best AI-agent RFP does not attempt to predict every future use case. It creates a disciplined first decision: whether a vendor can help the organization operate one valuable workflow with appropriate context, evidence, and accountability.

That is a better basis for expansion than a feature checklist. If the first workflow works, it leaves behind reusable habits: a clear job definition, source boundaries, preference and ownership rules, test cases, and a shared record of how human judgment enters the process. If it does not, the organization has learned where the gap lies before granting broad access or making the agent part of a critical operating rhythm.

Jovis is designed for teams that need to investigate approved business context in a shared workspace and keep the evidence visible to the people accountable for the outcome. The right evaluation begins with one real executive workflow.