AI Agent Vendor Evaluation Scorecard

You sit through three AI agent demos. Each agent answers the opening question, finds a sample record, and completes the scripted task. Every presentation looks capable. By the end, the providers are beginning to sound the same.

That is because the demo removed the conditions that separate a production system from a presentation. The data was clean. The request was familiar. The password worked. No policy exception appeared. No customer changed direction halfway through the task.

A polished conversation proves very little.

Your operation will supply duplicate records, ambiguous requests, expired credentials, unavailable systems, and missing information. The agent must still complete the work, stop safely, or hand the case to the right person.

The evaluation should answer one question: can this provider help you run a defined workflow in production at acceptable quality, control, and cost? Use the same workflow, cases, evidence, and scoring rules for every provider. The primary outcome is a defensible selection, not a memorable demo.

Before any provider earns a score, define the work it is being asked to prove.

Set the evaluation gate before the score

Write a one-page use-case brief before meeting vendors. Name the trigger, required inputs, allowed actions, final state, systems, channels, approval gates, exception types, volume, baseline, and accountable owner.

Reject any evaluation that cannot be tied to this brief. A provider may have impressive capabilities that do not solve the assigned work. The scorecard compares fit for the use case, not the size of the feature list.

NIST's AI Risk Management Framework Playbook recommends policies for third-party AI systems, transparency into system functions and limitations, thorough testing, clear usage instructions, lifecycle considerations, auditability, and logging. Turn those principles into requested evidence.

With the gate defined, the scorecard can focus on what separates one provider from another in production.

Use seven weighted categories

1. Complete the work: 25 points

Can the agent move from trigger to verified final state? Ask the provider to demonstrate the exact workflow with representative cases. Score:

• Communication across the channels the role requires.
• Correct use of the business systems and browser interfaces in scope.
• Accurate data entry and record selection.
• Completion verification after an action.
• Safe handling of missing information and duplicate work.
• Continuity when the channel or employee changes.

Do not award full points for a partial action that leaves an employee to finish the process. Define acceptable completion before the test.

2. Control and governance: 20 points

Ask who can define, approve, change, pause, and audit the agent. Score the provider's support for role boundaries, approval gates, human-only decisions, version history, change review, exception ownership, retention rules, and an emergency stop.

Look for an operating record, not a promise of responsible AI. The U.S. Government Accountability Office organizes AI accountability around governance, data, performance, and monitoring. Those categories are useful because they force the evaluation beyond the model response.

3. Testing and reliability: 15 points

Ask how the provider builds evaluation sets, tests workflow changes, handles model changes, monitors drift, and records failures. Require evidence for routine cases, edge cases, unsafe inputs, unavailable systems, retries, and recovery.

Ask what appears in the denominator of every rate. A completion rate can exclude failed starts, transfers, or cases the agent never accepted. Score higher when definitions are explicit and raw case evidence can be inspected.

4. Security and access: 15 points

Map the identity, permissions, credentials, files, networks, destinations, and records the agent can reach. Score least-privilege access, separation of environments, secure credential handling, encryption, logging, retention controls, incident response, vulnerability management, and independent assurance relevant to your requirements.

A computer-enabled agent can take action inside business software. Security therefore includes what the agent is allowed to do after authentication, not only how data is stored.

5. Production operating model: 10 points

Ask who owns launch, monitoring, incident response, optimization, employee training, and workflow changes. Identify the service boundary between your team and the provider. Score the time and skill required from your employees, the escalation route, support coverage, and the process for resolving a production defect.

If the answer is that your team will manage it, calculate that work. An easy build can still become an expensive operation.

6. Economics: 10 points

Request a cost model tied to the unit of work. Include implementation, platform fees, usage, communication, environments, monitoring, human oversight, exceptions, support, changes, and expected internal labor.

Score the provider on cost transparency and cost per acceptable completed outcome. A low price per minute or model call may produce a high cost per result when completion is low or human cleanup is high.

7. Adoption and support: 5 points

Frontline employees will discover cases the buyer and provider missed. Score how the provider gathers feedback, explains agent behavior, trains users, communicates changes, and supports the people who own exceptions.

Five points is enough to matter without allowing a friendly sales process to outweigh production evidence.

The weighted score narrows the field. It does not settle the decision. The strongest providers still need to perform the same difficult work under the same conditions.

Build a controlled bakeoff

Create a representative test set before vendors see it. A practical starting set might contain 40 cases: 20 routine, 10 variations, five known failure cases, and five unsafe or out-of-scope cases. This mix is an illustrative recommendation, not a universal standard. Adjust the size and mix to the risk and variation in your workflow.

Give every provider the same inputs, systems, permissions, time window, and success criteria. Require each agent to produce the final record and action log. Do not accept a narrated demonstration in place of the work.

Score each case as acceptable, unacceptable, or correctly escalated. Then inspect the failure reasons. A provider with fewer total errors may still have the wrong risk profile if its errors include unauthorized actions or silent false completion.

Ask for evidence behind every material claim

For claims about accuracy, completion, uptime, deployment time, savings, or return, request:

• The metric definition and denominator.
• The workflow, customer population, and time period.
• The sample size.
• Whether the result came from a test, pilot, or production system.
• Which cases were excluded.
• Who measured the result.
• Whether your use case, channels, and systems are comparable.

Do not turn another customer's result into your forecast. Use it to shape a testable hypothesis for your own pilot.

Once the claims have been reduced to evidence, separate preferences from requirements. Some controls cannot be traded for a better feature score.

Separate required gates from weighted preferences

Some requirements should not be traded for a higher total score. Create pass-or-fail gates for security, privacy, legal review, data location, identity, deletion, audit access, insurance, accessibility, or another requirement your organization must meet.

Apply the gates before ranking vendors. A provider that fails a mandatory control does not win by scoring well on features.

Check the contract against the operating claim

If the sales process promises an outcome, confirm how the agreement defines and reports it. Check implementation responsibility, acceptance criteria, change scope, support response, data ownership, log access, subcontractors, model changes, incident notice, export, termination, and transition.

Have the appropriate legal, security, privacy, procurement, and operational owners review the terms. A scorecard supports their decision. It does not replace it.

The contract can align the promises and responsibilities. Only live work can show whether the operating model holds.

Make the pilot the final evaluation stage

The shortlist should end with a bounded paid pilot using live work, approved access, named exception owners, and documented stop conditions. Compare production results with the manual baseline. Measure acceptable completion, human minutes, cycle time, rework, exceptions, cost, and any outcome-specific value.

A pilot is not an indefinite experiment. Set a decision date and the evidence required to expand, revise, or stop.

Keep the scoring record after selection. It becomes the first operating review. The same evidence can show whether the chosen provider delivered the controls, support, economics, and workflow quality used to justify the decision. Re-score material changes instead of treating the original review as permanent.

Vida helps teams build and manage outcome-based AI agents that communicate, use approved software, complete workflows, request approval, hand off exceptions, and report work. The evaluation can begin with your workflow and your evidence.

Bring us the scorecard and the cases that matter. We will show the work, including where the agent should stop. Evaluate a Vida Pilot.