Agentix Labs implementation resource

AI Agent Implementation Scorecard

Use this scorecard before greenlighting an AI agent project. It separates attractive demos from workflows that have clear value, usable data, defined risk, and a realistic path to production.

1. Workflow fit

  • The workflow repeats often enough to justify automation.
  • The current process has visible handoffs, delays, or quality drift.
  • The desired agent output can be judged with clear acceptance criteria.
  • There is an accountable owner for the workflow outcome.

2. Data and tool readiness

  • The agent can access the documents, systems, or APIs it needs.
  • Sensitive data boundaries are known before the pilot starts.
  • Tool permissions can be scoped to least privilege.
  • There is a logging path for prompts, actions, tool calls, and results.

3. Risk and guardrails

  • High-risk decisions require human approval or escalation.
  • Failure modes have rollback or manual fallback steps.
  • Compliance, privacy, and brand constraints are written down.
  • The pilot can run in a limited scope before broader rollout.

4. Business case

  • Success is tied to one or two business metrics.
  • The team can estimate time saved, revenue lift, risk reduction, or response-time improvement.
  • The workflow owner will review pilot results within 30 days.
  • There is budget or internal capacity to maintain the agent after launch.

How to score it

Give one point for every checked item. Then use the result to decide what happens next.

Need help turning a promising workflow into a governed pilot? Book an AI automation consultation with Agentix Labs.