AI Automation Readiness Checklist: Choose a Practical First Project
A useful first automation project starts with a recurring business task, a clear owner, and a result you can measure. A tool demonstration is useful later. First, decide what work should improve and how your team will know the change helped.
This checklist helps operations leaders choose a bounded pilot. It is a planning framework, not a guarantee of savings. Use it before commissioning an AI agent, connecting a new workflow platform, or building custom software.
1. Describe one workflow from start to finish
Write down the trigger, inputs, decisions, systems, and expected output. For example: a customer submits a service request; an employee identifies the request type, checks the CRM, assigns an owner, and prepares a response.
Capture the exceptions too. What happens when the customer is missing from the CRM, the request is ambiguous, or the assigned employee is unavailable? If the team cannot describe the process consistently, begin with process clarification.
- What starts the task?
- Who is responsible for completing it?
- Which decisions follow fixed rules?
- Which decisions require interpreting language or documents?
- What happens when the process fails?
2. Decide whether the task needs AI
A fixed routing rule may only need ordinary workflow automation. Reading varied request descriptions may benefit from AI-assisted classification. A project can combine both: use deterministic rules for known conditions and an AI component for a narrow interpretation task.
Start with the smallest useful scope. For an intake workflow, a first pilot could suggest a category and owner while an employee confirms the result. Automatically changing customer records or sending external messages can be considered after the pilot demonstrates reliable behavior and the business defines appropriate controls.
3. Check the data you actually have
List the records, documents, and reference material the workflow needs. Check whether they are current, consistently formatted, and available to the people and systems doing the work. Record access constraints before selecting a tool.
Build a representative evaluation set from information you are authorized to use. Include typical tasks, incomplete inputs, duplicates, and unusual cases. Keep a separate set of examples for testing changes so the team is not judging a system only on the examples used to build it.
4. Verify each integration
A promising demonstration can hide integration work. Confirm how the solution will read and update your CRM, ticketing system, accounting platform, or internal application. Check which actions are supported, how permissions are limited, and how errors are reported.
Ask the delivery team to explain what happens when a system is unavailable or sends the same event twice. The design should include a way to avoid duplicate work, a retry policy, and an owner for failures. These details belong in the project scope.
5. Define a baseline and a success measure
Measure the existing process before the pilot starts. Useful measures include handling time, turnaround time, correction rate, and the share of tasks that need escalation. Select the measures that match the business problem.
Here is an illustrative capacity calculation, not a Midwest Digital client result. A team processes 300 requests per month at eight minutes each. That is 40 hours of handling time. If a pilot reduces average handling time to five minutes, the gross capacity released is 15 hours per month. Subtract ongoing review, maintenance, and exception-handling time before assessing the result. Released capacity is not automatically cash savings.
Include software usage, integration support, implementation, and ongoing ownership in the cost comparison. A faster workflow that creates more rework may not be an improvement.
6. Assign ownership before launch
Name a business owner and a technical owner. The business owner decides whether the workflow is useful and which errors are unacceptable. The technical owner monitors failures, manages access, and maintains the integrations.
Write down when a person must review an output, how staff can override a decision, and how to stop or roll back the workflow. Agree on retention and access requirements for the information involved. Do not assume that a tool's default configuration fits your business.
A simple readiness scorecard
Mark each item green when it is documented, amber when it needs work, or red when it is unknown. This is a discussion aid; the colors are not a validated prediction of project success.
| Area | Evidence to collect |
|---|---|
| Process | A workflow map, a named owner, and documented exceptions. |
| Data | Representative examples, access permission, and a quality review. |
| Integration | Confirmed read/write methods, failure handling, and a test environment. |
| Measurement | A baseline, success criteria, and a method for tracking rework. |
| Operations | Monitoring, human review, maintenance ownership, and rollback instructions. |
Resolve red items that prevent safe testing before expanding the pilot. Prioritize a workflow with manageable exceptions, accessible data, and an owner who can validate results. A narrow project that works reliably creates a stronger foundation for later automation.
Prepare a one-page project brief
Summarize the workflow, current problem, systems involved, known constraints, desired outcome, and decision owner. Add the evidence still missing. This gives potential delivery partners something concrete to scope and makes proposals easier to compare.
Midwest Digital provides AI consulting, workflow automation, and custom software services. To discuss a potential first project, share your workflow and goals.