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Choosing the first workflow
First Workflow Selection Rubric
Use this to compare candidate workflows and choose the best first AI deployment target.
Step 1
Answer guided questions
Step 2
Get verdict
Step 3
Use result in strategy session
Candidate Comparison
Name your workflows. Score them. See which one to build first.
Use this to compare candidate workflows and choose the best first AI deployment target.
5-7 minutes6 dimensions
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Selection rubric
Example output from the ADA method.
Frequency
Does the workflow happen weekly or more often?
Value
Would improvement reduce delay, missed revenue, rework, customer friction, or owner time?
Reviewability
Can a human owner judge the output quickly?
Evidence
Does the source material already exist?
Risk
Can the first version stay away from final decisions, legal exposure, and customer commitments?
Time to value
Can the first useful version be tested in 30 days?
What most teams choose instead
Teams often pick the loudest demo. That creates excitement, not revenue. A first workflow should be boring enough to actually run, and tied to a number the business cares about, response time, margin, capacity, retention, important enough that the gain shows up in the first cycle.
ADA's default recommendation
Start with a workflow where AI prepares work for review: lead routing, proposal checks, onboarding missing-item review, reporting briefs, or support escalation summaries.
What should be parked
Park workflows that require final judgment, sensitive data, legal approval, pricing decisions, or customer-facing promises before the review process exists.
Quality Bar
Use these checks before calling the workflow ready.
The first workflow can be explained without mentioning a model name.
The selected workflow creates an observable before/after difference.
A human owner can review normal cases and edge cases.
The first test can run with real work within 30 days.
The chosen workflow teaches the company how to deploy the next one.
Where This Helps
Use it before build decisions get expensive.
AI roadmap sorting
Leadership planning
Department request review
Implementation sprint selection
Research Basis
Built against practical AI risk and quality standards.
NIST AI RMF PlaybookSupports mapping intended use, context, measurement, and risk management before rollout.ISO/IEC 42001Frames AI as a management system with policies, objectives, processes, and continuous improvement.OECD AI PrinciplesSupports oversight and safeguards appropriate to the business context.
Related Resources
Read this with the workflows and service pages it supports.
FAQ
Why does the first workflow matter so much?
The first workflow sets the operating pattern for AI: evidence, owner, review point, stop rule, and metric.
Should we start with the biggest problem?
Not always. Start with a meaningful problem that can be reviewed safely and tested quickly.
What is a poor first workflow?
A poor first workflow is high-risk, hard to review, data-poor, or owned by nobody.
Next Step
Use this result on a real workflow.
Bring the bottleneck, current handoff, and the result you want to improve.