Enterprise Intelligence Group

A 90-Day Retail AI Planning Example: Decisions Before Deployment

An illustrative sequence for scoping, testing and reviewing one retail AI workflow. Progress depends on evidence and readiness, not a promised result by day 90.

Where should a retail AI initiative start? With a defined operating decision and the evidence needed to assess whether AI is appropriate.

The sequence below uses 90 days as an illustrative planning horizon. It is not an EIG client case, a standard delivery commitment or a guarantee of savings. Access, data quality, integration, approvals and the consequences of failure determine what can responsibly be completed. A phase may need to be extended, repeated or stopped.

First phase: define the decision and the test

Choose one workflow, such as preparing a category review or assembling evidence for a planning exception. Describe what happens today, who owns the decision and which inputs the proposed assistance would require.

• Record the intended business outcome and its current measure, where available.
• Identify authorized sources, missing information and confidential material.
• Separate tasks the system may perform from decisions requiring approval.
• Define representative cases, important exceptions and unacceptable outcomes.
• Compare AI assistance with simpler process, reporting or configuration changes.

The decision at this stage is whether the use case is sufficiently clear and testable to proceed. A missing baseline or unresolved access requirement is an open dependency, not a reason to invent a number.

Second phase: test a bounded workflow

If the entry conditions are met, test with permitted data and the people who would use the output. Representative exceptions matter as much as routine cases.

For example, a planning assistant should distinguish confirmed supplier capacity from an assumption and identify when a required input is unavailable. A plausible recommendation is insufficient if its sources, constraints or approval path cannot be checked.

Record errors, review effort, unresolved dependencies and the work required to integrate the workflow. A successful demonstration does not establish production readiness. Security, permissions, operating ownership and failure handling require their own acceptance evidence.

Third phase: evaluate readiness and decide what follows

Compare results using consistent definitions and record other changes that could affect the outcome. Include the effort required to review and correct outputs; do not count only the automated step.

The next decision may be a controlled rollout, further testing, a narrower use case or no deployment. If rollout is justified, agree ownership, monitoring, escalation, rollback and the next review point.

What the planning horizon should leave behind

A useful record includes the workflow boundary, evidence and assumptions, test results, outstanding risks, accountable owners and a justified next decision. A project can produce valuable evidence that an approach is unsuitable. It does not need to claim a financial win to justify an honest conclusion.

EIG offers a scoped review of AI workflows, decision context, authority and performance. The work and any subsequent implementation are agreed separately; AI is not required for other EIG consulting engagements.

Discuss an AI workflow and performance review.

The EIG Library  ·  Insights  ·  AI Maturity Assessment  ·  Contact