How to set meaningful milestones for an AI implementation

Tie a milestone to an artifact a business owner can inspect or an action they can demonstrate. “Integration 80 percent complete” gives a sponsor little basis for releasing budget or planning staff time. A named milestone such as “the service desk receives a correctly linked draft in our test queue” can be verified.

Keep the decision visible at each stage

During discovery, produce an agreed workflow, boundary and casebook. The decision is whether the problem is sufficiently defined to build. During the pilot, show representative work reaching a test destination, including a case that requires human review. The decision is which categories are ready for a limited release.

At limited release, choose an operating group, an owner and a volume the team can supervise. Record actual review time, corrections and unresolved items. For a commercial maintenance business, a useful milestone might be preparing work order drafts for one region while site supervisors retain dispatch authority. Expand to another region only after checking its site codes and approval rules.

Plan the last milestone while writing the first

Handover should prove that staff can operate the workflow when the builder is unavailable. Have the operator find a stuck item, complete it manually and identify the record showing what was done. Confirm access, support hours, release notes and the ability to pause the system.

Put a decision owner and evidence requirement next to every milestone. If a stage misses its target, the team should know whether to revise the scope, repair a dependency or end the pilot. A sponsor who can see exactly what has been demonstrated can make that decision without deciphering a percentage reported in a status meeting.

Put this into practice

Bring a sample of the work and the tools your team uses. We can help define a first project, who reviews it, and how to tell if it works.

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