AI assistant use case

AI assistant for project health review

Use AI-supported review to test whether project information is clear, current and ready for the next governance conversation.

The problem

Why this workflow matters

Project health is rarely hidden because one metric is missing. It is usually scattered across status reports, RAID logs, decision records, financial notes, change impacts and informal sponsor conversations.

A project can look green while key decisions are overdue, risks have no owners, benefits are unclear or the next steering committee pack does not explain what action is needed. The challenge for the project manager is to see those gaps before the governance meeting does.

A useful AI assistant should help review the evidence already available, identify unclear or inconsistent signals and prepare a sharper conversation about what needs attention.

The solution

How an AI assistant can help

For project health review, the PMOEasy AI Assistant workflow is being shaped around structured evidence review. The assistant should help users inspect the artefacts they already maintain, such as status reports, RAID logs, issue logs, decision logs and benefits registers.

The goal is to identify gaps and questions: outdated risks, missing owners, unclear decisions, weak evidence for RAG status, actions without dates, or benefits that are not connected to current delivery work.

The assistant should support the project manager before governance forums by turning scattered delivery information into a clearer review checklist and a more focused set of escalation points.

Why you need this

Before and after the workflow

Before using the workflowAfter using the workflow
Health status depends on a broad narrative update.Health status is reviewed against risks, decisions, actions and evidence.
Governance packs bury what needs attention.The next decision, escalation or confirmation is easier to see.
Issues are found late in steering forums.Gaps are surfaced earlier for project-team review.

How to use it

A practical AI assistant workflow

1

Collect the active evidence

Bring together the latest status report, RAID log, decision log, issue log, change requests and benefits information.

2

Ask for a gap review

Use the assistant to find missing owners, stale dates, unclear actions, conflicting status messages and items that need sponsor attention.

3

Separate facts from judgement

Keep evidence, assumptions and recommendations separate so reviewers can understand what is known and what needs a decision.

4

Prepare the governance conversation

Use the review output to refine the status report, steering pack, decision log and action list before the meeting.

Prompt examples

Useful starting prompts

  • Review this project health evidence and identify unclear RAG rationale, missing owners, stale dates and governance questions.
  • Summarise the top project health concerns from this status report and RAID log without inventing new risks.
  • Turn these delivery notes into a steering committee readiness checklist.

Frequently asked questions

What to know before you use AI support

Is this the same as project assurance?

No. It can support preparation for assurance or governance review, but formal assurance still needs the organisation's agreed review method and accountable reviewers.

What artefacts should be reviewed together?

Start with the status report, RAID log, decision log, issue log, change requests, action register and any current benefits or milestone evidence.