How can AI help identify project risks?

Short answer

AI is good at spotting the risks that were said out loud and then forgotten. It reads every meeting for conditional language ('if the vendor is late', 'assuming the data is clean'), for assumptions nobody validated, for dates with no owner, and for statements that contradict an earlier decision. It will not predict risks nobody mentioned, that still needs experience.

How to do it

1
Harvest the conditionals
Every 'if', 'assuming', 'as long as' in a transcript is a candidate risk with a trigger already written.
2
Turn assumptions into risks
An assumption that nobody has verified is a risk with a probability of being wrong. Record who would confirm it.
3
Cross-check decisions
A new statement that conflicts with an earlier decision is a scope risk; flag it the same day, not at the review.
4
Score and assign
Give each risk an impact, a likelihood, an owner and a mitigation. A risk with no owner will not be watched.
5
Re-read the register every meeting
Risks that were closed by a decision should be closed in writing too.

Good to know

Most project risks appear in conversation before they appear in a register.
A contradiction between two meetings is detectable automatically; its resolution is a human decision.
Segua.ai records risks, open questions and contradictions per meeting, each linked to its source line.
Segua.ai never infers emotions or attitudes of participants, that is prohibited by the EU AI Act.

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Paste a transcript or let Segua.ai join your next call, then read the documents it writes.

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Other answers

Requirements

How do I turn a meeting transcript into requirements?

How to do it

Good to know

Related questions

See it on your own meeting

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