Using AI to Analyze Meeting Transcripts for Clarity
Demonstrates analyzing meeting transcripts with AI to identify ambiguous statements and generate clarifying questions before the meeting ends.
Transcript:
Today I wanted to talk about meeting transcripts. If you’re using a tool like Teams or Zoom, or any other meeting software, it’s likely that you now have access to some sort of transcript system. It produces a word for word account of who said what during the meeting. And it’s incredibly useful. It allows you to draw out actions and to-do’s and figure out what was said. However, something that you could also do with these transcripts before the meeting has even ended is do an analysis of anything that is ambiguous, has been mentioned without clear accountability, anything with high risk, specific terminology, anything that needs follow up, but no confirmation of how that follow up would be determined. And so you can take your transcript and run it back into an AI with a specific prompt that goes looking for things that should be clarified and it presents those as a series of questions. So for example, in this transcript, Sarah mentions, I’ll email it today, but there’s no confirmation of who the recipients will be. And so a question that should be asked back to the team before the meeting finishes is who specifically should receive this one page of. So this is a really powerful tool to be able to tidy up or finish a meeting that you’re having by running the transcript back through a language model looking for questions.