At last week’s quarterly department-review meeting, Yang from the planning team never took a single note. He simply set his phone in the middle of the table to record the discussion. When the meeting wrapped up, he said he would finish the presentation slides in half an hour. Yet he was still revising them at quitting time. Frustrated, he kept complaining that the AI-generated output was disjointed with no coherent storyline. Hoping to save time, he ended up putting in more work than if he had built the slides from scratch.

What many people overlook is that AI-powered presentation tools built into voice-recording apps work by first transcribing audio into text, then pulling bullet points from the transcript to fit pre-built slide templates. One critical step gets skipped entirely: you need a logically structured presentation, not a haphazard patchwork of meeting notes.

Take Otter, for example. It accurately labels different speakers in multi-person meetings. Even so, transcripts capture free-flowing back-and-forth dialogue — tangents, off-topic asides, interrupted thoughts, and tentative ideas that get discarded mid-discussion. When AI scrapes this raw text, it may slip in throwaway jokes or treat unconfirmed preliminary thoughts as final decisions.

I have seen users generate slides directly from a full department-meeting transcript using DingTalk Flash Notes. Half the resulting slides contained administrative side comments like “Submit attendance records next week” and “Send in team-building requests by month-end”, which had nothing to do with the project under discussion. Tools such as meetingminutes come with domain-specific summary templates and filter for theme-relevant content, yielding more accurate outputs. Even so, they cannot produce presentation-ready slides you can deliver straight to an audience.

Output quality varies wildly depending on the meeting format. If you record a formal press conference with a fixed agenda and speakers reading pre-approved scripts, AI-generated slides are mostly usable, since the material is already logically organized. For brainstorming sessions or cross-department coordination meetings, however, even with 98-percent accurate transcription, AI-built slides will be messy. The conversation itself lacks a clear narrative, and AI cannot invent a complete reporting framework out of thin air.

This frustration is understandable. People turn to these tools hoping to skip replaying recordings for key takeaways, building slide structures, and filling in content. The catch is that populating slides is rarely the time-consuming part. The real heavy lifting lies in structuring arguments and organizing logic — a task no tool can fully automate today.

I have talked to professionals who regularly create meeting-recap presentations. Their workflow now uses AI only to distill transcripts into high-level bullet points. They still build the slide framework manually. So far, no tool reliably churns out polished, presentation-ready slides with a single click.