City council packets. Steering committee briefings. Any meeting where the prep material is more than you can reasonably read. Here’s how AI changes what’s possible.
The standard advice for meeting prep is to review the agenda, read the supporting materials, identify the decisions that need to be made, and come in with your questions ready. Good advice — until the packet is 100 pages and you have a day job.
I serve on city council. Before every meeting, there’s a packet. It covers agenda items, staff reports, financials, project updates, consent items, public hearing materials. It is not a quick read.
AI changed what I can actually do with that packet.
What I Ask
When I get the packet, I ask AI to do two things:
- Identify anything concerning — budget variances, projects off track, items that don’t pass a basic smell test, anything that warrants a closer look
- Surface questions I should make sure get answered in the meeting
What comes back is a summary of the packet organized around what matters, not just what’s in it. Instead of reading every page to find the three things worth asking about, I have a starting point that tells me where to focus.
Why This Works for Long Documents
AI is good at reading dense material and pulling out the signal. A 100-page council packet has a lot of routine content — updates that haven’t changed, consent items that are genuinely uncontroversial, procedural sections that don’t require action. An AI can move through all of that and flag what’s actually different, unusual, or incomplete.
The two asks matter here for the same reason they matter in any meeting prep:
“Identify anything concerning” is a different question than “summarize this.” Summarizing gives you what’s there. Flagging concerns requires judgment — is this number higher than last period? Does this timeline make sense? Is something missing that should be here? That’s the read you don’t have time to do yourself on a 100-page document.
“Surface questions I should make sure get answered” turns passive reading into active preparation. Instead of absorbing information, you’re building an agenda for what you need from the meeting. That’s what separates showing up informed from showing up ready.
The Same Pattern Works at Work
The city council packet is the clearest example because the volume makes the value obvious — but the same approach applies to any meeting with substantial prep material.
When I start a work day with a lot on the calendar, I’ll ask Copilot to prepare me for my meetings and flag any prep work I need to complete before them. For a specific high-stakes meeting — a steering committee, a vendor review, anything where I need to be sharper than usual — I ask about that meeting specifically.
The prompt does the same two jobs: get me current on what I need to know, and tell me what I need to do before I walk in.
What It Doesn’t Replace
AI can flag that a budget line is 40% over projection. It can’t tell you whether that’s a problem or expected given the project phase — that requires context and judgment that comes from knowing the work.
AI can surface a question worth asking. It can’t read the room when you ask it, or know whether this is the right meeting to push on something or the wrong one.
The prep AI does is research prep. The meeting itself is still yours.
The Underlying Principle
The most useful thing AI does for meeting prep isn’t summarizing — it’s helping you ask better questions. When you walk into a meeting knowing what concerns to raise and what answers you need, you’re more effective regardless of your role.
That applies whether you’re a PM reviewing a project status report, a council member working through a city budget, or anyone else whose job requires showing up informed on material you didn’t have time to read cover to cover.
Part of the AI + PMO series. Coming later: AI for Meeting Prep: What It Gets Right and Wrong — a deeper look at the city council use case, including where AI missed things I had to catch myself.
Related posts:
- 5 PM Tasks AI Does Surprisingly Well — more patterns like this one
- AI + PMO: Manual Work to Eliminate — scaling these habits across a team