With all the time employees spend in UC and collaboration platforms these days, it’s kind of surprising that meeting culture doesn’t always get much attention. Leaders occasionally think about how meetings are scheduled and managed, but it’s rare for anything to go beyond surface level.
That’s a pretty big problem when you think about the depth of AI in meetings these days. AI isn’t just helping us plan meetings or transcribe conversations anymore. It’s taking notes, influencing decisions, and occasionally standing in for someone who didn’t join the call. That’s a weird role for any system to play, and it shows.
Clearly, AI can improve meeting culture, minimizing communication gaps with translation, saving teams time, and helping to connect distributed staff. But it can also widen the gaps that already exist, amplifying certain voices while quieting others, stripping context out of summaries, and creating new artifacts, with new levels of risk.
If the future of human-AI UC and collaboration is going to be shaped safely, businesses need to rethink their approach to designing meeting culture.
The Evolution of Meetings in the AI Era
It’s surprisingly easy to miss how much meetings have shifted. And this isn’t about shiny add-ons like avatars or immersive rooms. The bigger change is simpler. The meeting you remember isn’t the one that carries weight anymore.
The one that counts is the version the system records. With AI in meetings, conversations now run through a pipeline. Capture. Summarize. Store. Retrieve. Act. That sequence turns a live exchange into a data object. Once that happens, meeting culture bends around the artefact, not the moment. People stop asking “What did we talk about?” and start asking “What did the recap say?”
There are consequences. Presence gives way to permanence. Participation becomes traceability. Alignment turns into auditability. The meeting stops being a fleeting social space and becomes something closer to a system log: searchable, quotable, and reused long after the call ends.
This lands in the middle of what Microsoft has called the “infinite workday.” Their Work Trend Index shows employees are interrupted roughly every two minutes during core work hours by meetings, messages, or notifications. That constant fragmentation raises the stakes. When attention is scarce, the summary becomes the shortcut. The artifact becomes the memory.
Once summaries are the default reference point, they shape behaviour upstream. People talk differently when they know their words will be compressed. They signal more clearly. Or more safely. All of this changes meeting culture. That’s part of why UC buyers are changing tactics, scrutinizing governance, analytics, and workflow integrations, not just call quality or features
When meetings become data systems, culture follows the data.
How AI in Meetings Reshapes Meeting Culture
Most people talk about AI in meetings as a productivity boost. Fewer notes to write. Faster follow-ups. Less admin clutter. All true. Also pretty boring. The real shift is in how these tools quietly rewrite the social rules of meetings.
Who feels pressure to attend? Who gets credit after the call? Whose ideas survive once the calendar invite disappears? When AI starts capturing, summarizing, and redistributing meeting outcomes by default, it rewires expectations.
Some of those shifts are genuinely positive. They open doors that were closed for years, and reduce invisible penalties tied to time zones, neurodiversity, language, or sheer calendar overload. They make meetings less about being present and more about being understood.
