Most collaboration tools were built around humans talking to other humans.
That sounds obvious, but it matters. Email, Slack, Zoom, docs, project boards, and CRMs all assume the same basic pattern: people create the context, people maintain the memory, people connect the dots, and software moves the pieces around.
AI changes that assumption.
Not because AI replaces the team. That is the lazy version of the story. The more interesting shift is that AI can begin participating inside the team's shared context. It can help remember, synthesize, compare, draft, challenge, and turn messy work into durable outputs.
That is why I think collaboration is entering a third wave.
Wave One: Same Room
The first wave of collaboration was physical.
People gathered in the same room. They shared a table, a whiteboard, a hallway, a lab, a classroom, or a conference room. The advantage was context. Everyone could see the same artifacts. You could read the room. You knew when a decision had really landed and when people were just nodding.
I still believe there is something powerful about this kind of collaboration. Some of my best company-building memories are not the clean milestones. They are the messy rooms: whiteboards full of arrows, people arguing in good faith, someone catching the missing assumption five minutes before the plan became real.
The weakness was obvious. Physical collaboration did not scale well across geography, time zones, or long-term memory. If you were not in the room, you missed more than the transcript. You missed the context.
Wave Two: Digital Tools
The second wave moved collaboration online.
Email made work asynchronous. Shared documents made editing multiplayer. Slack compressed team communication into channels. Zoom made remote work viable for teams that previously depended on physical presence.
This wave changed the world. It also scattered the work.
The strategy conversation lives in Slack. The actual decision lives in a doc. The task lives in a project board. The customer context lives in a CRM. The meeting recording lives somewhere else. The reasoning behind the decision lives mostly in people's heads.
Digital collaboration solved distance, but it created fragmentation.
That fragmentation is now the default condition of knowledge work. Teams are connected, but the context is split across too many surfaces. Everyone spends too much time reassembling the work before they can actually do the work.
Wave Three: Shared AI Context
The third wave is not simply "AI inside every app."
That is already happening, and it is useful. But if every tool gets its own isolated AI feature, we may just create a smarter version of the same fragmentation problem.
The deeper shift is shared AI context: people and AI agents working from the same room, history, artifacts, and trust boundaries.
In this wave, AI is not just a sidebar that answers prompts for one user. It becomes a participant in a shared workspace. It can see what the team is working on, what has already been decided, what remains unresolved, and what output needs to exist at the end.
That changes the collaboration pattern.
Instead of asking, "Can AI write this for me?" the better question becomes:
Can AI help the team think, decide, remember, and follow through together?
That is a much bigger product and design problem than adding a chatbot to a workflow.
What Makes This Wave Different
The third wave has a few defining characteristics.
First, context becomes shared. The AI does not live only inside one person's private tab. It participates where the work is happening.
Second, outputs become durable. Conversations are not treated as disposable chat transcripts. They can become briefs, decisions, plans, tasks, artifacts, and reusable context.
Third, trust becomes visible. If AI can suggest, remember, or prepare action, the team needs to see what it knows, where the context came from, and what still requires human approval.
Fourth, AI has a role. Not all agents should behave the same way. A research agent, a product agent, an operator agent, and a meeting agent should have different scopes, boundaries, and expectations.
That is why the third wave is not just about intelligence. It is about collaboration design.
The Practical Shift
Imagine a team trying to make a launch decision.
In the second wave, they might discuss it in Slack, draft a doc, hold a meeting, create tasks, and then lose half the reasoning a week later.
In the third wave, the shared workspace can help preserve the decision trail. An AI participant can summarize the tradeoffs, flag contradictions, connect the current decision to previous assumptions, and prepare the execution pack for review.
The human team still decides. The AI does not become the accountable owner. But the work becomes easier to resume, inspect, and move forward.
That is the point.
The most valuable AI collaboration will not be the flashiest demo. It will be the system that reduces the tax of re-explaining, reassembling, and rediscovering what the team already knows.
What Teams Need To Learn
This third wave requires new habits.
Teams will need to be clearer about what is exploratory versus decided. They will need to define when AI can draft, when it can recommend, and when it must ask for approval. They will need to treat context as a shared asset, not a private side effect of individual work.
They will also need to protect the human parts of collaboration.
Judgment still matters. Taste still matters. Trust still matters. The fact that AI can synthesize a thousand pages does not mean it understands what the team should care about. The fact that AI can prepare an action does not mean it should take the action.
The winning teams will not be the ones that hand everything to AI. They will be the ones that learn where AI belongs in the room.
The Collaboration Layer Ahead
The first wave gave us presence.
The second wave gave us reach.
The third wave should give us shared intelligence.
Not a replacement for human collaboration, and not just another productivity feature. A new layer where people and AI agents can work in the same context, preserve what matters, and help teams turn conversation into durable progress.
That is the collaboration problem worth solving now.