Remember when spreadsheets were single-player? You'd email a file back and forth, hoping nobody overwrote your changes. Then Google Sheets came along and suddenly teams could work in the same document at once. It felt obvious in hindsight.
AI is hitting that same inflection point right now.
For the past two years, using ChatGPT or Claude has been a solitary thing—you and a chatbot, having a private conversation nobody else can see. That's changing fast, and if you've been paying attention to recent product launches, you've probably noticed the trend.
This Has Happened Before
Software tends to follow a pattern. First, someone builds a powerful tool for individuals. Then someone else figures out how to make it collaborative. Then the collaborative version eats the market.
We saw it with documents (Word → Google Docs), design tools (Photoshop → Figma), and even code editors (Sublime → VS Code with Live Share). Every time, the multiplayer version seemed unnecessary until it wasn't.
The Signals Are Everywhere
OpenAI recently added team workspaces. Anthropic launched shared projects. Google's pushing Gemini into Workspace for teams. These aren't minor feature updates—they're the companies behind these tools acknowledging that AI works better when it's not just you talking to a bot in isolation.
Why This Actually Matters
Here's the thing about solo AI use: you're constantly reinventing the wheel. Your coworker probably asked Claude the same question last week. Your teammate figured out a better prompt for summarizing meeting notes. But you'd never know because everyone's conversations are siloed.
When AI becomes collaborative, a few things click into place:
Your team builds a shared knowledge base without trying. Someone asks a good question, everyone benefits from the answer. You stop duplicating effort across the org.
People get better at using AI just by watching their teammates. I learned more prompting techniques from seeing how a colleague used ChatGPT than from any tutorial.
Different perspectives combine in interesting ways. A marketer and an engineer asking questions in the same thread often surface insights neither would find alone.
If You're Building AI Products
For anyone building in this space, a few things are becoming clear:
Bolting on collaboration later is painful. The products that win will be the ones that assumed multiplayer from the start.
Permissions get complicated fast. Who can see what? Can interns access the same AI conversations as executives? These questions matter more than you'd think.
Async matters. Not everyone works at the same time. Good collaborative AI needs threading, notifications, and the ability to pick up where someone else left off.
What's Coming
The next couple years will probably bring:
- Deeper Slack and Teams integrations (AI that lives where your team already works)
- Shared AI memory that remembers what your team has discussed across months of conversations
- Better brainstorming tools where multiple people and AI can riff on ideas together
- Workflows that span departments—marketing, engineering, and sales all working with the same AI context
The Bottom Line
This shift isn't surprising if you've watched software evolve over the past two decades. The solo version comes first. The collaborative version comes second and usually wins.
The companies adapting now—building their AI workflows around teams rather than individuals—will have a real head start. The rest will be playing catch-up, trying to retrofit collaboration into tools that were never designed for it.
The most capable AI isn't the one with the best model. It's the one that helps teams actually work together.
