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There’s never been more software pointed at the problem of working together. Teams, Slack, Loop, Notion, Miro, Jira, Asana, Monday — and now an AI assistant inside each of them, summarizing the threads we no longer have time to read and drafting the replies we no longer have time to write.
Collaboration, by every dashboard measure at least, is up.
Ask the people doing the work how connected they feel to colleagues outside their immediate team, though, and the answer tends to land somewhere between "less than before" and "I'm not sure who anyone is anymore." That's not a software problem. It's the predictable outcome of a decade of treating collaboration as a tool category.
The standard organizational response — to add another channel, another workspace, another AI-mediated digest — is actively making it worse.
Team Collaboration Is Not Social Collaboration
At the heart of this is a conflation between two different things that look similar from a distance. But they’re not.
At Lithos Partners, we use the analogy of your office to explain the difference:
Team collaboration is meeting-room shaped. Fixed membership, defined task, time-bound, outcome-led. It is exactly the kind of work AI mediates beautifully: summarize the meeting, surface the action, draft the follow-up. The meeting room is getting smaller, faster and more efficient by the month.
Social collaboration is shaped like your corridor, cafeteria or reception area. Open membership, evolving conversation, no agenda, no minutes — and crucially, no obvious metric. It's where the half-formed question gets asked, where the senior person who'd otherwise be unreachable says "I had this exact problem in 2019," where the new joiner figures out who actually gets things done.
The corridor is where belonging lives. It's also where the lived knowledge AI cannot generate continues to circulate — the stories, the workarounds, the "yeah we tried that, here's why it broke." None of that is in the LMS. None of it is in the wiki. Almost none of it has ever been written down.
And in most organizations, the corridor is the part of the digital workplace that has been most thoroughly neglected.
Adoption Is Not Appropriation
Technology research literature raises a useful distinction that organizations keep missing. Jennie Carroll's work on technology appropriation separates adoption — the initial decision to use a tool — from appropriation, the ongoing process by which users actively reshape that tool in practice. Carroll's central insight is that design isn't finished when the technology ships. Users complete it through use — and that completion is shaped by what they see their peers doing.
What does that process look like? Someone tries a tool. They get an unimpressive first result and nearly stop. Then they see a colleague post a prompt that solved a problem they didn't realize they had. They borrow it. They adapt it. They learn — usually from someone else's mistake rather than their own — when the tool is the wrong answer. Over weeks, they develop a personal sense of what the tool’s good for, what it isn't and how it fits the rhythm of their day. Eventually it stops being a thing they're using and becomes a thing they work with.
Appropriating AI
Every step in that sequence is mediated by other people. The first useful prompt is borrowed. The warning about hallucinations is overheard. The clever workflow is copied from someone two desks down — or two time zones away. Strip the social layer out and many users never get past the unimpressive first result.
Adoption is what license counts measure. Appropriation is where competence and value lives.
You cannot appropriate a tool alone — and certainly not at scale. You do it by watching what colleagues try, comparing notes, sharing prompts that worked and warnings that didn't. That conversation is the missing infrastructure underneath every AI rollout currently being declared a success on the basis of seat numbers.
It's also exactly what communities are for.
Where the Evidence Sits
Across the case studies we gathered while researching our book, "Digital Communications at Work," the pattern is the same: the organizations getting this right are not the ones with the most AI tools. They're the ones who built the social infrastructure around them.
Daiwa Institute of Research, a Tokyo-based research and systems firm within the Daiwa Securities Group, ran an ambassador-led Copilot program — selecting champions across business units to scaffold uptake through a Viva Engage community of practice. Licences grew from 300 to 750 within three months, with a 150-person internal waiting list and roughly 15 hours per user per month in operational time recovered. The community didn’t just promote the tool — it taught the organization how to use it.
Microsoft's own internal Copilot Champs community runs the same pattern at scale: around 7,000 members across functions on Viva Engage. Microsoft reports that members register 30% more active Copilot days than non-members on the same tenant. Same software, same access — the difference is the conversation.
A pharmaceutical organization took the inverse approach to the standard risk-led launch. Rather than leading with what employees couldn't do, it used an internal community to surface examples of effective enterprise LLM use, distilled into a fortnightly newsletter. Inspiration and governance reassurance delivered in a single artifact, by the people doing the work. The contrast with the more usual policy-PDF-and-mandatory-training combination is hard to overstate.
Nor is the pattern tied to one platform. Slack has published its own lighter-touch variant — a three-week microlearning program run inside a moderated channel, with small groups encouraged to share what they tried with a wider peer audience. Same shape, different ecosystem.
None of these are "AI initiatives." They're communities — strategic infrastructure with AI competence sitting on top.
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The Pitfall of Community Misuse
The most common failure mode, having seen one of these communities work, is to use it as a megaphone. Leadership notices the energy, decides the community should now carry the next change program, the next engagement campaign, the next CEO video — and the conversation dies within a quarter.
Communities are not broadcast channels. Overusing them as one kills the conversation you were trying to benefit from. If senior leaders need to push a message, push it through the channels designed for that. Leave the community alone.
What AI Strips Out, Communities Replace
The question most organizations are currently asking — how do we make our workflows more AI-efficient? — is incomplete. The better one is: what does AI strip out, and where does it need to be replaced?
Communities are the answer for much of it. They are where adoption becomes appropriation, where lived knowledge circulates, and where the people who didn’t know who anyone outside of their team was build those connections. The trust layer underneath the digital workplace follows from that connection — it can't be retrofitted onto an organization where people don't know who anyone is. Their value is not in metrics but in the moments that shape how work actually feels.
You can't measure your way into one. You can only build it — slowly, deliberately and with people who care.
Editor's Note: How else do communities support our workplaces?
- Why Organizations Need Communities of Practice More Than Ever — At a time when layoffs, hiring freezes and isolation are the norm, CoPs are a cost-effective way to retain knowledge and build connection within the workplace.
- Enterprise Social Isn't Over, It's Just Changing — Ultimately, enterprise social networks aren’t dying; they’re evolving. Their success hinges on culture, not technology.
- The End of the Social Collaboration Experiment: The Technology Is the Problem — Fifteen years has been an eternity in the enterprise, and yet, our collaboration tools haven’t changed that much from their MySpace-like origins
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