By Jaime Teevan, Chief Scientist & Technical Fellow
In recent years we’ve all lived through the transition to cloud computing, a sudden shift to remote work, and now the rapid rise of AI. Each individually has felt like a seismic event, but in reality they are all just chapters in one ongoing story: the digital evolution of collaboration. The latest chapter, AI, has so far focused on boosting individual productivity. The result has been real gains—fewer emails, faster drafts—but also a creeping cost. When content is generated without deep engagement, the burden shifts downstream. The next frontier isn’t simply faster solo work, it’s using AI to unlock the full potential of human collaboration.
From prompts to purpose. AI can be used to help teams work better together. People have millennia of experience collaborating, but collaboration breaks down at boundaries—across time zones, languages, and scale. AI can bridge these gaps, but only if we shift from optimizing individual prompts to aligning on shared purpose. That means designing organizational systems and work practices that support joint goal-setting, distributed grounding, and collective evaluation. It’s not enough for one person to prompt well; the team must co-construct the context that guides the model.
From documents to dialogue. After decades of creating and sharing knowledge in the form of documents, knowledge work is now becoming conversational. Instead of authoring artifacts from scratch, teams now co-create through interaction—brainstorms, chats, meetings—and AI turns those into persistent memory. This shift demands new representations, not just documents, but dialogic artifacts that reflect the social process of their creation, along with new knowledge systems that can reason across them. We need to be able to track evolving intent, synthesize across modalities, and preserve epistemic provenance.
From solo to social. A key challenge to making the above possible is that today’s models have been designed as fundamentally single-user. Making them collaborative requires teaching them to have social intelligence: the ability to model turn-taking, resolve conflicting inputs, and adapt to group norms. This is a frontier in model training, evaluation, and interaction design. We’re investing in new data, signals, and architectures to support multi-party alignment and shared agency.
Collaboration is the constant. The heart of work has always been working together. Tools evolve—from email to cloud docs to AI agents—but our need to connect, align, and build together endures. The history of technology is a story of removing barriers to collaboration: distance, delay, language barriers, information overload. AI is the next chapter in that story. But until it reshapes how we brainstorm, solve problems, and share understanding as teams, we’re only scratching the surface of its potential. That’s the vision we’re pursuing: AI that helps us work better, together. This site shares our breakthroughs, our failures (because science is about learning what doesn’t work), and the questions we’re excited to explore next.
Welcome to Collab AI—we’re glad to have you in the conversation.
Artificial intelligence