Most AI tools are designed for one person. You ask a question. The AI answers. You work alone. But real problems are rarely solved by one person alone. They are solved by teams.
A new research paper tackles this mismatch head-on. It introduces a concept called networked intelligence — AI that connects people, not just processes information for a single user.
The Limits of Solo AI
Current AI-for-science and AI-for-business systems focus on scaling a single reasoning process. Better models. Larger context windows. Longer agentic execution. One AI, one user, one thread of thought.
This works fine for straightforward tasks. Need a summary of a document? Done. Need to draft an email? Easy. But complex problems — designing a product, diagnosing a system failure, planning a market entry — require different expertise. The engineer sees one thing. The product manager sees another. The sales lead sees something else entirely.
A solo AI cannot bridge those perspectives. It does not know what the engineer learned yesterday that might change the product manager’s decision today.
What Networked Intelligence Looks Like
The researchers built a system called Mycelium — an active shared workspace that connects human team members and AI agents. As people work, the system captures important observations and hypotheses. It tracks how these pieces of information relate to the team’s evolving understanding. And crucially, it routes them to the person or agent whose next decision they can inform.
Think of it as a smart project dashboard that does not just show status — it connects insights across team members. The engineer’s log analysis gets surfaced to the product manager because it affects a feature decision. The sales lead’s customer feedback gets routed to engineering because it reveals a bug pattern.
The system was tested in a real biological research campaign. A local analytical finding made by one team member was automatically connected to a different expert’s work, turned into a mechanistic constraint, and eventually became a concrete experimental design. The connection happened through the system, not through a lucky hallway conversation.
Why This Matters for Business
Most businesses buy AI tools for individual productivity. Give everyone a chatbot. Let each person work faster. That helps, but it misses the bigger opportunity.
The real value of AI in a team setting is not faster individual work. It is better information flow between team members. The insight that sits in one person’s head (or one person’s AI chat history) is useless if the person who needs it never sees it.
Networked intelligence addresses this directly. Instead of each team member having their own AI assistant that does not talk to anyone else, the AI becomes a connective tissue — routing relevant information where it needs to go.
What to Watch For
Mycelium is research, not a product. But the ideas are already appearing in commercial tools. Notion’s AI can surface relevant pages. Slack’s AI can summarize what you missed. These are early steps toward the networked model.
When evaluating team AI tools, ask: does this tool connect people, or just help individuals work faster? Does it know what the team knows, or only what one person has asked it? Does it route information to the people who need it, or just respond when asked?
The best AI investment you can make for your team is not the most powerful model. It is the tool that helps the right information reach the right person at the right time. That is what networked intelligence delivers — and it is a very different thing from a better chatbot.