The idea of artificial superintelligence has long been a staple of science fiction, but recent research suggests it’s not as far off as we thought. According to a piece published in Technology Review, the path to distributed superintelligence lies not in building bigger models, but in connecting smaller, specialized AI agents across domains using a new kind of infrastructure: the Internet of Cognition.
This isn’t just about making AI smarter, it’s about making AI cooperative. Today’s AI agents can exchange data, yes, but they lack the ability to coordinate meaningfully without human intervention. That’s because they operate in silos, each with its own context, intent, and reasoning framework. To fix this, we need a semantic layer that allows agents to understand each other’s goals and share context in real time.
The Internet of Cognition is that layer. It’s designed to let AI agents communicate not just what they know, but why they know it and what they intend to do next. This is critical for complex, cross-functional tasks, like automating supply chain logistics, where an agent managing inventory must coordinate with one handling shipping, another handling customer service, and so on. Without shared context, these agents operate like isolated islands.
Underpinning the Internet of Cognition is another layer: the Internet of Agents. This layer handles discovery, identity verification, and cross-domain messaging. It’s the plumbing that lets agents find each other, verify who they are, and send messages that are understood across different systems. Without this, even the most advanced semantic layer would be useless.
This architecture is fundamentally horizontal. That is, it scales by adding more agents and connecting them, rather than by building ever-larger models. Vertical scaling, making one model bigger and more powerful, is insufficient for distributed superintelligence. Why? Because intelligence distributed across multiple agents, each with its own domain expertise, can solve problems that no single model could ever handle.
This is not theoretical. Companies are already experimenting with multi-agent systems. For example, Anthropic’s Cowork lets users automate file tasks without writing code, and tools like Claude Code and Goose are reshaping how developers approach coding. But these are still isolated tools. To unlock the full potential of AI automation, enterprises must architect systems that allow these tools to work together.
The Internet of Cognition is the missing piece. It’s not just about connecting AI agents, it’s about giving them shared meaning. Imagine a system where an AI agent in marketing can understand the intent of an agent in finance, or where a logistics agent can reason about customer service data to optimize delivery routes. That’s the kind of cross-functional problem-solving that will define the next generation of enterprise AI.
As first reported by Technology Review, this is the direction we’re headed. And it’s not just for research labs. Enterprises that want to automate complex workflows must start thinking about how to build these architectures now.
If you’re wondering how to get started, look to tools that already support agent discovery and messaging. For example, Anthropic’s Cowork is a good starting point for automating simple tasks. But to scale, you’ll need to think about how to connect those tools across departments.
The future of AI automation isn’t about building smarter tools, it’s about building smarter systems. And that means embracing horizontal scaling, semantic layers, and the kind of cross-domain coordination that only the Internet of Cognition can provide.