Enterprise AI is in 1991. Where’s its web?

Enterprise AI today feels strangely familiar: the infrastructure is powerful. The capabilities are real. The demonstrations are impressive. Models can write, summarize, reason, code, search, retrieve, translate, classify, plan, and increasingly act. The raw machinery is there. And yet, inside companies, the same pattern keeps repeating: pilots everywhere, transformation nowhere near the promise. The first article in this series argued that large language models were never built to run a company because companies operate through memory, context, feedback, constraints, state, incentives, and dependencies — not through isolated sequences of text. The second argued that enterprise AI must move from answers to outcomes, from prompts to constraints, and from copilots to systems of action. The third argued that when enterprise AI finally works, it will not look like a better chatbot. It will look like intelligence embedded into the organization itself. The next question is obvious: if all of that is true, where are we in the historical cycle? My answer is simple: enterprise AI is in 1991. It has TCP/IP. But it does not yet have the web. The internet worked before the web The analogy matters because it prevents us from confusing infrastructure with industrialization. In 1991, the internet already worked. TCP/IP moved packets. Email connected people across institutions. FTP moved files. Telnet enabled remote access. Universities, research labs, and technically sophisticated organizations could use the network. But for a normal company, the internet was still not a business environment in the modern sense. It was powerful, but not yet consumable. Then the World Wide Web added a thin but decisive layer: URLs, HTTP, HTML, servers, and browsers. CERN’s history of the web explains that by Christmas 1990 Tim Berners-Lee had already defined the basic concepts of HTML, HTTP, and URLs, and written the first browser/editor and server software. In 1991, CERN released the WWW software m