DIKIW FRAMEWORK APPLIED TO ENTERPRISE ARCHITECTURE
Enterprise architecture was built for information technology. Its domains cover business, data, applications and technology. Its tools describe how data is stored, moved and turned into information. That work remains essential.
Yet AI operates further up the DIKIW model, where knowledge and intelligence live, and our architecture has no place for them.
I call this next layer Intelligence Technology (I²T).
Applied to enterprise architecture, the DIKIW model gives us two pillars. On the left is IT architecture, built on a data base and a media repository, producing data and information. On the right is I²T architecture, built on a knowledge base and a model repository, producing knowledge and intelligence.
The bridge between them is where models learn from enterprise information and where intelligence acts back on enterprise systems. Wisdom spans both. Judgment, purpose and governance apply to how we handle data as much as to how we deploy intelligence.
Organizations are deploying intelligence into architectures that end at information. Much of the risk in AI adoption comes from that gap. Closing it starts with recognizing that I²T needs an architecture of its own.
