How Enterprise Architecture must evolve when AI agents become part of the enterprise workforce.
An element-level analysis of traditional EA frameworks, examining what changes, what breaks, and what survives when organisations deploy AI agents at scale. The analysis covers 1,062 framework elements across 36 topics in five domains:
- EA Development Method — How architecture development shifts from periodic cycles to continuous, agent-assisted processes
- EA Governance — How governance must operate at deployment speed or become irrelevant
- EA Repository — How architecture content must become machine-readable for both humans and agents
- Roles & Skills — How the EA function, architect roles, and required competencies transform
- Risk & Security — How new failure modes, observability gaps, and regulatory requirements reshape risk management
Work in progress. This is an AI-generated research synthesis. Content may change. Verify claims against original sources.
The website is a static site (vanilla HTML/CSS/JS, no build step) in the docs/ directory. All content is data-driven from JSON files in docs/data/.
To run locally:
cd docs
python3 -m http.server 8080