An AI-ready enterprise architecture is not defined by whether an enterprise has adopted a large model. It is defined by whether data, documents, systems, permissions, and delivery governance can support reliable AI usage.
Enterprises should first evaluate data consistency, system boundaries, identity and access control, auditability, and operational responsibilities. These foundations determine whether AI capabilities can enter real workflows safely.
For complex digital projects, architecture planning should connect business goals with implementation stages, risk controls, security requirements, and long-term maintenance. This helps AI, data platforms, cloud platforms, and business systems evolve together.