Enterprise AI desperately needs a lifecycle for context

Enterprise AI is increasingly limited not by model capability or data access, but by the lack of a governed way to manage business context—definitions, policies, exceptions, and ownership—across applications. For CIOs and technology leaders, the strategic risk is clear: when context changes in finance, legal, product, or support, AI systems can quickly become inconsistent, outdated, and operationally costly unless IT establishes a repeatable lifecycle for versioning, review, testing, and publishing context. This shifts IT from simply enabling AI to running a cross-functional control plane for enterprise knowledge, with business owners accountable for meaning and technology teams responsible for distribution and enforcement.