AI-native is not a feature. It is an architectural decision.

There is a difference between an organisation that uses AI and an organisation that is built around it, and it is not a difference of tooling.

Adding AI to an unchanged workflow

The common pattern is to keep the existing production line and insert a model into one of its steps. Drafting gets faster. Review does not. Approval does not. The bottleneck simply moves one step to the right, and the organisation concludes that AI did not deliver what was promised.

Redesigning the line

An AI-native architecture asks a different question: given that generation is now cheap, where does the scarce human judgement belong? Usually not in producing the first draft. It belongs in specification, in review and in authorisation — the three places where being wrong is expensive.

• Specification becomes more detailed, because ambiguity is now the main source of error.
• Review becomes a first-class stage with its own owners, not a courtesy read.
• Authorisation becomes explicit and recorded, because an unattributed output cannot be defended.

Why this matters in a regulated institution

In an unregulated setting, a plausible answer with no provenance is an inconvenience. In a ministry, a bank or an operator, it is a finding. The architectural decision is therefore not about which model to use; it is about where accountability sits once the model is in the loop.