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What "AI-ready" means for a legacy app, and how to tell if yours is

Published 22 October 2026 · dotNew Labs

"AI-ready" gets used loosely. For a business application it has a plain meaning: an AI assistant or agent can use the app's data and actions safely, with the same permissions and records as a person would. Most legacy apps fail that test for ordinary reasons that can be fixed.

AI assistantor agentMCP servernamed actionsAPIas the signed-in userYour app + datarules written downonly what the task needsuser's own permissionsAudit logwho asked, what ran, what came back
An AI-ready app: AI tools reach it through a small set of actions, under the user's own identity, and every call is recorded.

Six questions that decide it

  1. Is there a clean way in? AI tools work through an API. Many older apps have none, only screens. Some expose old SOAP services that nobody documents.
  2. Are the business rules written down? An agent can't respect a rule that only exists in a stored procedure or a button-click handler.
  3. Does every request carry a real user? The agent should act as the signed-in person, with their permissions, not as a shared service account that can see everything.
  4. Is the data understandable? Column names like FLG2 and codes nobody remembers make answers wrong. A short data guide fixes most of this.
  5. Is every action recorded? In regulated work you need to show who asked what, what the AI did, and what it returned.
  6. Is the app on supported technology? Opening an unpatched app to new kinds of traffic adds risk instead of value.

Where MCP fits

The Model Context Protocol (MCP) is an open standard for connecting AI assistants to tools and data. An MCP server sits in front of your app and offers a small set of named actions, such as "look up an appointment" or "list overdue claims". It is a good way to make an app usable by AI tools, but it needs a real API and real permissions behind it. MCP on top of a shared admin login is not AI-ready.

A sensible first step

What AI-ready is not

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