How to plan an AI integration with existing systems

A grounded guide to connecting AI tools to real business data and actions.

By KTD Developers · Updated 27 September 2026
THE SHORT ANSWER

Start with authorised data access and one clear task. Define what a model may read, suggest or change, then build validation and human approval around the integration.

01

Inventory the systems

List source systems, available APIs, record ownership and access permissions. Check whether information is accurate and current before connecting an assistant.

  • Authorised data sources
  • Read-only vs write access
  • Retention and audit requirements
  • Fallback when a connection fails
02

Design the trust boundary

Separate retrieved information from instructions. Treat incoming documents as untrusted content; validate structured outputs before passing them to operational tools.

Use human approval for irreversible actions. Log enough to investigate errors without retaining more personal data than necessary.

03

Test the end-to-end workflow

Test ambiguous requests, missing records, access-denied states and provider outages. A successful demo on one clean example is not evidence of production readiness.

Questions worth asking

Can AI connect to our CRM?

Often, if access is authorised and a suitable integration interface exists. Scope it around specific reads or actions rather than broad access.

Advice here is general; the appropriate implementation depends on the people, systems and constraints involved.

Talk through your project.

Tell us what needs to work better. We’ll help decide what is worth building.

Plan a CRM