What it means
System integration is the work of connecting an AI tool with the existing systems, data and processes an organisation already uses, so that information flows between them reliably and securely. It is often the largest and least visible part of an AI project.
Real-world example
A job centre pilots an AI tool that drafts summaries of client meetings. To be useful, it must pull client data from the case management system, respect existing access rights, and save approved summaries back into the case file in the correct format. The integration work takes longer than configuring the AI itself.
Why it matters for AI adoption
A stand-alone AI tool that requires copying and pasting between systems rarely delivers lasting value, and it can create data protection risks. Realistic project plans budget significant time and expertise for integration, testing and operation, not just for the AI component.
Questions to ask
- Which existing systems must the AI tool read from or write to, and who owns them?
- Who will maintain the integration when either system changes?