Start with automation — not AI

AI is often asked to fix work caused by broken data: the same information entered into two systems, a status no one trusts, and processes no one owns. The first step is then rarely a model. It is making the systems talk to each other.

Automation that pays off first

• An order, invoice, or application moves automatically between the site, accounting, and email.
• Staff stop copying names, dates, and status between systems.
• An error shows up in one place instead of collecting in Excel.
• The next step in the process happens without someone having to remember it.

When AI adds something

AI is useful when the data is already in the right place and the job is to classify, summarise, translate, or flag exceptions. It is a poor first investment when no one knows which number is correct. We therefore start with integration and automation, and add AI where it shortens work that is already defined.

The right order reduces the risk

First a clear process, then data in one place, then automation. AI comes in when those three are in place. Then the benefit can be measured — and turned off if it adds nothing.