What Businesses Should Know Before Implementing AI

Can you describe the process without using the word AI?

If a process cannot be described as a sequence of steps, decisions and exceptions, it is not ready to be automated. This is not a technology constraint — it is the same clarity you would need to train a new member of staff.

A useful exercise: have the person who actually does the work narrate it while doing it. The exceptions they mention in passing are usually the hardest and most important part of the specification.

Where does the information live?

Automation depends on information being retrievable. If the answer to a customer's question exists only in a long-serving employee's memory, the first piece of work is writing it down, not building software.

This is frequently the single largest hidden cost in an AI project, and it is worth discovering before budget is committed rather than after.

• Is the information written down, or only known?
• Is there one version of it, or several that disagree?
• Who owns keeping it current once the system depends on it?
• Can the systems holding it be accessed programmatically?

Who owns it after launch?

An AI feature is not a fixed asset. Its behaviour needs reviewing as your business changes, and someone needs to own that. Projects that stall after launch usually had no named owner.

Agree this before the build, along with how success will be measured and who decides whether to extend or stop.

What are the consequences of being wrong?

Sort candidate processes by what happens when the system makes a mistake. An incorrect opening-hours answer is an inconvenience. An incorrect allergen, dosage or eligibility answer is a serious matter.

Start with the low-consequence, high-frequency work. It builds organisational confidence and delivers value while the harder governance questions are worked through properly.