AI readiness is not the same as technical sophistication. A business can use modern software and still be unprepared for AI if its processes are unclear, its information is unreliable, or nobody owns the operational outcome. Readiness is the ability to turn a specific opportunity into a controlled, measurable system.

The workflow must be understood

You should be able to describe the trigger, inputs, decisions, exceptions, outputs, and responsible people. If the process changes depending on who performs it, discovery is still needed before implementation. AI can support judgement, but it cannot rescue a workflow that has never been made explicit.

The information must be usable

Useful information does not need to be perfect, but it must be accessible, sufficiently complete, and legally appropriate for the intended use. Establish where it lives, who controls it, how quality is checked, and what sensitive information must be excluded or protected.

The outcome must be commercially meaningful

Choose an opportunity with a visible operating metric: turnaround time, labour hours, conversion, accuracy, service capacity, or risk exposure. Assign an owner who can make process decisions and judge whether the system improves the business. Without ownership and a measurable target, even a technically successful implementation can become an unused experiment.