Find the AI opportunities that move a real number

The direct answer

An organisation should prioritise AI use cases by starting with costly or valuable business problems, not with available tools. Each opportunity is tested for its effect on revenue, cost, time or material risk, then assessed for readiness, delivery complexity and the evidence needed to prove value.

Use this audit when

• teams have produced more AI ideas than the organisation can fund
• the board is asking where AI could create measurable value
• vendors are proposing solutions before the problem is agreed
• leaders need a defensible first move

What the audit produces

• an AI Opportunity Map organised around business problems
• a ranked shortlist of value pools and candidate use cases
• known constraints, dependencies and risks
• an explicit park or stop decision for weak ideas
• the right next step, which may be readiness, an operational audit, strategy work or no investment

How opportunities are filtered

We define the business number, establish the current baseline where evidence exists, identify the people and workflows affected, and compare value potential with execution difficulty. Where evidence is weak, the output is a test rather than a confident business case.

What this is not

It is not a guaranteed ROI forecast, a technology procurement exercise or a substitute for detailed implementation discovery. Exact value estimates depend on access to operating data and accountable owners.

Related paths

• Check readiness
• Investigate costly workflows
• Build the investment roadmap