How to Prioritise AI Use Cases

AI use cases should be prioritised based on business value and strategic relevance alongside feasibility, readiness, risk, complexity and expected time to value.

The most technically impressive idea is not necessarily the best place to start.

Prioritisation should begin by asking what could materially improve if the opportunity succeeds.

• Revenue or lead conversion
• Customer response and experience
• Employee capacity
• Operational efficiency
• Knowledge access
• Error reduction
• Digital experience

A use case can have attractive local benefits while having little connection to the business's broader priorities.

Stronger opportunities tend to support an objective the organisation already considers important.

Potential value needs to be balanced against what is realistically achievable.

Data quality, system integration, process complexity, technical requirements and availability of suitable information can all affect feasibility.

A business may have a valuable opportunity but not yet be ready to implement it.

Readiness can involve process maturity, data availability, system access, ownership, employee adoption and the ability to establish appropriate controls.

Higher-value opportunities can sometimes involve greater risk or implementation complexity.

That does not necessarily mean they should be rejected. It means they should be understood properly and compared with alternatives.

An opportunity that can demonstrate useful value relatively quickly may be a stronger starting point than a much larger initiative that requires significant investment before results can be evaluated.

This is particularly useful when a business is beginning its AI journey and needs to build confidence through practical results.

Prioritisation does not mean selecting only one idea forever.

A sensible portfolio may contain an opportunity to start now, several opportunities worth exploring next, and others that should wait until prerequisites are in place.

DEEPS treats prioritisation as part of a broader decision process. Potential opportunities are first understood in their business context and then considered against value, feasibility, complexity, risk and the information available.

The purpose is not to create a mathematically perfect ranking. It is to create a useful basis for deciding where deeper investigation should happen next.