How to Prioritise AI Use Cases in Your SME

Create a shortlist of concrete tasks

Ask teams where work repeatedly waits, gets rewritten or requires searching across documents. Describe each idea as a task with a trigger, input, output and recipient.

Replace broad ideas such as AI for sales with a testable workflow, such as drafting a follow-up from an approved meeting brief.

Assess value with evidence

Estimate task frequency and current effort from a representative sample. Identify the quality issue or delay you want to reduce. Avoid counting every minute of generated output as saved labour.

For an illustrative proposal draft, include time spent gathering requirements, checking claims and correcting the document. Compare the complete workflow.

Check feasibility and ownership

Ask whether the information is accessible and reliable, whether a business owner can approve the output and whether the team can support the tool.

Use the data readiness guide to investigate source problems. Give unclear ownership or missing access a visible status instead of hiding it inside an overall score.

Keep risk visible

List the consequences of an incorrect result and the controls needed before testing. A high-value idea may still be unsuitable for a first pilot if errors are difficult to detect or reverse.

Use the governance guide to define boundaries. IMDA’s enterprise AI resources provide additional context for adoption.

Choose and document the next experiment

Select one idea with a clear owner, available inputs and a checkable result. Record assumptions, costs, success criteria and stop conditions.

Move into the SME AI adoption guide for pilot planning. Revisit the shortlist after learning from the first experiment rather than committing to a long tool rollout immediately.

Sources and further reading

• IMDA: Artificial Intelligence