AI Audit for SMEs: Find the Workflows Worth Automating First

Start with the workflows that already hurt

List recurring tasks that consume management or team time, slow revenue, create missed follow-ups or require repeated copying between systems. Common SME candidates include CRM administration, lead qualification, sales follow-up, reporting, onboarding, support triage and document preparation.

The best first use case is usually frequent, rules-based enough to observe, supported by accessible data and easy to measure before and after implementation.

Score business impact before technical novelty

• Hours spent per week or month
• Revenue or pipeline affected by delays and missed actions
• Volume and frequency of the workflow
• Quality and accessibility of data
• Number of systems that must be connected
• Exception rate and need for human approval
• How easily success can be measured

What an SME AI audit should deliver

A useful audit should finish with a prioritized shortlist rather than a catalogue of AI tools. Each candidate workflow should have an owner, a current-state map, an automation hypothesis, required systems, control points and a measurable target.

The output should also distinguish quick wins from projects that need data cleanup, process standardization or a broader architecture first.

Move from audit to one bounded implementation

Once one workflow is clearly defined, the fastest way to validate the business case is usually to implement a bounded version and measure it. NLG can turn a selected workflow into an architecture, first working version where access allows, and an industrialization roadmap.

For a clearly bounded workflow, the NLG AI Automation Sprint is currently €1,250 excluding VAT with no ongoing commitment. Larger or multi-system projects require separate scoping.