Measurement · Singapore Business Insights

How to Measure Generative AI ROI

A high login count is not a return on investment. Useful measurement connects the AI workflow to a baseline, an operational change and a financial or strategic outcome.

By Standley Ming7 min read

Set the baseline first

Before changing the workflow, measure the current time, volume, error or rework rate, service level and employee effort. Without a baseline, improvement becomes a story rather than evidence.

Use a balanced scorecard

Combine efficiency with quality, adoption and risk so a faster process is not mistaken for a better one.

  • Time per task and throughput
  • First-pass quality and rework
  • Response or cycle time
  • Employee adoption and exception rate
  • Customer or employee experience
  • Incidents, overrides and policy compliance

Translate operational value

Time saved is valuable only when the organisation can use it. Identify whether capacity supports more customers, faster turnaround, reduced outsourcing, lower overtime or higher-value employee work.

Review at practical intervals

Measure early workflow performance during the pilot, then review adoption and business impact after employees have had time to change how they work. A 30-, 60- and 90-day cadence is often more informative than a one-off launch report.

Choose the next practical step

Assess your readiness, estimate an indicative budget or discuss a priority workflow.

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