Separate resource use from outcomes
Efficiency improves the relationship between resources and output. Efficacy improves whether the intended outcome is achieved. An AI assistant may reduce preparation time while also helping people identify risks they previously missed. These benefits should be measured separately.
A faster process can still produce worse results. Pair speed measures with quality, rework, and downstream effects so the business case does not reward a local optimization that harms the whole workflow.
Establish the baseline before delivery
Measure representative tasks before introducing the product. Record variation by complexity and user experience, not just the average. Define the observation period and include the cost of human review, correction, and support.
When possible, compare similar groups or introduce the change progressively. If other process changes happen at the same time, state the attribution limits rather than claiming that AI caused the entire improvement.
Give value realization an owner
If a tool frees capacity, decide what the organization will do with it: absorb more demand, improve service, reduce overtime, or redeploy effort. Estimated minutes saved should not automatically be reported as financial savings.
Review realized benefits after adoption, including model costs, operational support, and changed risk exposure. The business owner should sign off the outcome, while the product team supplies evidence and explains uncertainty.
| Lens | Efficiency | Efficacy |
|---|---|---|
| Question | Can we use fewer resources? | Can we achieve a better result? |
| Example | Less handling time per case | More correct cases resolved |
| Measure | Cost, time, throughput | Quality, decisions, outcomes |
| Watch out for | Unrealized time savings | Attributing all change to AI |
Put the idea to work.
AI Use Case Qualification FrameworkA measurable baseline, a named beneficiary, and a credible benefit hypothesis.
Related concepts
References & further reading
These sources provide supporting context. The operating frameworks and recommendations are editorial interpretations, not claims of endorsement.