Business strategies for a successful gen AI solution · Topic 2 of 4
Measuring the Impact of Gen AI
How to measure the impact of gen AI: baselines, KPIs for productivity, cost, revenue, quality and experience, adoption, and pilots with control groups.
- 3 min
- Set a baseline before launch.
- KPIs must match business goals: productivity, cost, revenue, quality, customer and employee experience, adoption, risk.
- Measure fairly with control groups, A/B tests and human evaluation.
What it is
Leaders must show that gen AI creates value, decide which initiatives to scale, and stop those that do not work. That requires measuring impact: setting a baseline, choosing key performance indicators (KPIs) tied to business goals, tracking adoption, and comparing results fairly.
How it works
Start with a baseline
You cannot show improvement without knowing the starting point. Before launch, record current performance: how long a task takes, what it costs, error rates, customer satisfaction. Then measure the same things after.
Categories of KPIs
| Category | Example KPIs |
|---|---|
| Productivity and efficiency | Time saved per task, cases handled per agent, time to first draft |
| Cost | Cost per transaction, cost per resolved case, reduction in outsourcing |
| Revenue and growth | Conversion rate, revenue from new AI-enabled products, average order value |
| Quality | Accuracy, error and rework rates, groundedness of answers |
| Customer experience | Customer satisfaction (CSAT), net promoter score, resolution time |
| Employee experience | Employee satisfaction, time spent on high-value work |
| Adoption | Active users, usage frequency, share of eligible tasks using the tool |
| Risk and safety | Policy violations, incidents, blocked unsafe outputs |
Pick KPIs that match the original goal. If the goal was faster customer service, measure resolution time and satisfaction, not the number of prompts sent.
Measuring fairly
| Technique | What it does |
|---|---|
| Pilot with a control group | Compare a group using gen AI with a similar group that does not |
| A/B testing | Show different versions to different users and compare outcomes |
| Before and after comparison | Compare against the baseline, accounting for seasonal changes |
| User feedback | Surveys and ratings capture perceived quality and usefulness |
| Human evaluation of outputs | Experts score samples of outputs for quality and accuracy |
Leading and lagging indicators
Leading indicators move early: adoption, usage, user satisfaction. Lagging indicators take longer: cost savings, revenue, retention. Track both. Low adoption early is a warning that lagging benefits will not arrive, and usually points to training or workflow problems rather than to the model.
Return on investment
Compare the value (time saved multiplied by labor cost, extra revenue, reduced errors) with the total cost (licenses or usage, development, data preparation, training, change management, ongoing monitoring). Include ongoing costs, not only the build.
A worked scenario
A support center pilots Agent Assist with half its agents (the other half is the control group). The baseline average handle time is 9 minutes. After six weeks, the pilot group averages 7 minutes with stable customer satisfaction, and adoption is 85 percent of eligible conversations. Costs per contact fall, so leadership approves scaling, and adds a KPI for quality by reviewing a sample of conversations each week.
How the exam asks about this
- "How do we know the improvement came from gen AI?" Compare with a control group or baseline.
- "Which KPI fits a goal of faster service?" Resolution or handle time.
- "Adoption is low after launch." Investigate training, workflow fit and change management.
- "What is a leading indicator?" Adoption or usage, which moves before financial results.
What to remember for the exam
- Set a baseline before launch.
- KPIs must match business goals: productivity, cost, revenue, quality, customer and employee experience, adoption, risk.
- Measure fairly with control groups, A/B tests and human evaluation.
- Track leading indicators (adoption) and lagging indicators (financial results).
- ROI includes all ongoing costs.
Usage alone is not value. A tool can be used heavily without improving the business outcome it was meant to change.
Common mistakes
Measuring only technical metrics. Leaders need business outcomes.
No baseline. Without one, improvement cannot be proven.
Ignoring adoption. Benefits depend on people using the tool in their work.
Check yourself
Why set a baseline before launching a gen AI tool?
To compare performance after launch with the starting point and prove improvement.
What is a control group used for?
To compare a group using gen AI with a similar group that is not, isolating the effect of the tool.
Give an example of a leading indicator.
Adoption or usage rate of the gen AI tool.
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