AI ROI Metrics Assessment

Image Source

Quiz Questions

1.
How difficult is it for teams to find accurate, up-to-date information or data in your organization?
- A.
  Not difficult
- B.
  Somewhat difficult
- C.
  Very difficult
2.
Does your team have access to the AI tools they need to up-level their work?
- A.
  Yes
- B.
  No
3.
Do your teams have the right skills and training to use AI effectively?
- A.
  Yes
- B.
  No
4.
Is AI mostly being used by individuals or by teams working together?
- A.
  Mostly individuals
- B.
  Mostly teams
- C.
  Both equally
5.
About what percentage of your organization is actively using AI in their work?
- A.
  0-25%
- B.
  26%-50%
- C.
  51%-75%
- D.
  76%-100%
6.
Are teams in your organization saving time or reducing costs by using AI?
- A.
  Yes
- B.
  No
7.
Has AI improved the accuracy, consistency, or quality of your teams' work?
- A.
  Yes
- B.
  No
8.
Are your teams setting more ambitious goals because of AI?
- A.
  Yes
- B.
  No
9.
Has your organization changed its structure or processes to support AI innovation or experimentation?
- A.
  Yes
- B.
  No
10.
Has AI led to new features, products, offerings, or revenue streams in your organization?
- A.
  Yes
- B.
  No

Quiz Outcomes

1.
Recommended Metric: Adoption
Image Source
You’re in the “get people using AI” chapter of your story. This is all about building momentum, not perfection. Your next big move is to grow AI adoption and usage across teams, so people can experiment and find real, repeatable value. Next steps could include investing in:TrainingEnablementAI labsHackathons, working sessions dedicated to experimentation, and other exploration opportunitiesTo measure adoption success, focus on leading indicators like:Percentage of employees actively using AIWeekly or monthly active usersNumber of AI pilots, experiments, and hackathons runAI hackathon participationResource allocation to exploration (hours spent in AI trainings or workshops, teams with AI in their formal scope, budget dedicated to experimentation, etc.) These metrics will give you an early read on whether your investments in exploration are setting you up for future efficiency, quality, and innovation gains.To complete this exercise, copy the results above and send them to the Project Owner.
2.
Recommended Metric: Efficiency
Image Source
Good news: AI is already helping people work faster or cheaper. You’re seeing wins, but much of that value likely sits with individuals rather than being fully baked into team workflows. You’ll want to focus on efficiency next by codifying and scaling individual use cases into team workflows.Measure hard, operational metrics like:Cycle time per workflowTime saved per task with AIAutomation rateCost reduction attributable to AI (including reduced contractor or vendor spend)These efficiency metrics will make your early ROI visible and credible. They'll also highlight where to standardize and scale personal successes into team-level capabilities.To complete this exercise, copy the results above and send them to the Project Owner.
3.
Recommended Metric: Quality
Image Source
AI isn’t just speeding things up — it’s helping teams deliver more accurate, consistent, and reliable work. You’ve probably got decent readiness and efficiency in place, and now the story is about quality at scale.To prove that out, you'll want to focus on building AI into review processes and standards. Track metrics like:Accuracy, quality, and consistency, such as error/defect rates and amount of rework requiredAdherence to internal standards or policiesCustomer outcomes, such as CSAT or NPSPre-AI KPIs (e.g., win rate, incident rate, conversion rate) and how they’ve shifted post-AIThese metrics will show that AI is systematically upgrading the quality and consistency of core work, not just creating one-off wins. Sweet success!To complete this exercise, copy the results above and send them to the Project Owner.
4.
Recommended Metric: Innovation
Image Source
Congratulations! You've reached the highest levels of AI ROI. AI is helping your teams deliver innovation and new value. At this stage, the key question is less “Are we faster?” and more “How much new value are we creating?” You'll want to focus on supporting AI incubators, new offerings, and revenue experiments.Prioritize business metrics like:Number of AI-powered features, products, or offerings launchedPatents or IP createdNew revenue or margin attributable to AI initiativesYou can also track adoption and engagement with AI-driven offerings and entry into new markets or segments enabled by AI. These metrics will help quantify how AI is transforming your organization’s growth story, not just its productivity. Onward and upward!To complete this exercise, copy the results above and send them to the Project Owner.