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Module 725 minutes

Measuring ROI and Impact

Measure and demonstrate AI value. Track metrics, calculate ROI, communicate impact to stakeholders.

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Learning Objectives

  • Define AI success metrics
  • Calculate and track ROI
  • Measure business impact
  • Communicate value to stakeholders

Measure What Matters

If you can't measure it, you can't improve it—or justify it.

Metrics Framework

Input Metrics:

  • Investment (dollars, time)
  • Resources allocated
  • Training completed

Output Metrics:

  • AI systems deployed
  • Users trained
  • Processes automated

Outcome Metrics:

  • Cost savings
  • Revenue impact
  • Time saved
  • Quality improvements
  • Customer satisfaction

Focus on outcomes, not just outputs.

ROI Calculation

Costs:

  • Technology (licenses, infrastructure)
  • Labor (development, operations)
  • Training and change management
  • Ongoing maintenance

Benefits:

  • Cost savings (efficiency gains)
  • Revenue increase (new capabilities)
  • Risk reduction (better decisions)
  • Strategic value (competitiveness)

ROI = (Total Benefits - Total Costs) / Total Costs × 100%

Measuring Impact

Productivity:

  • Hours saved per week
  • Tasks automated
  • Faster decision-making

Quality:

  • Error rate reduction
  • Consistency improvements
  • Customer satisfaction

Innovation:

  • New products/features
  • Market opportunities
  • Competitive advantage

Stakeholder Reporting

Executive Dashboard:

  • High-level KPIs
  • Trend over time
  • vs. targets
  • Financial impact

Department Reports:

  • Specific use cases
  • Adoption metrics
  • Success stories
  • Challenges and needs

Attribution Challenges

AI often contributes to outcomes, not solely causes them.

Solutions:

  • A/B testing where possible
  • Before/after comparisons
  • Control groups
  • Conservative estimates
  • Qualitative + quantitative

Key Takeaways

  • Focus on business outcomes, not just AI outputs
  • Calculate ROI conservatively—better to over-deliver
  • Track leading indicators to predict success
  • Use both quantitative metrics and qualitative stories
  • Report regularly to maintain stakeholder buy-in

Practice Exercises

Apply what you've learned with these practical exercises:

  • 1.Define KPIs for AI initiatives
  • 2.Calculate ROI for one project
  • 3.Create executive dashboard
  • 4.Develop stakeholder communication plan

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