tech
What Leaders Get Wrong About the ROI of AI
Companies have invested hundreds of billions of dollars in AI. But if you ask most executives about AI right now, the conversation quickly turns to one question: Where is the return?
TL;DR
- Companies are investing heavily in AI but struggle to articulate a clear return on investment.
- Traditional metrics like productivity and cost savings are often insufficient to capture AI's value.
- AI's impact is better measured by insights, predictive power, skill-building, and scenario evaluation.
- Focus should be on defining desired business outcomes first, then determining how AI can help achieve them.
- Measuring AI usage (adoption rates) is an activity metric, not a measure of success.
- Success metrics should align with business goals, track changes in how work is done, and indicate progress towards outcomes.
- Leaders must explicitly define value, measure against it from the start, and make early indicators visible.
- Realizing AI's potential requires connecting adoption to real business impact and scaling what works.