- Why most common perceptions of what drives economic value from AI are not what the data supports
- The seven factors that most reliably drive economic value from AI—and why several of them will surprise you
- The six-stage AI Economic Maturity Model—a research-based roadmap showing how organizations progress from pilots to high-value returns
AI's Economic Reality in 2026: What Actually Drives Value
AI is consuming billions in corporate budgets, and boards and senior executives are demanding proof of returns. But most guidance on how to get value from AI is either generic or anecdotal. What does the data actually say about what separates organizations getting real economic value from AI—and those that are not?
Based on their survey of more than 1,000 global executives, Professor Tom Davenport and Laks Srinivasan, CEO of the Return on AI Institute, found that 90% of organizations report getting significant value from AI—but the drivers of that value are not what most leaders assume.
On March 17, 2026, in a live, interactive HBR webinar, Davenport and Srinivasan will discuss:
While AI investment continues to grow rapidly, the gap between organizations that capture real economic value and those that don't is widening. The difference lies not in which AI tools you deploy, but in how deliberately you measure, manage, and report the value those tools create.
To discover what's actually driving AI value in 2026—and to get a practical roadmap for where your organization stands—join Davenport, Srinivasan, and HBR on March 17.
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