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As HR practitioners help their organizations implement AI across a growing number of use cases, clarity about the value each one is expected to create makes it easier to measure whether it delivered. This new report, based on interviews with 30 executives, speaks directly to this. While the report covers various aspects of AI, from the true pace of enterprise AI adoption to why survey-based ROI studies often contradict each other, one part to highlight is the section on the seven levers of how AI creates value, from reducing labor intensity to improving decision making. Interestingly, 91% of the AI use cases discussed centered on reducing labor intensity, suggesting opportunities to use AI to create value beyond any one lever. Also, although each of these seven levers is listed separately, they are not mutually exclusive (e.g., an application that reduces labor intensity may also reduce cycle time). To help put the framework into practice, I created a modified version, adding practical examples and space to list your own AI use cases and evaluate them against each lever. The resulting visual can help you spot whether your AI portfolio is spread broadly across the seven levers or leaning on just one, providing insight to evaluate and evolve your strategy. As a bonus, I’m resharing my slide, Framing Talent Initiatives Within the Business Context, which can be paired with the AI framework to articulate AI-based talent initiatives that can create stakeholder value.
