"The problem is that many leaders are applying a mature-business scorecard to work that isn't mature yet-and the result is a predictable misread. AI initiatives don't mature on the same timeline as a product refresh or a cost-reduction program."
"When leaders demand conventional ROI on a one-to-three year horizon, teams respond rationally: they optimize for what's measurable. They chase near-term efficiency wins, avoid the messier work of process redesign, and build pilots designed to survive a financial review rather than to learn something."
"The result is what's now being called 'proof-of-concept fatigue'-organizations running dozens of AI experiments, few of which ever reach production. Strong measurement discipline is exactly what separates organizations that scale AI from those that accumulate pilots."
Leadership frequently evaluates AI initiatives using traditional business metrics, which are inappropriate for emerging technologies. This leads to misinterpretation of performance and premature project cancellations. AI projects require time to mature, with initial value often seen in decision-making speed and data quality rather than immediate financial returns. When leaders demand conventional ROI too soon, teams focus on short-term metrics, resulting in a cycle of proof-of-concept fatigue where many AI experiments fail to progress to production.
Read at Fast Company
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