Harvard Business Review LogoApril 30, 2026Illustration by Mandy TsouMany companies are investing heavily in AI but failing to translate isolated productivity gains into meaningful business results. The problem is a “micro-productivity trap,” where firms optimize tasks withoutGenerative AI has sprinted from novelty to boardroom priority in record time. But despite the widespread adoption of this technology, not every company is realizing bottom-line improvement commensurate with its capabilities.
How to Move from AI Experimentation to AI Transformation
Many companies are investing heavily in AI but failing to translate isolated productivity gains into meaningful business results. The problem is a “micro-productivity trap,” where firms optimize tasks without rethinking workflows or value creation, preventing organization-wide impact. This article outlines four steps to escape this trap—strategically narrowing use cases, reimagining cross-functional workflows, engaging frontline employees, and measuring outcomes tied to business value—illustrated through examples from companies like Lowe’s and a Fortune 1000 manufacturing firm.
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