Enrich, Don’t Extract: Why Selling AI as a Productivity Tool Backfires, and How Leaders Can Introduce AI as a Path to More Meaningful Work

Abstract: Organizations are investing heavily in generative AI, yet many deployments stall at shallow, defensive use. This article examines new field research from Stanford, Virginia, and Dartmouth showing that how managers frame AI shapes whether employees embrace it: in a law firm, a division that was introduced to an AI tool as a way to enrich its work used the tool 58% more and experimented with it 70% more than an otherwise similar division told the tool would speed up drafting. Drawing on Gallup, Microsoft, Workday, and BCG data and on peer-reviewed research on meaningful work, self-determination, and job design, the article traces how productivity-first framing fuels hidden use, lost meaning, and stalled value, while enrichment framing backed by real resources enables discovery. It sets out five evidence-based responses: co-diagnosing work, resourcing learning and exploration time, reinvesting freed capacity, measuring value rather than volume, and governing with worker voice. Documented examples from finance, retail, healthcare, biopharma, technology, and media illustrate each response, and three pillars for long-term capability close the article.