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Operating modelRelevance · high2026-07-08
McKinsey & Company·6 min read

New research: AI transformation value depends on operating‑model change, not tool adoption

TechnologyFinancial ServicesHealthcareManufacturingRetailProfessional Services

McKinsey’s July 2026 article on "From adoption to impact" argues that enterprise AI value emerges across three horizons: experimenting with tools, scaling use cases, and finally reinventing workflows and operating models. Their research finds that simply increasing AI usage rarely yields durable advantage; companies that redesign roles, workflows, and decision rights around AI see the most sustained performance gains.

Why it matters for leaders
As the senior AI/Data voice in a technology company, this gives you a mandate to frame AI not as a feature but as an operating‑model change. Your first MVP should be chosen where you can redesign how work gets done, not just bolt a model onto an existing workflow. This also sets expectations with the C‑suite that organizational change and process re‑engineering are part of the AI budget, not optional extras.
Opportunity signal

Position your AI roadmap explicitly around a few high‑impact workflows where you can redesign roles and decisions, using the first MVP as a showcase of full‑workflow change rather than a narrow efficiency tool.

high
Risk signal

If AI is framed as "just another tool" owned by IT, you will under‑deliver on value and risk an internal backlash against further AI investment when early pilots fail to move core metrics.

medium
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