The key to AI value is hiding in plain sight: Your operating model
Discover how AI reinventors redesign operating models to capture enterprise value through faster workflows, stronger capabilities, and smarter resource allocation.
The latest McKinsey research indicates that firms pursuing artificial‑intelligence transformation do not win by copying a single “best” operating model. Instead, they achieve success when they deliberately shape their internal structures and follow through with disciplined execution.
Design Choices over One‑size‑fit‑all
The study was authored by Brooke Weddle, Deepak Mahadevan, Richard Steele and Tom Welchman, with contributions from Laura Pineault and Marie Bäckström Twallin, all representing McKinsey’s People & Organization Practice. Their analysis stresses that AI—especially the emerging class known as agentic AI—requires a fundamentally new way of organizing work. The technology alters decision‑making pathways, reshapes cross‑functional collaboration, redefines how capabilities are built, and shifts the locations where value is generated.
Critical Questions for Leaders
As companies shift from pilot projects to a full reinvention of daily operations, the authors highlight two pivotal questions. First, which specific operating‑model decisions set apart firms that actually capture AI‑driven value? Second, where should senior executives concentrate their attention to amplify the impact of those decisions? The report argues that answering these questions hinges on intentional design rather than defaulting to generic templates.
Survey Scope and Participant Profile
McKinsey’s effort built on a prior global survey of AI maturity and readiness, then expanded the inquiry by reaching more than 700 executives and senior leaders. The respondents spanned a wide spectrum of titles—including CEOs, presidents, C‑suite officers, general managers, managing directors, vice presidents, directors and heads of business functions. These individuals represented organizations from a variety of industries and geographic regions, providing a broad view of how operating models influence AI transformation outcomes.
“reinventors” Show Stronger Performance
The findings reveal that firms the researchers label “reinventors”—those that are fundamentally reimagining how work gets done—are more likely to report robust operating‑model performance. This group outperforms organizations that remain in earlier phases of AI adoption, suggesting that a deep redesign of processes and structures correlates with higher perceived success.
Implications for the Business Community
The study’s conclusions imply that companies cannot rely on a single, pre‑packaged operating model to unlock AI value. Executives must make purposeful choices about governance, talent development, and cross‑functional workflows, then ensure those choices are consistently applied. By doing so, they position their firms to move beyond experimentation toward sustained, value‑creating AI integration.
In sum, the research underscores that the hidden key to extracting AI’s benefits lies in the deliberate construction and disciplined execution of an organization’s operating model, rather than in chasing a universal best practice.
Source: mckinsey.com · 2026-09-09