As AI tools spread faster than organisations can absorb them, a December 2025 McKinsey article argues the bottleneck is leadership: organisations need more “domain owners” who can translate business priorities into tech delivery and adoption.
In Building the AI muscle of your business leaders (published online in December 2025), McKinsey authors Dana Maor, Eric Lamarre, and Kate Smaje make a simple point: scaling AI is less about access to tools and more about having enough leaders who can connect business problems to what technology can realistically deliver.
Their focus is on “domain owners”—senior leaders who run a business line or function and can carry an AI-enabled change end to end. For association executives, the parallel is familiar: digital initiatives stall when accountability sits “somewhere between” the secretariat, IT vendors, and committees. The article argues that leaders closest to member value must also be close enough to delivery to steer trade-offs, pace, and adoption.
A concrete example in the article follows Adam Boyd at Citizens Bank, who set out to redesign a home-equity lending journey so customers could move from application to funding in days rather than weeks. He didn’t delegate the work. He partnered across technology, risk, compliance, finance, and marketing; learned agile delivery; stayed involved in iterative testing; and then owned the organisational change—resolving workflow conflicts and upskilling frontline teams—until the new model was working at scale.
For boards and CEOs, the practical governance implications are clear. First, treat AI initiatives as operating-model change, not a software purchase, with one accountable executive per priority domain. Second, resource cross-functional teams and empower leaders to make trade-offs quickly, rather than pushing decisions up a crowded hierarchy. Third, expect leaders to build “tech fluency” as part of their role—enough to challenge plans, understand data constraints, and manage risk responsibly.
The question the authors pose is worth bringing into 2026 planning cycles: do you have enough leaders who can turn AI ambition into member-facing outcomes?
