Harvard Business Review LogoAugust 11, 2026David Malan/Getty ImagesOrganizations often blame employees when AI adoption stalls, assuming resistance stems from fear or lack of skills. Research across 23 interviews and three leadership workshops in 11 European ITWhen a company struggles to adapt to AI, the blame usually lands on employees: Leaders assume they resist, either because they lack the skills or because they fear for their jobs. Over three years, across 23 interviews and three deliberative workshops with leadership teams in 11 European IT services firms, we found the brake came from the leadership team itself.
“Leadership Drift” Is Stalling Your AI Strategy
Organizations often blame employees when AI adoption stalls, assuming resistance stems from fear or lack of skills. Research across 23 interviews and three leadership workshops in 11 European IT services firms points to a different obstacle: senior leaders. Executives often recognize privately that AI requires fundamental changes to pricing, staffing, and business models, yet abandon those positions during group discussions. The authors call this pattern “AI leadership drift,” where reassuring narratives replace difficult strategic decisions. To counter it, leaders should ground discussions in their own data rather than industry hype, study how comparable firms are responding to AI, tie every AI initiative to a strategic question with a review date, and assign someone responsibility for keeping uncomfortable issues on the leadership agenda.
TL;DRAI
Research in 23 IT leadership teams across 11 European firms: AI adoption stalls from leadership misalignment, not employee resistance. CTOs must prioritize C-level governance alignment as the key barrier to AI scaling; leadership coherence matters more than training.
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