Agility Under Fire: Barriers to Off-the-Shelf AI Adaptation

This study examines how off-the-shelf AI affects organizational agility in Germany’s Cooperative Financial Network. Drawing on 22 interviews across banks, service providers, and consultants and using a Gioia approach, we surface a dual lock-in: hyperscalers anchor a standardized core while a centralized integrator enforces uniform roadmaps and update cycles. Together with technological rigidity, layered bureaucracy, and data-governance frictions, this limits local sensing, rapid experimentation, and reconfiguration. Our contribution is conceptual: based on qualitative analysis, we integrate these empirically derived concepts into a framework that explains mechanisms and boundary conditions under which standardization constrains agility. We also outline design principles for a hybrid architecture, standardized backbone plus modular extensions, paired with dual governance and data contracts. The paper refines the agility-standardization debate and offers actionable guidance for financial networks seeking scale efficiency and organizational agility.