Why Traditional Transformation Models Are Not Working For AI

This article argues that traditional digital transformation methodologies are fundamentally ill-suited for AI transformation. Drawing on examples from Agile, Lean, DevOps, Change Management, Design Thinking, Digital Adoption Platforms, Data-Driven Transformation, scalable platform models, and ecosystem-driven approaches, the author explains why each framework fails to address the unique characteristics of AI—namely its experimental nature, rapid evolution, distributed impact across organizations, and heightened governance and ethical risks. The article contextualizes these challenges with current industry developments, including BCG’s rapid growth in AI advisory services, Coca-Cola’s large-scale AI partnership with Microsoft, and the limitations of voluntary AI regulation efforts in the UK. It concludes that AI transformation represents a fundamentally new class of organizational change that cannot be solved by repackaging existing methodologies, and that a new, purpose-built transformation approach is required—one that balances speed, governance, experimentation, and strategic oversight.