AI doesn’t fit the old playbook, so why are so many companies still using it?

In "Why Traditional Transformation Models Are Not Working for AI," Dr. Brian Massey outlines a critical mismatch between legacy change frameworks and the nature of artificial intelligence. Traditional models were designed for predictable, linear change, but AI is dynamic, non-linear, and continuously evolving.

Key Points from the Article:
- Traditional models are too rigid: Legacy transformation frameworks are static and sequential, making them poorly suited for the fluid, experimental nature of AI.
- AI demands adaptability: Real impact comes from iterative, data-driven strategies that can flex and evolve alongside AI capabilities.
- Governance and ethics are central: AI introduces new challenges around transparency, bias, and data privacy, requiring stronger oversight and often centralized functions.
- It’s a team sport: Success depends on cross-functional collaboration; aligning tech, operations, leadership, and governance under one shared vision.

Syntari’s Perspective:
At Syntari, we believe that bridging this gap requires more than just retooling strategy, it demands a modern product operating model. This model shifts organizations away from one-off transformations toward continuous capability-building. In this approach, AI is not a project, it’s a product: iterated, owned, scaled, and constantly improved. We build, and help others build, cross-functional teams around outcomes, enable rapid learning cycles, and ensure governance is embedded from day one. That’s how our clients turn AI into a lasting advantage, scaling smarter, adapting faster, and leaving outdated models behind. Rafi Menachem

For a more in-depth understanding, you can access the full article here: https://lnkd.in/eESJAYhY