AI Doesn’t Fit the Old Playbook — So Why Are Companies Still Using It?

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 That’s how our clients turn AI into a lasting advantage, scaling smarter, adapting faster, and leaving outdated models behind.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