AI Operating Models: Why Transformation Trumps Simple Adoption

A new whitepaper from KPMG in India and Nasscom identifies organizational transformation as the defining challenge of the current AI decade. While most enterprises initially focused on simple tool adoption, the report argues that true value now depends on restructuring entire operating models to leverage AI capabilities. This shift is critical as the market moves beyond basic automation and toward deeper, agentic workflows that require structural changes in how companies manage talent and data.

Experts and academic pioneers, such as Turing Award winner Richard Sutton, are increasingly signaling that current AI methodologies may reach a plateau, necessitating new ventures and research directions. Sutton’s work at his new lab, Oak Labs, reflects a growing skepticism toward the current trajectory of AI models. This skepticism suggests that the industry is entering a more mature phase where engineering-led breakthroughs must be supported by systemic business changes to sustain long-term growth and productivity.

Enterprises that fail to adapt their internal processes are at high risk of becoming obsolete in the face of more agile, AI-integrated competitors. The focus is shifting toward 'agentic orchestration,' where reliability and multi-step execution take precedence over the raw power of individual models. As these organizational models evolve, Indian firms are expected to prioritize security, permission enforcement, and fiscal control over their AI usage to avoid unmanageable costs and potential security breaches.