Your business doesn’t need random acts of AI. Here’s why

Most organizations are failing to integrate artificial intelligence effectively because their foundational operating systems were designed for a 20th-century industrial era focused on predictability and consistency, rather than the speed and continuous learning required by AI. Melissa Reeve, author of "Hyperadaptive: Rewiring the Enterprise to Become AI-Native," argues that companies attempting to bolt AI onto outdated structures experience stalled pilots and plateaued adoption, leading to a "jagged edge" where some teams advance rapidly while others remain stagnant. This phenomenon, described by Ethan Mollick, highlights the inefficiency of hierarchical, siloed, and slow decision-making processes in an AI-driven landscape. Reeve posits that successful companies are not defined by their technology choices but by their organizational transformation into what she terms "hyperadaptive" entities. These organizations are architected to sense, learn, and make decisions with a speed and data-driven accuracy that surpasses human capabilities alone. The core issue is that a 21st-century technology like AI cannot be effectively run on a 20th-century operating model, necessitating a fundamental rewiring of enterprise structures to achieve AI-native operations and compete in a rapidly evolving market.