Experience Stern | Faculty & Research

Overview: Generative AI (GenAI) has spread through organizations at remarkable speed, with firms investing billions in hopes of boosting productivity and innovation. Yet many companies – especially in healthcare – report that GenAI has fallen short of delivering organization-wide benefits. In their new research, “Generative Organizational Learning: Affordances for New Modes of Knowledge Search, Creation, Transfer, and Forgetting with LLMs,” NYU Stern Professor Batia Wiesenfeld and co-author Katherine Kellogg (MIT Sloan) show why. Studying a healthcare system at the forefront of GenAI adoption, the authors find that GenAI can dramatically expand organizational learning and innovation – but only when paired with the right organizational structures, processes, and skills. Without these complements, the promise of GenAI remains elusive.

Why Study This Now: GenAI is rapidly evolving, and its use across industries is accelerating faster than organizations’ understanding of how to deploy it effectively. Healthcare systems face urgent challenges – high costs, severe burnout, and limited resources – that demand scalable innovation. At the same time, leaders are grappling with how to harness GenAI safely and productively.

What the Researchers Found: The study examines how GenAI changes organizational learning – how employees search for ideas, create solutions, share knowledge, and discard what doesn’t work. Key findings include:

• GenAI broadens participation in innovation. Employees far beyond traditional expert roles can now contribute ideas and solutions.
• Scalable innovations become abundant. Instead of a few hard-won breakthroughs, organizations can generate large volumes of potential solutions.
• New organizational systems are essential. Leaders can create structures such as “promptathons” and on-demand GenAI “office hours” to channel this surge of innovation.
• Risky “knowledge” increases. GenAI produces ideas that may be inaccurate or unsafe, requiring new guardrails such as “judge” LLMs to evaluate and filter outputs.

What Does This Change: The research challenges the long-standing assumption that organizations operate under conditions of knowledge scarcity. With GenAI, the core challenge shifts from finding ideas to curating them – deciding what to adopt, adapt, or discard. For managers, this means innovation success depends less on individual brilliance and more on organizational design.

Key Insight: “GenAI does not automatically deliver value,” explains Wiesenfeld. “It’s real payoff comes when organizations redesign how people learn, innovate, and evaluate ideas – turning knowledge abundance into a strategic advantage rather than a liability.”