A decade ago, I wrote about learning agility as a leadership capability that business schools should take more seriously. See “Can Learning Agility Be Taught in Business Schools.” Since then, the case has only grown stronger. The acceleration of technological change, especially the rise of AI, combined with increasing economic and geopolitical uncertainty have elevated learning agility from a desirable leadership trait to an essential capability for managers and entrepreneurs.
But learning agility as a learning objective is only part of the story. Here, I make the case for learning agility as a conceptual guide to curriculum development in an AI world.
In the earlier article, I highlighted differences in the way business professors and talent professionals think about learning agility. Business professors tend to equate learning agility with “learning to learn” or the “ability to learn,” while talent professionals emphasize its application to identifying high-potential talent and connecting people to developmental assignments. Both perspectives are useful, but neither fully captures why learning agility matters. We need a more thoughtful framing of the concept.
For that I turn to Michigan Ross School of Business, a pioneer in experiential learning. Former dean Scott DeRue and colleagues define learning agility as “the ability to come up to speed quickly in one’s understanding of a situation and move across ideas flexibly in service of learning both within and across experiences.” It’s not simply about learning. It’s about the speed and flexibility of learning.
While the ability to learn quickly and adapt knowledge across contexts has always been valuable, it becomes indispensable in the age of AI. Managers and entrepreneurs are expected to operate across more domains, absorb more information, and respond to change more quickly than ever before. Therefore, learning agility should take its place among other durable skills, such as communication, critical thinking, and teamwork.
In some ways, elements of learning agility already appear in many surveys of workplace needs. For example, both “resilience, flexibility, and agility” and “curiosity and lifelong learning” are in high demand by companies in surveys by the World Economic Forum. The concept of learning agility simply brings these parts of these skills together into a more coherent framework.
But if learning agility were just another item on a list of learning objectives, the conversation could stop there. What makes learning agility more interesting is that it can also serve as a guide to curriculum development. Similar to terms like ethics, globalization, and entrepreneurship, learning agility shapes not only what we hope students become, but also how we organize the educational experience itself, especially in the age of AI.
Curriculum structure, for example, might begin to look different when viewed through the lens of learning agility. For decades, business schools have organized programs around the assumption that students must first master disciplinary foundations (e.g., finance, accounting, marketing, operations, etc.) before applying them in integrative settings. The capstone course naturally appears near the end of the program.
When AI enables foundational knowledge to be accessed on demand, the educational challenge shifts from knowledge acquisition to knowledge application. Rather than requiring students to master every concept or tool before confronting a complex problem, schools can place students in real, integrative situations earlier and help them pull the necessary knowledge into the experience as needed.
The goal is not to diminish the importance of disciplinary expertise. Quite the opposite; foundational knowledge remains essential but is viewed even more as a means to an end, rather than an end in itself. The facilitator’s challenge is to help learners identify knowledge gaps, acquire relevant insights, and apply them effectively. The focus shifts from what students know to how quickly and effectively they learn.
Our perspective also sheds light on experiential learning. The reality is that two students can participate in the same project, international immersion, or entrepreneurial venture and come away with very different developmental outcomes. This causes me to see learning agility as a multiplier. The more quickly learners make sense of an experience and the more flexibly they apply those lessons to new situations, the greater the value they derive from any given experience.
In addition to accelerating learning, AI can strengthen the flexibility component of learning agility. One of the challenges of learning from experience is that individuals often become trapped in a single mental model. Generative AI can serve as a “cognitive sparring partner,” exposing users to competing interpretations, alternative scenarios, and unfamiliar disciplinary perspectives. In business schools we especially need to consider business problems from the perspective of human rights and biodiversity, in addition to profits and efficiency.
Learning agility also helps us to understand some of the risks of AI. If we are not careful, AI can reduce cognitive engagement, create an illusion of understanding, and exhibit a form of sycophancy. Either way, users may be less likely to recognize when existing mental models no longer fit a situation. Learning agility reminds us to be purposeful in structuring courses to force the kind of questioning and exploration (and “unlearning”) we need. It’s not only about acquiring answers (producing outputs) quickly, but also about the process—developing the capacity to learn from an experience and transfer that learning to new contexts. In a recent episode of The Global Exchange podcast, I spoke with Tawnya Means about what that looks like.
Indeed, recent discussions among management education leaders have left little doubt that the rise of AI is forcing business schools to rethink where they create value. I have been saying that it is forcing business schools to move up the value chain. See Competitor or Catalyst? The Role of AI in Shaping the Future of Management Education. As information becomes more abundant and accessible, the distinctive contribution of business schools shifts from delivering knowledge to developing agile learners.
That is why I believe learning agility deserves attention not only as a learning objective but also as a conceptual guide to the curriculum. It reminds us that the future of business education is not simply about helping students acquire knowledge. It is about helping them learn quickly, adapt continuously, and take responsibility for their own development over a lifetime.