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“That’s one small step for man, one giant leap for mankind.”
— Neil Armstrong, Astronaut
With these iconic words in 1969, Neil Armstrong marked a moment of human achievement that transcended its immediate context. His words symbolized not only a monumental accomplishment but also the broader potential for human progress.
That same year, Peter Drucker foresaw a different leap for mankind: the rise of the knowledge worker. This prompted different thinking about resources. Unlike physical resources, knowledge is renewable and can be expanded in novel ways. Thus, managing and empowering knowledge workers presented new challenges for modern management, where innovation and continuous learning became essential in the knowledge economy.
However, while many organizations have embraced Drucker’s argument, they have often done so using outdated practices—treating knowledge like other resource classes of the past, something to be secured, accumulated, and scaled. This extractive mindset is epitomized by the term “productivity.” Such an approach misunderstands the unique nature of knowledge as a renewable resource.
The rapid rise of artificial intelligence (AI) demonstrates that generativity—not just productivity—is what truly matters in today’s world. Whereas productivity is about squeezing more output from a fixed set of inputs, generativity focuses on renewing and expanding the inputs themselves. How, then, can managers expand their thinking beyond productivity to fully embrace the potential of generativity?
The Renewability of Knowledge
To maintain its value, knowledge requires constant renewal. A “knowing economy” thrives on the continuous generation of relevant knowledge, which can then be used to create evolving streams of value. In today’s dynamic environment, this process is no longer about incremental knowledge or learning. Organizations must move beyond merely “knowing what works” to embrace “knowing what’s next.” This form of generative learning enables the ongoing renewal of knowledge and opens new pathways for growth.
In any organization, most current knowledge has a short lifespan before it becomes obsolete. Thus, generative renewal must be an ongoing process, guiding organizations toward the next valuable “knowing domain.” This is a journey fraught with ambiguity and uncertainty, involving playful exploration and an evolving sense of adjacent possibilities. Businesses need to move beyond legacy knowledge assets and explore new areas of understanding.
Generative learning is characterized by diversity, adversity, and intensity—a distinctly human-centric experience. True generative learning is a unique form of knowledge creation that emphasizes human imagination, creativity, and adaptability.
Embracing Generativity
As we move into the age of generative AI, the importance of generating new knowledge for value creation—through the symbiosis of human and machine intelligence—cannot be overstated. This symbiosis is evidenced in advancements such as the recent Nobel Prize in Chemistry, which was awarded for leveraging the potential of AI in innovative ways. Are we on the cusp of a new golden age of progress driven by generative learning?
In a new age of generativity, managers must embrace a greater range of thinking styles that support both efficiency and creativity, renewal, and continuous exploration. While this call to action is not new, it is now essential to manage new levels of value creation and innovation in the next knowledge economy.
Developing new meta skills
Generativity thrives when workers are valued for keeping eyes on the horizon rather than just feet on the ground. They are empowered to pursue “what’s next” rather than merely executing existing tasks. This requires a new set of foundational meta-skills to serve as an organization´s epicenter for imaginative, creative and innovative knowledge work. Future focus thus becomes a primary aspect of performance- a form of sensegiving that modulates functional expertise and general management skills.
First, everyone must develop skills for mindful[1] aspiration to make possible futures vivid, tangible objects of organizational discourse. Second, everyone must build self-regulation skills[2] that accommodate the inherent novelty associated with generative learning and the pursuit of entirely new streams of value.
Organizations need to learn to reason not only from current values but also towards new values, directing attention at satisfying current wants and generating new ones. Mindful thinking anchors focus on the present, whilst disclosing gateways to new values. Aspirational thinking is future-oriented, projecting new worlds of meaning and value. Self-regulation ensures continuity and balance between present and future, recognizing that – just like family and work – we cannot subsume one under the other.
In the words of Timothy Snyder[3], “when we think with values, we are drawing from the past, but we are not stuck in it. We are considering the present, but we are not sanctifying it. We are oriented toward the future, and we are making it.”
Likewise, teams will need to learn how to use these meta skills to help them explore new ideas and make the requisite shifts in their thinking to adapt to expanding performance parameters across space and time. This allows for both individual growth and the generative renewal of the organization’s knowledge base while fueling creative resilience.
Leveraging AI as a partner
The rise of generative AI offers unprecedented opportunities for augmenting human intelligence. Managers must embrace AI as a collaborative partner, enabling their teams to combine human creativity with machine efficiency to generate new solutions, novel insights, and rapidly test the potential for value creation at each turn. Remember, AI has no values, but we do. Values are key guardrails for exercising judgment.
Fostering diversity of thought
Generative learning flourishes in environments that are diverse in perspectives, ideas, and experiences. Ensure teams are composed of individuals with different backgrounds, skills, and worldviews, infused with the freedom to unleash the rich range of thinking styles necessary for generativity to take root and human well-being to flourish.
By focusing on renewability and generativity, managers can drive their organizations toward sustainable innovation and growth. The future belongs to those who are willing to move beyond legacy models of productivity and embrace the dynamic, evolving possibilities of the next knowledge economy.
About the authors:
Joseph Pistrui is co-founder of Generative Learning, Professor of Entrepreneurship & Innovation at IE University in Madrid, and a Senior Research Fellow at the Center for the Future of Organization, Drucker School of Management.
Dimo Dimov is co-founder of Generative Learning, Professor of Entrepreneurship & Innovation at University of Bath in the UK, and author of two books on entrepreneurship.
Portions of this work were assisted by ChatGPT, which was used for summarizing texts and proofreading. All analysis and interpretation were conducted independently by the authors.
[1] We are referring here to Ellen Langer’s definition of mindfulness “. . . the process of actively noticing new things. When you do that, it puts you in the present. It makes you more sensitive to context and perspective. It’s the essence of engagement.”
[2] We consider self-regulation as involving both the initiation and maintenance of behavioral change in addition to inhibiting undesired behaviors or responding to situational demands.
[3] Taken from On Freedom, Penguin Random House UK, 2024.