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The Changing Landscape of Knowledge and Education
For many years, universities operated on a straightforward model: knowledge was scarce. Students paid tuition, attended lectures, completed assignments, and eventually earned a credential. This system served two main purposes: it provided access to valuable knowledge that was difficult to obtain elsewhere and signaled to employers that students had invested time and effort into mastering that knowledge.
This model worked because the supply of high-quality information was limited, which kept prices—both in terms of tuition and wage premiums—high. However, the situation has changed dramatically. The supply curve for knowledge has shifted to the right, making information more accessible than ever before. As a result, the intersection with demand now occurs at a lower price point, putting pressure on both tuition fees and the wage advantages traditionally associated with university degrees.
According to global consultancy McKinsey, generative AI could add between $2.6 trillion and $4.4 trillion in annual global productivity. This is because AI significantly reduces the marginal cost of producing and organizing information. Large language models can now explain, translate, summarize, and draft content almost instantly. When the supply of information increases so rapidly, economic principles suggest that the price will fall. Consequently, the “knowledge premium” that universities have long sold is beginning to deflate.
Employers Are Adapting Quickly
Employers are already responding to these changes. Markets react faster than curriculums, and since the launch of ChatGPT, entry-level job listings in the United Kingdom have fallen by about a third. In the United States, several states are removing degree requirements from public-sector roles. For example, in Maryland, the share of state-government job ads requiring a degree dropped from roughly 68% to 53% between 2022 and 2024.
In economic terms, this shift reflects how employers are repricing labor. AI is now a substitute for many routine tasks that graduates once performed. If a chatbot can complete the work at near-zero marginal cost, the wage premium paid to a junior analyst shrinks. However, not all knowledge is being affected equally. Economists like David Autor and Daron Acemoglu highlight that technology can both substitute for and complement certain types of knowledge.
Codifiable knowledge—such as tax codes or contract templates—is increasingly being replaced by AI. On the other hand, tacit knowledge—contextual skills like leading a team through conflict—acts as a complement, and its value may even rise. Data supports this trend. Labor market analytics company Lightcast notes that one-third of the skills employers want have changed between 2021 and 2024. The American Enterprise Institute warns that mid-level knowledge workers, whose jobs depend on repeatable expertise, are most at risk of wage pressure.
What Is Scarce Now?
Herbert Simon, a Nobel Prize-winning economist and cognitive scientist, famously said, “A wealth of information creates a poverty of attention.” When facts become cheap and plentiful, our limited capacity to filter, judge, and apply them becomes the real bottleneck. This means that the scarcity today is no longer information itself but the human capabilities that machines still struggle to replicate.
These include focused attention, sound judgment, strong ethics, creativity, and collaboration. I refer to these human complements as the C.R.E.A.T.E.R. framework:
- Critical thinking – asking smart questions and spotting weak arguments
- Resilience and adaptability – staying steady when everything changes
- Emotional intelligence – understanding people and leading with empathy
- Accountability and ethics – taking responsibility for difficult calls
- Teamwork and collaboration – working well with people who think differently
- Entrepreneurial creativity – seeing gaps and building new solutions
- Reflection and lifelong learning – staying curious and ready to grow
These capabilities are the genuine scarcity in today’s market. They act as complements to AI, not substitutes, which is why their wage returns hold or even climb.
What Universities Can Do Right Now
Universities must adapt to this new reality. Here are some steps they can take:
- Audit courses: If ChatGPT can already score highly on an exam, the marginal value of teaching that content is near zero. Assessments should focus more on judgment and synthesis.
- Reinvest in the learning experience: Allocate resources to coached projects, real-world simulations, and ethical decision labs where AI is a tool, not the performer.
- Credential what matters: Create micro-credentials for skills such as collaboration, initiative, and ethical reasoning. These signal AI complements, not substitutes, and employers notice.
- Work with industry collaboratively: Invite employers to co-design assessments, not dictate them. A good partnership works like a design studio rather than a boardroom order sheet. Academics bring teaching expertise and rigor, while employers provide real-world use cases, and students help test and refine ideas.
Universities can no longer rely on scarcity to set the price for curated and credentialed information. Their comparative advantage now lies in cultivating human skills that act as complements to AI. If they fail to adapt, the market—students and employers alike—will move on without them.
The opportunity is clear: shift the product from content delivery to judgment formation. Teach students how to think with, not against, intelligent machines. Because the old model, the one that priced knowledge as a scarce good, is already slipping below its economic break-even point.
