Practice Makes Perfect: Tacit Knowledge, Generative AI, and Returns to Schooling and Experience

Research indicates that generative AI alters human capital dynamics by substituting machine-supplied codified knowledge for formal schooling while increasing the relative value of practice-based tacit knowledge and judgment. Consequently, returns to traditional schooling may decline as codified knowledge cheapens, whereas returns to experiential learning and practice rise, potentially rotating the workforce experience wage profile.

This shift alters the foundational economic assumptions underpinning organizational talent acquisition, compensation, and human capital valuation. By eroding the premium on codified education while amplifying the value of experiential judgment, institutions must re-evaluate how workforce capabilities are developed and rewarded. Understanding these shifting returns is essential for mitigating structural skill imbalances as AI integration matures.

Generative AI reduces the scarcity and cost of codified knowledge directly at the point of production.

Forward consideration, not a verified fact.