The problem of structural labor shortages in the digital economy requires the implementation of breakthrough personnel innovations. Generative AI (GAI), which has automation and cognitive augmentation functions, is considered a strategic tool for managing the transformation of cognitive potential and compensating for labor shortages. The lack of quantitative assessment of the scale of labor shortage compensation through the dual effect (replacement and augmentation) of GAI in key sectors of the economy and the need to verify the strategic role of GAI as a personnel innovation are driving research on this issue. An assessment was conducted of the management of the transformation of the economy’s cognitive potential through the introduction of AI as a personnel innovation in conditions of a labour shortage. A comprehensive approach was applied, combining general scientific methods, statistical analysis, and economic mathematical modelling. The overall compensation of cognitive load through the implementation of generative AI in trade, manufacturing, and professional activities will amount to 5.752 million people in terms of headcount equivalent by 2027, which is more than four times the projected need to compensate for the structural deficit (1.4 million people). Generative AI acts not only as a means of covering the staffing deficit but also as a tool for the qualitative transformation of the economy’s cognitive potential, shifting the focus of employment to hybrid jobs and tasks that require a “human core” of competencies. For the first time, the concept of the “cognitive substitutability coefficient of GAI” (λGAI) has been proposed within the framework of the model of cognitive transformation of labor resources to quantitatively assess the total compensatory effect (automation + augmentation) of implementing GAI in the economy.
No takes yet. Share an insight, caveat, or question.
Kozhukalova et al. (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: