Augmenting, Not Eliminating, Work: Artificial Intelligence, Labor Markets, and Corporate Governance in the Age of Automation
Paper Session
Sunday, Jan. 3, 2027 8:00 AM - 10:00 AM (EST)
- Chair: Deidre McCloskey, CATO Institute
Why AI Has Not (Yet) Destroyed Jobs: Evidence from Firm Level Adoption
Abstract
Despite widespread concerns that artificial intelligence (AI) would lead to large-scale job displacement, recent firm-level evidence suggests that employment losses have been limited thus far. Empirical studies using matched firm data indicate that AI adoption is primarily associated with productivity gains driven by capital deepening and task reallocation rather than direct labor substitution, with little to no short-run decline in total employment. In many cases, AI-adopting firms experience higher wages, increased innovation, and firm growth that offsets task-level automation. These patterns suggest that AI has largely functioned as an augmenting technology at the firm level. However, important questions remain regarding the distribution of these gains across workers and firms, as well as the longer-term implications for employment, skill demand, and inequality. This research proposes to examine the channels through which AI affects productivity and labor outcomes, assess who benefits from AI-driven growth, and evaluate the conditions under which AI augmentation may translate into more inclusive labor market outcomes.The Political Economy of Corporate Governance in the Age of Artificial Intelligence (AI): The Case for a Universal Individual Account (UIA)
Abstract
This paper explores the effect of generative AI systems on corporate governance, which is often conceptualized as a three-player relationship among capital, management, and labor. The rapid diffusion of AI across industries is transforming labor markets by automating both routine and cognitive tasks, increasingly substituting for human workers in administrative, analytical, and decision-making roles. Unlike earlier technological shocks that primarily affected manual labor, AI is expanding automation into white-collar occupations and may lead to large-scale labor displacement. At the same time, AI-driven productivity gains can sustain corporate profitability and increase firm valuations, thereby strengthening capital markets even as labor demand declines. This dynamic risk furthers decoupling corporate financial performance from wage growth and could intensify the divergence between capital income and labor income. Such structural changes may have profound implications for the political economy of corporate governance. If a growing share of the population no longer participates in the economy primarily as workers, traditional mechanisms linking citizens to corporate performance may weaken. While proposals such as universal basic income (UBI) seek to address technologically driven unemployment, they risk generating adverse incentive effects and political pressures for redistributive policies that could undermine investment and innovation. The article proposes an alternative policy framework: the "universal individual account"(UIA). Inspired by individual retirement accounts, UIAs would allocate periodic capital contributions to all citizens from birth onward, enabling individuals to accumulate diversified ownership stakes in the economy. By transforming citizens into long-term investors, UIAs would preserve broad societal alignment with corporate success, maintain incentives for productivity and innovation, and integrate citizens into the corporate governance system through capital ownership rather than income transfers.Algorithmic Management and Labour Regulation: Governing Artificial Intelligence in the Workplace in Emerging Economies
Abstract
The increasing integration of artificial intelligence (AI) into workplace management is transforming how employers organise, supervise and evaluate labour. Through algorithmic management systems, employers now rely on automated decision-making tools to allocate tasks, monitor worker productivity and make employment-related decisions. While these technologies promise efficiency and productivity gains, they also raise complex legal and regulatory concerns, particularly in emerging economies where labour law frameworks are still evolving. This paper examines the implications of algorithmic management for labour regulation and employment relations in emerging economies, using Nigeria as a primary case study. It explores how AI-driven workplace governance challenges traditional labour law doctrines, including employer accountability, transparency in decision-making, procedural fairness in disciplinary processes, and the protection of collective labour rights. Particular attention is given to the "black box" nature of algorithmic systems, which obscure decision-making processes and limit effective regulatory oversight. The paper further analyses regulatory gaps in addressing algorithmic management and considers emerging global responses, including developments in Europe and the United States aimed at regulating automated decision-making in employment contexts. It advances the literature by proposing a context-sensitive regulatory framework for governing algorithmic management in emerging economies, addressing deficiencies in transparency, accountability, and worker protection within existing labor law systems. It also considers the implications of algorithmic management for labor market inequality, job security, and the reconfiguration of employer—employee power dynamics. The paper argues that without deliberate legal reform, the expansion of algorithmic management risks undermining fundamental labour rights in rapidly digitalizing labor markets.Discussant(s)
Yaya Sissoko
,
Indiana University of Pennsylvania
Steven Payson
,
Johns Hopkins University
Rolanda Santos
,
John Carroll University
JEL Classifications
- J1 - Demographic Economics
- J0 - General