Labor Markets and the Future of Work

This is the third installment in our four-part series examining artificial intelligence (AI) through a wide-angle economic lens. In the first essay, we explored the historical development of artificial intelligence and the recurring cycles of enthusiasm and disappointment that have shaped the field’s development. The second examined how major technological innovations diffuse through the economy and why productivity gains often take years or decades to fully materialize. If you have not yet read those pieces, we encourage you to explore them as well.

Across this series, we examine four related questions: the origins of modern AI technologies, the economic dynamics that shape technological adoption, the implications for labor markets and the future of work, and the potential consequences for productivity and long-term economic growth.

Executive Summary

The third installment of this series examines how generative artificial intelligence may reshape labor markets and the future of work.

Historically, technological revolutions have triggered fears of mass unemployment that have ultimately always proved exaggerated. While individual occupations were displaced, new industries and roles emerged, and the growth generated by new technology lifted living standards across the board.. Economists often point to this historical pattern as evidence that automation ultimately complements human labor rather than replacing it.

Generative AI may challenge that assumption. Unlike previous waves of automation that targeted routine manual work, modern AI systems are increasingly capable of performing cognitive tasks once dominated with highly educated professionals. Lawyers, analysts, programmers, marketers, and other knowledge workers now face potential automation of the key workflows that define their careers.

Early research suggests the effects may be uneven. In routine tasks, AI tools appear to help less experienced, junior workers improve productivity. In more complex, judgment-based work, however, the technology may amplify differences in expertise, benefiting highly skilled professionals while displacing junior workers whose roles traditionally served as training grounds. From drug discovery to scientific research to legal and financial services, AI increasingly doesn’t just automate; it breaks new ground. Benefits are likely to accrue to the highest-paid, most senior talent and to the owners of capital.

At the same time, corporate incentives are increasingly aligned with labor substitution. Firms are adopting AI tools to reduce headcount, slow hiring, and improve margins. This shift is occurring alongside structural labor market trends such as declining mobility, rising education costs, and slower workforce adaptation.

Whether generative AI will obviate most human skills, necessitating a one-day workweek and universal basic income, or will simply shift the frontiers of what humans and computers can do together cannot be known with certainty. The trajectory will depend not only on technological capabilities but also on policy choices, organizational strategies, and how institutions adapt to the changing nature of work.

For investors, these dynamics matter because changes in productivity and labor costs ultimately shape corporate profitability, economic growth, and long-term market returns.

About the Author

Josh Rowe, Managing Director of Research at HB Wealth, wrote a PhD thesis in the history and economics of technology, focusing on computer automation of office work in the 20th century. He has studied the history of AI, venture capital’s funding of technological innovation, and the impact of technological change on financial markets—both as a resident of the ivory tower and as an investor. This surprising moment in history is the first time that he can say with any confidence that the years he spent in libraries and databases working on a doctoral dissertation might be of any practical use. He used AI in organizing and editing these essays, but the ideas (right and wrong) here are his own.

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