AI and Automation Drive Labor Efficiency as Productivity Paradox Fades

A Shakespearean “sea change” is unfolding in the labor market as the long-standing “productivity paradox” shows early signs of resolution, according to Bank of America (BofA) Research. This term—originally used by Shakespeare to describe a sudden and profound transformation—now appears to capture the economic shift driven by artificial intelligence (AI), automation, and post-pandemic efficiency strategies [1].

The productivity paradox, first articulated by Nobel laureate Robert Solow in 1987, highlights a puzzling disconnect between technological advancements and measurable gains in productivity. Despite the proliferation of digital tools and the rise of AI, worker productivity metrics have remained stubbornly flat for over two decades [1]. However, BofA’s analysis suggests that a fundamental shift is taking root, driven by the confluence of AI adoption and the need for businesses to operate with fewer resources in the wake of inflationary pressures [1].

Savita Subramanian, Head of US Equity & Quantitative Strategy at BofA, explains that companies are increasingly turning to processes and automation to reduce labor dependency. By calculating sales growth adjusted for inflation and dividing it by the number of employees, BofA developed a proxy for productivity. The results indicate that firms are achieving more with fewer workers, a trend it calls “labor efficiency” [1]. This shift is not only about displacing employees but also about rethinking traditional business models.

The transformation is reshaping valuation dynamics in the S&P 500, according to BofA’s findings. Innovation-driven companies—particularly in tech and healthcare—trade at higher multiples compared to more capital-intensive manufacturers [1]. However, the rapid expansion of data center infrastructure signals a potential reversal as AI shifts from an asset-light to a more capital-heavy endeavor [1]. This could challenge the so-called “innovation premium” that has favored high-R&D firms.

Subramanian also highlights broader structural changes in the economy, including a slowdown in globalization and the end of a low-interest-rate era that once enabled aggressive financial engineering. These shifts have curtailed companies’ ability to manipulate earnings through buybacks and debt-driven strategies, making it more difficult to artificially inflate performance [1].

The economic “sea change” parallels the thematic shifts in Shakespeare’s late plays, which often featured sudden reversals of fortune. Subramanian draws this comparison not just for literary flair but to underscore the magnitude of the current transformation. Just as the industrial revolution reshaped society, the rise of AI and automation may redefine the future of work and investment [1].

Critics like Jeremy Grantham have raised concerns over the ethical implications of stock buybacks, and while their frequency has slightly declined, they remain elevated by historical standards [1]. This reflects the complexity of the current landscape, where companies must balance efficiency, ethics, and investor expectations.

While the productivity surge is still unfolding, BofA sees AI as a catalyst rather than a standalone solution. The firm’s research suggests that the combination of AI and post-pandemic operational pressures is unlocking efficiency in ways previously unattainable [1]. The challenge now is to ensure these gains are sustainable and broadly distributed.

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[1] https://fortune.com/2025/08/23/worker-productivity-ai-bofa-automation-inflation-do-more-with-less-sea-change/