Bostic: Businesses are not clear about whether AI tools will complement or replace workers on net

Bostic: Businesses are not clear about whether AI tools will complement or replace workers on net

Bostic: Businesses Uncertain Whether AI Tools Will Complement or Replace Workers

Recent analyses highlight growing uncertainty among businesses about whether artificial intelligence (AI) will ultimately augment or displace workers. Federal Reserve Bank of Atlanta President Raphael Bostic has noted this ambiguity, emphasizing that the net impact of AI on employment remains unclear despite rapid technological adoption.

Studies suggest that while AI adoption is accelerating, its labor market effects are neither universally disruptive nor uniformly positive. A Yale Budget Lab analysis of U.S. employment trends since 2022 found no statistically significant correlation between AI exposure and changes in employment or unemployment rates. The study observed that shifts in occupational composition—such as workers transitioning to new roles—mirror historical patterns seen during earlier technological transitions (e.g., the internet era), with no discernible acceleration linked to generative AI.

Worker sentiment, however, reveals deeper divisions. A global ADP Research Institute survey of 35,000 private-sector employees found that 85% expect AI to affect their jobs within two to three years, but opinions are split: 43% anticipate AI will help them save time, while 42% fear it will replace some or most of their tasks. Remote workers and younger employees, in particular, express heightened concerns about displacement, though confidence in skill adaptability remains higher among those who perceive AI as a productivity enhancer.

Research further complicates the narrative. A ScienceDirect study of 3,682 full-time workers found that AI is often perceived as complementary rather than substitutive, particularly in roles requiring human judgment or creativity. For example, AI tools are increasingly used to support tasks in sustainable development and green technologies, enhancing efficiency without direct job replacement. Conversely, data-rich industries like finance and software development face higher automation risks due to abundant training data, while data-poor sectors such as healthcare and construction struggle with fragmented adoption.

The lack of consensus underscores the need for better data. Current metrics, including AI exposure indices and usage statistics, remain limited in scope and granularity. As Bostic and others caution, the long-term labor market effects of AI will likely unfold over decades, not months, with outcomes shaped by industry-specific dynamics, workforce adaptability, and evolving regulatory frameworks. For now, businesses and policymakers must navigate a landscape where AI's potential to both create and displace jobs remains an open question.