Why we believe AI reshapes work more so than it reduces overall payrolls

Core Thesis on Labor Impact

• BofA Global Research rejects "apocalyptic" job destruction narratives, arguing AI will primarily transform specific tasks rather than eliminate entire occupations at scale.
• While approximately 25% of global jobs are exposed to generative AI (per ILO data), only 2.3% have high automation potential, whereas 13% offer significant augmentation potential.
• Roles facing shrinkage include collaborative coding support, customer service, administrative work, data entry, and specific ICT functions.
• The primary shift involves reallocating human effort from routine tasks (drafting, searching, processing) to higher-value activities like interpretation, decision-making, communication, and strategy.

Emerging and Evolving Job Categories

• AI Specialists: New roles include prompt engineers, AI trainers, model evaluators, and positions requiring ethical judgment and domain expertise.
• Hybrid Professionals: Existing roles will expand to integrate AI tools, such as research analysts focusing on interpreting AI-generated data or lawyers utilizing AI for document review while shifting to legal strategy.
• Human-Centered Services: Sectors like healthcare, elderly care, education, and personal services are expected to grow due to higher real incomes and shifting consumer demand toward trust-based interactions.
• Entrepreneurship: Agentic AI may lower barriers to entry, enabling "one-person companies" and fostering new small business formation.
• Historical precedent shows that 60% of current US jobs did not exist in the 1940s, suggesting new roles will emerge endogenously as productivity increases.

Historical Parallels and Adaptation Capacity

• Past General Purpose Technologies (Industrial Revolution, Internet, Excel) displaced tasks but ultimately raised productivity, lowered costs, and created unimagined jobs.
• Advanced economies (Europe, Americas) face the highest exposure rates (approx. 33% of jobs) compared to low-income economies (approx. 11%), yet are better positioned to adapt.
• Adaptation drivers in advanced economies include higher human capital, advanced education systems, deep digital infrastructure, and flexible labor markets.
• Aging demographics in Europe, North Asia, and North America may benefit from AI offsetting labor shortages by boosting output per worker.

Client Feedback and Contested Views

• Investors generally agree on high exposure for white-collar cognitive jobs but debate the interpretation of risks associated with "agentic AI" (autonomous action capabilities emerging in late 2024/2025).
• Concerns exist that capital owners may capture disproportionate wealth, potentially limiting the consumer base for new service-sector jobs.
• The research team anticipates government intervention to ensure even distribution of productivity gains and facilitate labor transitions.

Wages, Inequality, and Labor Distribution

• Aggregate wage data from the post-2022 period shows no direct, broad-based decline in wages linked to AI exposure across 200+ US occupations.
• Dispersion risks exist: experienced workers utilizing AI effectively may see wage growth, while demand for entry-level routine tasks may shrink.
• A primary risk is the disproportionate flow of productivity gains to capital owners and firms with strong data/infrastructure, potentially increasing the capital share of income.
• Policy levers for mitigation include training programs, labor mobility support, wage insurance, and tax design reforms.

Youth Employment Dynamics

• Youth unemployment (ages 22-25) in AI-exposed occupations has declined significantly, but this cannot be solely attributed to AI.
• Structural factors, such as a doubling of new graduates in China over the last decade and slowed labor demand in the property sector, are significant drivers of weak youth employment.
• AI may specifically reduce demand for entry-level routine work that traditionally served as a training ground for early-career professionals.

Macroeconomic Implications and Interest Rates

• AI-driven productivity is theoretically disinflationary over the long term by lowering unit labor costs and expanding supply capacity.
• Central banks may gain room to tolerate temporary inflation spikes if productivity gains materialize, though immediate effects on rates may be limited.
• Productivity growth could paradoxically push up the neutral real rate by increasing the return on capital, creating a complex policy trade-off.
• Transition costs, including potential fiscal spending on labor market adjustments, could increase bond supply and pressure long-term rates.
• Gains are likely to be uneven, with early productivity spikes concentrated in leading firms rather than the aggregate economy.