Earnings Call, Interview, Conference Presentation
Why we believe AI reshapes work more so than it reduces overall payrolls
- Historical precedents and current data suggest AI will primarily transform or augment tasks rather than eliminate entire occupations at scale, with about 25% of global jobs exposed to generative AI and 13% showing high augmentation potential versus only 2.3% with high automation potential.
- Significant disruption is anticipated in collaborative code support, customer service, administrative work, and data entry, leading to redesigned roles where workers shift from mechanical data processing to interpretation, strategy, and communication, while new specialized positions like prompt engineers and AI trainers emerge.
- Sectors centered on trust, care, and human interaction such as healthcare and education are expected to expand, alongside opportunities for entrepreneurship and small business formation as agentic AI lowers barriers to entry, though 60% of US jobs currently existed in occupations that did not exist in the 1940s, indicating future job creation will be difficult to predict.
- Advanced economies face the highest exposure to AI due to their white-collar workforces, with Europe and Central Asia showing the highest regional exposure rates, followed by the Americas, yet they are better positioned to convert this exposure into productivity gains through superior human capital and digital infrastructure compared to low-income economies where only about 11% of jobs are exposed.
- Risks include faster and more uneven adjustment concentrated in white-collar work and early career roles, with evidence showing a decline in employment for US workers aged 22 to 25 in AI-exposed occupations and concerns that capital owners may capture a larger share of wealth if new labor-intensive tasks are not created.
- Agentic AI starting from 2024 is expected to automate larger portions of production chains and coordinate workflows, prompting concerns that companies may lay off employees at a faster pace, although some clients anticipate government intervention similar to moves in Europe, China, and the US to ensure even distribution of gains.
- Macro-economic impacts include potential disinflationary pressure and higher neutral rates over time, as productivity gains lower unit labor costs and expand supply capacity, though near-term effects on inflation and rates may be limited due to uneven distribution of gains among leading firms.
- Wage dispersion may increase within occupations as experienced workers become more productive while demand for routine entry-level tasks declines, with some investors worrying that unequal wealth distribution could limit new job creation, while others note that current youth unemployment trends in regions like China involve structural demographic factors beyond AI displacement.
- The outlook notes that while productivity gains should historically lead to output expansion and lower costs, the transition may involve temporary inflation spikes and increased fiscal spending due to labor market pressures, with the discussion on AI's impact expected to continue over the coming year.