What Impact Will AI Have on the Labor Market?

The transition to artificial intelligence, however, is progressing more rapidly than previous technological shifts. Examining the labor market, data reveal that AI’s impact is generating three distinct dynamics: targeted automation of specific tasks, the use of AI to address demographic aging, and a rapid surge in demand for labor in skill‑short sectors.

Impact on Entry‑Level Roles

Early signals show AI beginning to automate repetitive, rule‑based activities. This is most evident in entry‑level positions, where workflows tend to be highly structured and predictable; now, more experienced employees are tasked with verifying the outputs produced by AI.

Analyzing AI exposure across occupations in the U.S. labor market, our research found that roughly 21 % of U.S. jobs involve tasks that are technically automatable by AI. It is important to emphasize that this figure reflects task exposure—not job elimination—and falls within the 20 %–30 % range identified by other academic and industry studies.

Industries with a high concentration of administrative, customer‑service, and back‑office roles are most exposed to AI. Healthcare, retail, and commercial services stand out for the sheer volume of such activities rather than for the potential to automate direct‑to‑customer work.

Nonetheless, job reductions are manifesting through slower hiring and higher turnover, resulting in a 29 % decline in global entry‑level job postings since 2024[1]. The long‑term concern is a potential talent pipeline shortage for early‑career professionals, as companies may struggle to develop the experienced workforce they will need in the future.

Closing Workforce Gaps to Meet Demographic Aging

In many skilled occupations, the primary challenge is a labor shortage—not job loss. Experienced workers are retiring faster than new hires can replace them, especially in professions that require lengthy training, certifications, or that find it difficult to attract younger talent. In these areas, AI is increasingly leveraged to augment small teams, boosting productivity and reducing operational friction.

Both research and our corporate experience suggest that AI adoption is largely driven by the need to increase productivity, even as entry‑level tasks are automated early on. 78 % of senior executives agree with this assessment[2], now viewing AI as more advantageous for revenue growth than for cost reduction.

Consequently, AI helps organizations maintain production and service levels where workforce shortages and an aging labor force would otherwise curtail operational capacity. In the United States, workers aged 55 and older now comprise about one‑quarter of the labor force, and healthcare is among the sectors facing the greatest replacement challenges. In this context, AI exposure in healthcare focuses primarily on administrative and documentation activities rather than direct patient care.

AI Is Creating a Skills Shortage

Simultaneously, AI is spawning new job categories while intensifying demand for existing ones, such as data‑center engineering, grid modernization, and roles that blend commercial insight with AI implementation.

Companies across various sectors report that these AI‑related positions are considerably harder to fill than traditional roles. The risk to the labor market, therefore, is not an excess of workers but a shortage of adequately skilled talent. Our analysis shows that, even within the same industry, firms that embed AI into workflows and redesign processes are poised to achieve substantially higher margins and productivity than those that remain in pilot or experimental phases. This execution gap stems from differences in operational capability, corporate governance, and organizational readiness.

Investment Implications

In sectors with moderate automation intensity yet a sizable workforce, investment opportunities are evident, but realized benefits will depend on company‑level implementation, creating the potential for marked differentiation among firms.

Across industries, this dynamic manifests in varied ways. Retail is particularly exposed, with approximately 4.6 million U.S. jobs affected by AI, impacting roughly 30 % of activities such as cash handling, planning, inventory management, and pricing. Manufacturing shows high technical automation potential but considerable variation across sub‑sectors: capital‑goods industries retain a larger concentration of AI‑exposed design, coordination, and documentation roles compared with the automotive sector, where physical automation is already entrenched.

Overall, these trends point to a labor market undergoing structural transition. As AI adoption accelerates, factors such as the risk that entry‑level job reductions may diminish the pool of qualified workers in the future, the growing need to upskill the existing workforce, and demographic pressures that exacerbate critical skill shortages will increasingly shape corporate operational resilience and long‑term performance.

By Sally Springer, Senior Sustainable Research Analyst, Global Research, Columbia Threadneedle Investments