How is generative AI transforming the labor market?

According to Harvard Business Review, a study conducted by Suraj Srinivasan and his coauthors provides early answers. According to their findings, job postings for roles involving structured and repetitive tasks declined by 13% after the spread of generative AI. In contrast, demand for jobs requiring analytical, technical, and creative skills increased by 20%. This suggests that AI is not only eliminating certain jobs but also creating new opportunities.

The study also finds that in occupations more prone to automation, the number of required skills has decreased by 7%. Meanwhile, in roles with high potential for augmentation, there has been an increase in demand for new skills, such as using AI tools and writing effective prompts.

The impact of generative AI also varies across industries. The largest declines in job postings were observed in the finance and technology sectors. However, even in these fields, AI is not fully replacing human workers. For example, financial analysts can use AI to process large amounts of data more efficiently, but human judgment remains essential for decision-making.

Another line of research examines AI’s impact at the task level rather than the occupation level. This approach shows that there is still a significant gap between AI’s theoretical capabilities and its real-world use. For instance, in computer and mathematics-related occupations, about 94% of tasks could theoretically be accelerated by AI, yet actual usage covers only around 33% of those tasks. This indicates that much of AI’s potential has not yet been realized.

Overall, about 97% of tasks fall into categories that AI can theoretically perform either fully or partially. However, in many occupations—such as cooks, mechanics, and lifeguards AI has little to no impact because their tasks require physical or highly specialized human skills.

Looking at broader labor market indicators, there is still no clear evidence of large-scale disruption. The difference in unemployment rates between occupations highly exposed to AI and those with low exposure is statistically insignificant (close to zero). This suggests that, so far, generative AI has not caused widespread job losses.

However, more subtle effects are emerging. According to projections from the U.S. Bureau of Labor Statistics, employment growth tends to be slightly weaker in occupations with higher AI exposure. Specifically, for every 10 percentage point increase in AI task coverage, projected employment growth decreases by about 0.6 percentage points.

One area of concern is younger workers. Research shows that employment in AI-exposed occupations among individuals aged 22 to 25 has declined by 6% to 16%. Importantly, this decline appears to be driven more by reduced hiring rather than increased layoffs.

In conclusion, current evidence suggests that generative AI is not simply replacing jobs but transforming the nature of work. While some roles are declining, others are expanding, and new skills are emerging. The dominant trend is the growing importance of human-AI collaboration, where AI enhances productivity rather than fully substituting human labor.