As artificial intelligence (AI) tools increasingly permeate daily work environments, their impact on the job market, especially for emerging professionals, is attracting attention. A recent study by the Stanford Digital Economy Lab, affiliated with the Stanford Institute for Human-Centered AI, highlights how early-career workers are feeling the effects more pronouncedly, with young software engineers among those most affected.
Analyzing data from Automatic Data Processing (ADP), the largest payroll provider in the U.S., the research uncovers trends in employment and earnings across various sectors, locations, and age groups. Findings published in August reveal that while there’s growing demand for AI skills, generative AI tools are effectively performing tasks previously done by early-career professionals. However, these tools currently lack the nuanced expertise that comes from years of experience, rendering senior positions less susceptible.
The study’s authors caution that this trend could forecast broader impacts, potentially affecting different age groups and roles over time. Bharat Chandar, a postdoctoral fellow involved in the research, emphasizes the ongoing need to track these changes, as other factors in the tech industry may also contribute to employment shifts.
Software engineers are recognized as particularly exposed to AI influences, with significant discussions around how AI coding tools affect these roles, especially for younger workers. Since late 2022, a decline in employment has been noted among software engineers aged 22 to 30, while job stability has persisted for mid-level and senior positions. This decline’s root causes may extend beyond AI, underscoring the complexity of the tech industry’s landscape.
In a broader context encompassing various “computer occupations,” similar patterns have been observed, suggesting a genuine impact of AI across industries. The research differentiates between AI-driven augmentation and automation of work. Jobs where AI augments human tasks have not experienced the same downturn as those where AI can automate work processes.
This analytical differentiation was supported by data from the Anthropic Economic Index, which assesses whether AI typically supports or replaces employee functions. The research team looks forward to accessing more comprehensive data from other AI developers like OpenAI and Google to refine their understanding.
Looking ahead, there is a plan to extend research beyond U.S. borders, acknowledging that the global scope of AI’s impact on employment will provide a deeper understanding of its role in the evolving job market. Despite challenges, there is a potential silver lining: AI, when used to augment rather than replace, could enhance productivity and create new opportunities for early-career professionals.