Seyed Mahdi Hosseini Maasoum

Hosseini Maasoum is an academic economist and co-author of a widely cited 2025 SSRN working paper examining how generative AI adoption affects employment by seniority level. The paper, produced with co-author Lichtinger, analyses 62 million US worker resumes across 285,000 firms over the period 2015 to 2025 and was presented at the Stanford Digital Economy Lab. Its central finding — that entry-level job postings fell 15% in AI-integrating firms while senior-level postings fell only 3% — established the 'seniority trap' concept in AI employment research.

The methodology distinguishes the paper from survey-based research: resume data captures actual hiring outcomes across a large and longitudinal sample, rather than employer intentions or self-reported estimates. The decline in entry-level postings is driven by slower hiring rather than increased separations or accelerated promotions, meaning AI is closing the bottom rungs of career ladders rather than flattening hierarchies. The study was produced in August 2025, making its findings available before the March 2026 displacement acceleration visible in Challenger and BLS data.

The policy implication Hosseini Maasoum and Lichtinger draw is forward-looking: if entry-level pipelines are automated away today, firms will face a structural senior talent shortage within three to five years. The workers who would have become senior engineers, analysts, and managers in 2028 to 2030 are the cohort currently finding no entry-level postings. The research provides an academic foundation for arguments that AI displacement is not merely a near-term labour market problem but a long-term human capital depletion risk.