2026 ASEE Annual Conference & Exposition

The rapid integration of artificial intelligence (AI) and advanced automation is reshaping mechanical engineering practice, altering both the nature of engineering work and the skills employers demand. While prior research has documented the growing influence of AI in engineering broadly, limited empirical evidence exists on how employer expectations for AI-related competencies in mechanical engineering have evolved over time and across geographic regions. Drawing on skill-biased technological change and human capital theory, this study examines longitudinal and regional trends in AI-related skill demand using large-scale online job posting data. The study analyzes 508,477 U.S. mechanical engineer job postings collected from 2015 to September 2025 from LinkUp, a job market data provider that sources postings directly from employer websites. A hybrid two-stage skill identification approach was employed. First, an inductive discovery process using natural language processing and a locally deployed large language model identified engineering-specific AI and data-driven competencies from a representative sample of postings. Second, these inductively derived terms were integrated with the Lightcast-Burning Glass Skills Taxonomy to create a domain-specific AI skill dictionary, which was applied to the full dataset. Job postings were classified as AI-related if they contained at least one validated AI-related term. Temporal and geographic analyses were conducted at the state and city levels.

Preliminary results show a substantial increase in AI-related skill demand over the study period, with AI-related postings rising from approximately 10% of mechanical engineer job postings in 2015 to over 20% by 2025. Growth accelerated notably after 2020, despite short-term fluctuations linked to broader labor market volatility. The findings also reveal pronounced geographic concentration, with California, Michigan, and Texas emerging as leading hubs for AI-enabled mechanical engineering roles. The results also report the 10 most frequently requested skills. These findings highlight the growing importance of AI-related competencies in mechanical engineering and underscore the need for responsive curriculum development and ongoing professional upskilling to align engineering education and workforce development with evolving labor market demands. We prefer this work-in-progress paper to be presented as a poster.