2026 ASEE Annual Conference & Exposition

With generative AI rapidly reshaping engineering practice, higher education faces growing pressure to prepare students and professionals for evolving workforce expectations. This paper presents preliminary findings from semi-structured interviews with civil, construction, and environmental engineering (CCEE) employers and alumni affiliated with a large, public R1 university. Interviews aimed to understand: (1) AI training and workforce development needs, (2) how training pathways shape professionals’ perceptions of AI’s opportunities, risks, and ethics, and (3) the role of universities in preparing graduates for AI-enabled engineering practice. Preliminary results indicate that perceptions of AI are shaped less by employers’ beliefs about its disruptive impact than by exposure and training, with training possibly mediating the outlook, ethical concerns, and expectations for workforce readiness and university involvement. This work-in-progress is a preliminary analysis for a multi-college interdisciplinary project whose findings will inform future survey development, workforce analytics integration, and the design of AI-infused CCEE curricula, certificates, and industry-engaged learning pathways.