Education · SOC 25-1032
Grading and grant writing are AI-assistable, but lab supervision and hands-on engineering instruction require human expertise.
Parts of the job are exposed, but judgment and context still matter.
Timeline: AI simulation and tutoring tools will absorb routine instructional tasks within 5 years, but hands-on lab leadership and frontier engineering research remain robust through 2030.
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Industry pages show which sectors this occupation feeds and the AI companies driving the shift.
AI job-risk card
Engineering Teachers, Postsecondary is watch on AIFear. Parts of the job are exposed, but judgment and context still matter.
AIFear.com
Our AI Fear Score for Engineering Teachers, Postsecondary is 40/100 (Watch). Parts of the job are exposed, but judgment and context still matter.
40 out of 100, based on an AI-model review of this occupation's O*NET tasks against what current AI can actually do.
Most exposed: Drafting syllabi, handouts, and course materials, Grading student assignments and lab reports, Advising on standard curricula and career paths, Planning and revising standard course content. Harder to automate: Conducting and supervising laboratory research, Teaching design judgment and engineering ethics, Mentoring capstone and thesis projects, Securing and managing research grants.
Lean into AI-assisted simulation and design tools, Research grant writing, Laboratory management, Engineering ethics education. Consider roles such as Engineering Research Scientist or R&D Lab Director or Technical Program Manager.
Tasks, skills and AI-exposure for this role were reviewed by an AI model against its O*NET task profile (curated roles use published research anchors). Pay and employment, where shown, are U.S. BLS OEWS (May 2024) figures. This is an estimate, not a prediction about any individual's job. Compare all occupations.