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Will AI replace Engineering Professor?
Educational Instruction and Library · $109,270 median pay · Graduate or professional degree
Automation exposure
How much of the work AI can already do
More exposed than 25% of the occupations in the index.
Averaged across 24 O*NET tasks, weighted by importance.
AI assistance potential
How much AI tools make the worker more capable
Postsecondary engineering teachers stand to gain immense productivity improvements from AI tools across all core pillars of their role: research, teaching, and administrative duties. For research, AI accelerates literature reviews, code generation for simulations, data analysis, and manuscript drafting. For teaching, generative AI dramatically speeds up curriculum design, problem set generation, slide creation, and automated grading assistance (especially for programming and analytical coursework). Furthermore, AI tools streamline the drafting of grant proposals and research reports. While live instruction, laboratory safety supervision, and direct student mentorship remain inherently human, an AI-fluent engineering professor can manage larger research outputs, produce richer teaching materials, and maintain faster publication cycles than a non-fluent peer.
What the work involves and who it suits, beyond AI.
What the two scores mean
Automation exposure is how much of the work current AI can already perform. A high score means the tasks are exposed, not that the job will disappear: how employers use that is a separate question.
AI assistance potential is how much AI tools make a worker in this occupation more capable. It is upside, not risk — a job can score high on both.
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