Engineering Teachers, Postsecondary
SOC: 25-1032.00 · Job Zone: 5
Key Takeaways
- ●AI Impact Score: 57/100 — Partial Automation Likely. Partial automation is likely for key tasks in this occupation.
- ●40K workers currently employed.
- ●Mean annual wage: $106,120. Higher wages create stronger economic incentive for AI replacement.
- ●4 of 15 key tasks can already be performed by AI tools today.
What Engineering Teachers, Postsecondary Do
Teach courses pertaining to the application of physical laws and principles of engineering for the development of machines, materials, instruments, processes, and services. Includes teachers of subjects such as chemical, civil, electrical, industrial, mechanical, mineral, and petroleum engineering. Includes both teachers primarily engaged in teaching and those who do a combination of teaching and research.
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AI Impact Analysis
Engineering Teachers, Postsecondary represent a specialized workforce of 39,910 professionals earning a mean annual wage of $106,120. This highly skilled occupation requires extensive expertise in both engineering principles and pedagogy, placing it in Job Zone 5 - the highest complexity level. The absence of projected employment change data suggests stability, but this masks the significant technological disruption already underway in higher education.
AI is rapidly automating core instructional tasks that comprise much of an engineering professor's workload. Course material preparation is being revolutionized by ChatGPT and Claude, which can generate syllabi, homework assignments, and handouts tailored to specific engineering disciplines. Grading and evaluation - traditionally consuming 20-30% of faculty time - is being automated by tools like Gradescope and Turnitin, which now use AI to assess not just multiple choice but also complex engineering calculations and design work. Research activities are being augmented by AI tools like Semantic Scholar and Elicit for literature reviews, while grant proposal writing is being assisted by platforms like GrantAI that analyze successful funding patterns.
Critical human-essential tasks center on the highest-value interpersonal and creative functions. Facilitating and moderating class discussions requires real-time adaptation to student questions and the ability to guide complex engineering problem-solving processes. Laboratory supervision demands hands-on safety oversight and the ability to troubleshoot equipment failures in real-time. Student mentoring and advising requires emotional intelligence and the ability to understand individual career aspirations and learning challenges. Creative thinking in research design and the ability to form collaborative relationships with industry partners remain distinctly human capabilities.
The transformation timeline is accelerating rapidly. Within 1-3 years, expect widespread adoption of AI teaching assistants handling routine student queries and automated grading systems for standardized assignments. The 3-5 year horizon will see AI-generated course content becoming standard, with professors shifting to curators and facilitators rather than content creators. Virtual reality and AI-powered simulation environments will begin replacing traditional laboratory experiences for certain engineering concepts.
Major universities are already implementing these changes. MIT has deployed AI tutoring systems across engineering courses, while Stanford uses automated code review systems for computer engineering classes. Georgia Tech's online engineering programs extensively use AI for student assessment and personalized learning paths. Corporate training programs from companies like Siemens and GE are replacing traditional engineering education models with AI-powered simulation and adaptive learning platforms.
Task-by-Task AI Analysis
| Task | AI Status |
|---|---|
Conduct research in a particular field of knowledge and publish findings in professional journals, books, or electronic media. AI assists with literature reviews and data analysis but human insight drives research direction and interpretation. | AI Assists Now |
Prepare course materials, such as syllabi, homework assignments, and handouts. AI can generate comprehensive course materials based on learning objectives and curriculum standards. | AI Can Do This Now |
Evaluate and grade students' class work, laboratory work, assignments, and papers. AI grading systems now handle complex engineering calculations and provide detailed feedback. | AI Can Do This Now |
Write grant proposals to procure external research funding. AI assists with proposal structure and language but human expertise drives research vision and methodology. | AI Assists 1-2 years |
Supervise undergraduate or graduate teaching, internship, and research work. Requires complex mentoring relationships and real-time problem-solving guidance that AI cannot provide. | Human Essential 5+ years |
Keep abreast of developments in the field by reading current literature, talking with colleagues, and participating in professional conferences. AI can summarize research papers and identify trends but human networking and conference participation remain essential. | AI Assists Now |
Prepare and deliver lectures to undergraduate or graduate students on topics such as mechanics, hydraulics, and robotics. AI can create presentation content but delivery and real-time adaptation to student needs requires human interaction. | AI Assists 1-2 years |
Initiate, facilitate, and moderate class discussions. Requires real-time adaptation to student questions and the ability to guide complex problem-solving processes. | Human Essential 5+ years |
Supervise students' laboratory work. Safety oversight and hands-on troubleshooting of equipment requires physical presence and expert judgment. | Human Essential 5+ years |
Compile, administer, and grade examinations, or assign this work to others. AI can generate questions, administer tests, and provide automated grading with detailed analytics. | AI Can Do This Now |
Collaborate with colleagues to address teaching and research issues. Complex interpersonal collaboration and consensus-building requires human emotional intelligence and relationship management. | Human Essential 5+ years |
Plan, evaluate, and revise curricula, course content, and course materials and methods of instruction. AI can analyze learning outcomes and suggest improvements but curriculum design requires human pedagogical expertise. | AI Assists 3-5 years |
Maintain student attendance records, grades, and other required records. Learning management systems with AI integration fully automate record-keeping and reporting functions. | AI Can Do This Now |
Maintain regularly scheduled office hours to advise and assist students. AI chatbots can handle routine questions but complex academic and career advising requires human guidance. | AI Assists 1-2 years |
Participate in student recruitment, registration, and placement activities. AI can streamline processes and identify prospects but relationship building and decision-making require human involvement. | AI Assists 1-2 years |
AI Tools Disrupting Engineering Teachers, Postsecondary
Key Skills
Key Tasks
- •Conduct research in a particular field of knowledge and publish findings in professional journals, books, or electronic media.
- •Prepare course materials, such as syllabi, homework assignments, and handouts.
- •Evaluate and grade students' class work, laboratory work, assignments, and papers.
- •Write grant proposals to procure external research funding.
- •Supervise undergraduate or graduate teaching, internship, and research work.
- •Keep abreast of developments in the field by reading current literature, talking with colleagues, and participating in professional conferences.
- •Prepare and deliver lectures to undergraduate or graduate students on topics such as mechanics, hydraulics, and robotics.
- •Initiate, facilitate, and moderate class discussions.
- •Supervise students' laboratory work.
- •Compile, administer, and grade examinations, or assign this work to others.
- •Collaborate with colleagues to address teaching and research issues.
- •Plan, evaluate, and revise curricula, course content, and course materials and methods of instruction.
Technology Skills Used
Hot + In Demand Hot Technology In Demand ↗ = View AI replaceability analysis
Salary Range
Career Transition Guidance
Engineering Teachers facing AI disruption have strong transition opportunities into related technical leadership roles. The closest career path is Architectural and Engineering Managers (11-9041.00), leveraging existing technical expertise while adding business management skills. This transition typically requires 2-3 years of management training and industry experience. Computer Science Teachers, Postsecondary (25-1021.00) offers another natural progression, requiring additional programming and AI literacy training that can be completed in 1-2 years through professional development programs.
Alternatively, Materials Scientists (19-2032.00) and other research-focused positions allow professors to transition their research expertise into industry R&D roles. These positions value the same analytical thinking, research methodology, and technical writing skills that engineering professors already possess. Career/Technical Education Teachers (25-1194.00) provides opportunities to apply teaching skills in more hands-on, industry-connected environments where human instruction remains essential. The key transferable skills include critical thinking (3.88/5), mathematics (3.88/5), and the core teaching competencies that AI cannot replicate.
Related Occupations
Frequently Asked Questions
Will AI replace Engineering Teachers, Postsecondary?
No, but the role will transform significantly. With our AI Impact Score of 57/100, approximately half of current tasks face automation within 5-10 years. The 39,910 engineering professors will shift from content creators to learning facilitators and research mentors.
What AI tools are used in Engineering Teachers, Postsecondary roles?
Current tools include ChatGPT for content creation, Gradescope for automated grading, Semantic Scholar for research assistance, and Canvas for administrative tasks. Traditional engineering software like AutoCAD, SolidWorks, and Python remain essential but are increasingly AI-enhanced.
What is the salary outlook for Engineering Teachers, Postsecondary with AI?
The current mean annual wage of $106,120 may increase for professors who successfully adapt to AI-augmented teaching. High-value human skills like mentoring and research leadership will command premium compensation as routine tasks become automated.
What skills should Engineering Teachers, Postsecondary develop for the AI era?
Focus on human-essential skills: complex problem-solving facilitation, emotional intelligence for student mentoring, creative research design, and industry collaboration. The top-rated skills of Speaking (4.12/5) and Learning Strategies (4.12/5) become even more critical as AI handles routine content delivery.
How many Engineering Teachers, Postsecondary jobs are there in the US?
There are currently 39,910 engineering teachers in postsecondary education. While no projected change data is available, the role is evolving rather than disappearing, with increased demand for AI-literate faculty who can bridge technology and pedagogy.