Somewhat Resilient
Last Update: 8/30/2026
AI Resilience Score for Engineering Teachers:
43.4%
Median Score
Meaningful human contribution
Measures the parts of the occupation that still require a human touch. This score averages data from up to four AI exposure datasets, focusing on the role’s resilience against automation.
Low
Long-term employer demand
Predicts the health of the job market for this role through 2034. Using Bureau of Labor Statistics data, it balances projected annual job openings (60%) with overall employment growth (40%).
Med
Sustained economic opportunity
Measures future earning potential and career flexibility. This score is a blend of total projected labor income (67%) and the role’s inherent ability to adapt to economic and technological shifts (33%).
Med
This reflects the reliability of your score based on the number of data sources available for this career and how closely those sources agree on the outlook. A higher confidence means more consistent evidence from labor experts and AI models.
This result is backed by strong agreement across multiple data sources.
Contributing sources
AI Resilience Report forEngineering Teachers, Postsecondary
$109,270 median salary•3,900 annual openings•SOC Code: 25-1032.00
Engineering Teachers, Postsecondary are somewhat less resilient to AI impacts than most occupations, according to our analysis of 8 sources.
Engineering professors are labeled "Somewhat Resilient" because AI is actively changing a meaningful chunk of their daily work, like grading, writing syllabi, and tracking student progress, even while the most human parts of the job remain hard to replace. The core value of this career still lives in hands-on lab supervision, one-on-one mentoring, and guiding students through real engineering challenges, and those are exactly the things AI cannot replicate.
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Engineering professors are labeled "Somewhat Resilient" because AI is actively changing a meaningful chunk of their daily work, like grading, writing syllabi, and tracking student progress, even while the most human parts of the job remain hard to replace. The core value of this career still lives in hands-on lab supervision, one-on-one mentoring, and guiding students through real engineering challenges, and those are exactly the things AI cannot replicate.
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Engineering Teachers
Updated Quarterly
How is AI changing Engineering Teachers jobs?
Right now, AI is mostly augmenting engineering professors rather than replacing them, especially for the paperwork-heavy parts of the job. A new survey of 438 higher-ed educators found that most faculty and staff who responded to the survey use AI tools to create and administer assessments, and most of them believe students use AI tools while taking assessments, which lines up with the high automation scores for recordkeeping, exam grading, and prepping syllabi. A systematic review in Frontiers in Education [1] found that AI agents can cut code-assessment time by more than half and help predict which students are struggling with high accuracy, freeing professors to focus on mentoring.
Engineering-specific research shows the same pattern: an ASEE peer-reviewed paper [2] argues that the widespread accessibility of AI technologies represents a critical inflection point, demanding a reconsideration of how educators prepare students for engineering problem-solving, collaboration, and ethical decision-making. But hands-on tasks — supervising labs, guiding research, and sitting on committees — remain very human. A brand-new Frontiers study of engineering faculty [1] reports that professors are adapting through "reluctant engagement," accommodating AI not from conviction but from perceived inevitability, while reasserting the irreplaceable value of experiential, in-person, and mentorship-based learning.
Sources
How fast is AI adoption growing for Engineering Teachers?
Adoption is moving quickly, but unevenly. The Digital Education Council's Global Survey 2026 [3] reports that a majority of faculty in APAC, EMEA, and Latin America continue to see themselves using AI in their teaching in the future. This has remained largely unchanged from 2025, though in the U.S. and Canada, faculty intent to use AI has declined by 9 percentage points, from 76% in 2025 to 67% in 2026.
Two big forces are speeding things up: cheap, ready-made tools (ChatGPT, Copilot, auto-grading platforms) and pressure from employers. Inside Higher Ed [4] reports that as of March, more than a third—35 percent—of entry-level jobs require AI skills, up from 13 percent six months prior, pushing engineering programs like Purdue's to add AI requirements across hundreds of degree plans. Professional societies are joining in too — IEEE Spectrum [5] reports that IEEE's 2026 Education Week produced 114 events, 23 resources, and 11 special offers to help faculty upskill.
What's slowing adoption down is trust and integrity. Because AI can boost grades on take-home work — a UC Berkeley study cited by Axios [6] found that since the release of ChatGPT in 2022, "excellent" grades rose by 30% in classes where AI is useful — engineering faculty are rethinking assessments rather than handing them over to bots. The bottom line: your future professors will use AI to handle busywork, but the human coaching, lab supervision, and career mentoring that make an engineer are exactly the parts that AI can't do.
Sources
Will AI replace Engineering Teachers?
Not entirely. We think AI will take over some tasks, but not the whole job.
Our 43.4% AI Resilience Score reflects real pressure on this role. The parts of the job that are most routine, grading, recordkeeping, syllabus prep, are already being automated. Research shows AI agents can cut code-assessment time by more than half and predict which students are struggling with high accuracy [1]. That is genuinely significant workflow change, not just minor tweaks.
But the core of what an engineering professor does is harder to hand off. Supervising labs, guiding research, mentoring students through complex problem-solving, and modeling professional judgment are deeply human activities. A study of engineering faculty found professors are adapting by leaning into experiential, in-person, and mentorship-based learning as the parts AI cannot replicate [1]. Meanwhile, engineering programs are adding AI requirements across degree plans precisely because employers want graduates who can work alongside these tools [4], which means professors need to teach that too.
The economic picture is mixed but not alarming. Employer demand and earning potential both land at medium, meaning this career is not thriving, but it is not collapsing either. The professors who will do best are the ones who let AI handle the busywork and invest their energy in the human coaching that actually makes engineers.
Sources
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Latest AI news for Engineering Teachers
These articles provide valuable insights for aspiring Engineering Teachers, Postsecondary, highlighting the importance of integrating AI in education. For instance, the piece on AI-based tools for scientific writing emphasizes the need for educators to adapt their teaching methods to enhance student skills. Additionally, the exploration of AI's impact on various professions illustrates the necessity for engineering faculty to prepare students for a future where AI plays a pivotal role. Embracing these changes fosters AI resilience, ensuring that educators remain relevant and equipped to guide students through evolving technological landscapes.
Microsoft researchers have revealed the 40 jobs most exposed to AI—and even teachers make the list
fortune.com • 7/31/2025
Sorry, Gen Z: AI is expected to soon reshape dozens of popular professions—and possibly make some tasks obsolete.
Faculty Spotlight: Mohamed Farag and Exploring Generative AI with a Business Mindset - Information Networking Institute - College of Engineering
www.cmu.edu • 6/9/2025
Assistant Teaching Professor Mohamed Farag builds his curriculum around how students can apply what they see in the classroom to the real...
3 Questions: How to help students recognize potential bias in their AI datasets
news.mit.edu • 6/2/2025
Courses on developing AI models for health care need to focus more on teaching how to identify and address bias, says MIT Research Scientist...
Education faculty explore AI in the classroom
www.psu.edu • 12/3/2024
Penn State College of Education faculty members are working to help students harness the powers of generative artificial intelligence by...
Teacher’s Perceptions of Using an Artificial Intelligence-Based Educational Tool for Scientific Writing
www.frontiersin.org • 3/28/2022
Efforts have constantly been made to incorporate AI into teaching and learning; however, the successful implementation of new instructional...
More Career Info
Career: Engineering Teachers, Postsecondary
They teach college students about engineering, helping them understand concepts and solve problems to prepare for engineering careers.
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Employment & Wage Data
Median Wage
$109,270
Jobs (2025)
50,900
Growth (2025-35)
+7.8%
Annual Openings
3,900
Education
Doctoral or professional degree
Experience
None
Source: Bureau of Labor Statistics, Employment Projections 2025-2035
Task-Level AI Resilience Scores
AI-generated estimates of task resilience over the next 3 years
1
Perform administrative duties, such as serving as department head.
2
Participate in campus and community events.
3
Supervise students' laboratory work.
4
Serve on academic or administrative committees that deal with institutional policies, departmental matters, and academic issues.
5
Act as advisers to student organizations.
6
Supervise undergraduate or graduate teaching, internship, and research work.
7
Provide professional consulting services to government or industry.
Tasks are ranked by their AI resilience, with the most resilient tasks shown first. Core tasks are essential functions of this occupation, while supplemental tasks provide additional context.
