AI Resilience Report forEngineering Teachers, Postsecondary

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.

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.