Israeli Universities Restructure Degrees as AI Challenges Traditional Teaching

Israeli higher education is undergoing a fundamental restructuring as generative AI forces universities to reconsider what a degree should deliver. The transformation extends beyond preventing students from using ChatGPT to write papers—it's reshaping curricula, assessment methods, and the very definition of what graduates need to know.

Computer science enrollment at Israeli universities fell 15% over two years, from 7,277 students in 2022/23 to 6,219 in 2024/25, according to data from Israel's Council for Higher Education. Many students shifted into AI-adjacent fields like data science and data engineering, where enrollment more than doubled from roughly 500 to 1,042 students over the same period.

Why it matters

The Israeli experience offers a preview of challenges facing universities globally. When AI can generate competent written work instantly, traditional assessment methods collapse. Universities must either find new ways to verify learning or risk becoming credential mills that certify AI-assisted work rather than human capability. The shift also reveals how quickly labor market signals can redirect student demand, even in historically stable fields like computer science.

From lectures to mentorship

Prof. Ami Moyal, chair of the Planning and Budgeting Committee of Israel's Council for Higher Education and an AI pioneer, argues the solution requires changing what universities produce. "AI won't replace employees with a strong AI orientation. It will replace employees who don't have that orientation," Moyal said.

The CHE is investing NIS 200 million (roughly $55 million) in retraining academic staff, with institutions matching that amount. The goal: transform faculty from lecturers who transmit knowledge into mentors who develop critical thinking, teamwork, and presentation skills.

But implementation faces structural obstacles. Universities still rely heavily on large introductory courses with hundreds of students. Oral exams and small-group discussions—the most effective ways to verify genuine understanding—don't scale to that model.

The assessment crisis

Prof. Manuel Trajtenberg, former chair of the Planning and Budgeting Committee, notes that AI detection tools have created an arms race no one can win. "One question is whether you can still ask students for papers, especially in advanced degrees, when the first thing they do is turn to AI," he said.

The alternative—oral exams, conversations, and presentations—works for graduate seminars but becomes impractical in mass undergraduate education. "It's an unsolved problem," Trajtenberg acknowledged. "If the goal of training is to impart skills, you need to know how to assess mastery of them, and that's much more complex than knowledge-based exams."

Redefining computer science

Rather than abandoning computer science, Israeli institutions are redefining it. The CHE approved nine new AI degree programs over the past year. Moyal believes software developers will increasingly manage teams of AI agents rather than write code directly, making task definition and quality control more important than programming syntax.

Dadi Perlmutter, chairman of the Technion's executive committee, emphasized that foundational knowledge remains essential. "You wouldn't take someone who knows how to use Claude and let them develop a missile," he said. Engineering departments remain at capacity, and the military continues recruiting physicists.

Trajtenberg sees AI as a powerful research accelerator—"like a research assistant who works 24/7 and doesn't complain"—but insists researchers remain essential for framing problems and directing solutions.

The details were first reported by Calcalistech, with reporting by Shahar Ilan.