Top 5 Jobs in Education That Are Most at Risk from AI in Israel - And How to Adapt

AI is no longer just a buzzword for Israeli schools - real adoption is underway and it matters for everyday education jobs: an IDI analysis of a CBS survey found 28% of Israeli businesses used AI in the past six months (with many employees reporting routine tasks shifted to AI), and HolonIQ's 2025 trends note that

AI moves from hype to serious implementation

across skills and workforce pathways; that combination means roles that hinge on repetitive grading, roster upkeep or templated lesson content are the most exposed.

For educators and administrators in Israel the challenge is practical: adapt workflows, learn prompt‑driven tools, and refocus on student-facing skills rather than data drudgery - think routine term spreadsheets handled in minutes so staff can spend that time on struggling students.

Short, work‑focused training can bridge the gap: the Nucamp AI Essentials for Work bootcamp teaches prompt writing and real workplace AI applications to help school staff pivot into higher‑value tasks.

The methodology blended Israeli labour mappings and task‑level automation research to pick the five education roles most exposed to AI: first, national job‑level data (which found about 15% of Israeli jobs at high risk and 54% at moderate risk) provided the exposure backdrop (Times of Israel: study on Israeli job automation risk); second, a task‑based filter - drawing on international estimates of which activities are automatable and summarized in task‑automation reviews - flagged roles dominated by routine, repetitive activities (Task automation review: international estimates of automatable activities); and third, local skill‑trend reports and Labour Ministry analysis validated where reskilling pipelines and policy support could realistically absorb displaced workers (Israel Hayom and Labour Ministry analysis on reskilling and automation).

Roles that scored high on repeatable tasks, low on discretionary judgement, and high concentration in schools therefore rose to the top - a triangulated, Israel‑focused approach that ties national risk rates to the “boring and repetitive” activities most likely to be automated.

“Staying informed about job market trends and being willing to acquire new skills is crucial in this rapidly changing environment.”

School secretaries, registrars and payroll/accounts clerks are squarely in the crosshairs because their work is built on repeatable, document‑heavy tasks that AI already handles well: attendance tracking, enrollment processing, filing and routine invoice or reimbursement workflows can be automated or routed to virtual agents, shaving hours off daily back‑office chores and turning piles of attendance sheets and enrollment forms into searchable records in minutes; vendors report implementations that cut admin time dramatically and add audit‑ready controls (AI tools for school administrators: attendance, enrollment, and records automation).

That matters in Israel, a country the data show is unusually exposed to AI-driven change and where the Labor Ministry flags skills investment as the key defense for affected workers (Israel Labor Ministry analysis on AI exposure and reskilling).

Practical takeaways: prioritize small, staged automations for repetitive workflows and train staff to oversee AI outputs so human judgement - especially when payroll exceptions or confidential student issues arise - remains central, echoing international findings that clerical roles face the highest automation risk (CNBC analysis of AI and automation impact on clerical jobs).

“Staying informed about job market trends and being willing to acquire new skills is crucial in this rapidly changing environment.”

Standardized exam graders and routine assessment markers in Israel are squarely exposed as AI moves from pilot projects to real-world performance: the Education Ministry's pilot showed software could scan and grade handwritten matriculation tests and, “three hours later, it produced results that were almost the same as the average grade given by the teachers,” signaling how quickly bulk scoring can be automated (Education Ministry pilot on AI grading); at the same time an Israeli study found ChatGPT‑4 passed medical licensing exams and even outscored many residents in some specialties, illustrating AI's rapid aptitude for high‑stakes assessment tasks (Israeli study: ChatGPT‑4 performance on license exams).

Universities are also weighing AI proctoring tools that photograph students and lock down browsers, changing how integrity and grading intertwine (college proctoring software discussions).

For graders this means routine scoring could shift to monitoring AI outputs, handling edge cases, and safeguarding assessment fairness - imagine piles of handwritten papers becoming searchable archives overnight, freeing human reviewers to focus on nuance, bias and contested marks.

“The fact AI can successfully face license exams only shows technology's maturity and highlights the fact that we must learn how to use it.”

Entry‑level, drill‑based private tutors in Israel face clear exposure as national pilots put a personal AI tutor in every student's pocket: the eSelf–CET experiment offers face‑to‑face avatar tutors that adapt to each learner, speak in Hebrew to start, and can generate images and videos on the fly to explain a tricky math step or rehearse an English oral exam - so a single student can get focused practice anytime, inside or outside the classroom (Calcalist Tech coverage of the eSelf–CET national AI tutor pilot in Israel).

Times of Israel coverage notes these conversational companions respond to questions with multimedia, making routine drill work instantly interactive and searchable, which undercuts the traditional model of repetitive, hourly private lessons (Times of Israel report on conversational avatar companions for student learning).

For tutors who teach scripted practice and repetition, the “so what?” is tangible: tasks that once required paid, hourly time can be delivered by an always‑on avatar - potentially at far lower cost than private sessions that can run up to about $70 an hour - so the practical adaptation is to specialise in human‑led mentoring, complex diagnosis, and motivation work that an avatar can't (yet) replace.

“Education is one of the strongest predictors of future opportunity – yet access to quality support remains deeply unequal, at a time when it's more critical than ever. This is precisely how AI should be integrated into education: not as a replacement for human educators, but as a powerful supplement that extends learning and promotes independence.”

Curriculum and content writers who churn out standard lessons and worksheets are squarely in the line of fire because the same AI features that speed course creation - automatic quiz and worksheet generation, instant summaries and translations, adaptive pathways and learning analytics - make routine, templated materials easy to produce at scale; as Educause explains, AI can automatically generate quizzes, flashcards and tailored content and use learner data to refine materials, while practical guides show how IDs can lean on prompt engineering and AI workflows to speed drafting and localization (Educause article: 10 Ways Artificial Intelligence Is Transforming Instructional Design, Practical guide to AI-powered instructional design (eLearning Industry)).

For Israel this is a real operational choice - national pushes on teacher preparation and AI integration mean schools could adopt these tools quickly, so writers who specialize in one-size-fits-all worksheets risk being sidelined unless they pivot to higher‑value skills: designing culturally relevant scenarios, authoring complex performance tasks, and supervising AI outputs for pedagogical soundness; imagine a week's worth of worksheets turned into leveled, audio‑annotated packets and searchable learning paths in minutes - content creators who focus on nuance, alignment and assessment fairness will be the ones schools still need (Teacher professional development and AI in Israel - 2025 guide).

Junior academic researchers and research assistants in Israeli education departments face a double squeeze from AI: routine research chores - literature scans, coding open‑ended responses, drafting baseline analyses - are increasingly automatable, which eats into the traditional training ladder for early‑career scholars, and international evidence shows that over‑reliance on AI dialogue systems can blunt critical thinking rather than boost it (effects of over‑reliance on AI dialogue systems).

At the same time, a multinational study of junior consultants found that inexperienced staff who lead AI training can recommend risk mitigations that run counter to expert advice, underlining why institutions should not simply outsource governance to the most junior team members (Harvard/MIT/Wharton research on juniors and AI training).

The practical consequence for Israel is concrete: entry‑level pipelines may shrink unless roles evolve - imagine a grad‑assistant's week replaced by a near‑instant annotated literature pull that leaves only the hard interpretive disputes for humans to settle.

Smart adaptation pairs technical prompt skills with methodological judgment and AI oversight training, dovetailing with national teacher upskilling efforts to keep early‑career researchers valuable to schools and universities (teacher professional development targets).

“Our interviews revealed two findings that run counter to the existing literature.”

Convert exposure into agency: Israeli education workers should treat the Ministry's national rollouts and sandbox pilots as a clear invitation to reskill, not a threat - join local pilots and mentor programs, learn to supervise AI outputs, and move from repeating worksheets to designing culturally relevant tasks and edge‑case assessments that only humans can defend; the Ministry's sandbox and large mentor push mean there are real, school‑level opportunities to test tools under regulated conditions (JNS: AI sandbox for public education).

Short, practical programs that teach promptcraft and workplace AI workflows will pay immediate dividends - teachers who learn to use these tools can reclaim time for students and higher‑value work, and targeted bootcamps like Nucamp's AI Essentials for Work teach prompt writing, real AI tools, and job‑based applications in 15 weeks (AI Essentials for Work syllabus), making the transition affordable and actionable.

In practice: start with a 4–6 week focus on prompt skills and assessment oversight, volunteer as a school change agent to pilot classroom workflows, document wins (time saved, improved interventions), then scale skills into curriculum design or edtech collaborations - so the “so what?” becomes tangible: more time with struggling students instead of stacks of routine tasks, and a career that rides the AI wave rather than being swept away.

Our studies show that with AI, teachers can regain one to two workdays per week and help close two-year learning gaps in just a few weeks.