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No. UNESCO's 2024 AI in Education report explicitly addresses this and concludes that current and foreseeable AI augments rather than replaces teachers. The strongest current applications save teacher time on grading and admin so teachers spend more time on instruction, mentorship, and pastoral care — the parts of teaching humans do irreplaceably well. AI as a teacher-replacement is neither technically credible nor pedagogically defensible at this stage.

The EU AI Act (formally adopted 2024, with phased application through 2026-2027) classifies AI used in education access and assessment (admission decisions, student evaluation) as high-risk. High-risk systems require: risk-management documentation, data-governance practices, human oversight, transparency to data subjects, and conformity-assessment processes before deployment. The Act applies to EU deployments and to EU-affecting cross-border deployments. Non-EU institutions exporting student data to EU-located AI processors are also indirectly affected. Most institutions handle compliance by keeping AI advisory (human-in-the-loop) and documenting their AI-use policy formally.

Approaches vary. Some schools ban AI in academic work; some allow AI with disclosure; some integrate AI into assessment by changing the assessment design (more in-class work, more process-evidence, more oral defence). UNESCO's 2024 guidance recommends that schools develop explicit policies with student and teacher input rather than ban-by-default or allow-by-default. The most resilient approach focuses on assessment design (you cannot easily ChatGPT a live oral exam or a portfolio-defence interview) rather than detection (AI-detection tools are unreliable in practice).

Data is rapidly changing. NCES tracks AI adoption in US K-12 with surveys showing single-digit percentages in 2022 and a growing share by 2024-2026. EdSurge's annual surveys show similar growth. Anecdotally, the parent chatbot and auto-grading applications are growing fastest in 2026 because they save staff time without touching high-stakes decisions. Predictive early-warning is adopted slower because it requires institutional comfort with risk-flagging students, even with human-counsellor review. International data is patchier — UNESCO and OECD are building country-level tracking.

Five questions per UNESCO 2024 guidance and EU AI Act conformity-assessment framework: (1) What human decision is the AI advising? (2) Who reviews and can override the AI output? (3) Where is student data processed and stored? (4) What signals drove this AI decision (explainability)? (5) How is the AI evaluated for bias against protected groups? Administrators able to answer all five are ready to pilot; administrators who cannot should engage the vendor or partner to clarify before deployment.