AI for Everything: Opportunities, Challenges, and Responsible Use of Artificial Intelligence in School Education

AI assistance can improve a pupil’s immediate output without improving independent learning. This targeted, structured review examines school education at approximately ages 6–18, synthesizing 25 cited sources and extracting comparable design and outcome information from eight studies or reviews. Logged revision searches, DOI metadata, source decisions, and extraction records support auditability without claiming a comprehensive systematic search. Domain-specific intelligent tutoring systems and general-purpose generative AI have different evidence bases. Effects depend on comparators, outcome measures, implementation, and assessment conditions; confidence intervals and reported uncertainty are retained rather than combining incompatible results. A school evidence table distinguishes pupils from repeated observations and immediate assisted performance from verified unaided outcomes. Self-regulated learning, cognitive offloading, and scaffolding inform a proposed attempt–consult–verify–explain–fade–transfer routine. An unvalidated decision aid links developmental context, tool eligibility, supervision, and local unaided-learning evidence, complementing existing competency, child-rights, and assessment-regime frameworks. Schools should prioritize learning, inclusion, safety, and teacher responsibility, and revise or stop uses that do not meet those goals.