AI in Chemistry Education: A Thematic Narrative Review of Opportunities, Limitations, and Equity Gaps (2020–2026)

Abstract

Generative artificial intelligence (AI) has prompted rapidly growing body of scholarship on the role in chemistry education since the public release of ChatGPT in the late of 2022. This thematic narrative review synthesizes 40 English-language sources including empirical studies, curriculum reports, and stakeholder surveys, and systematic/bibliometric reviews published between 2020 and 2026, identified through a structured, author-curated search of recent chemistry-education and analytical-chemistry literature (see Methodology). Sources were coded inductively and organized into six recurring themes: AI/ML literacy as curriculum content; AI-driven tutoring, personalization, and accessibility; empirical evaluations of generative AI's chemical reasoning; stakeholder perceptions; AI's transformation of chemistry research and scientific communication; and equity, ethics, and systemic barriers. Across the reviewed literature, a recurring position though not a formal consensus is that AI should support rather than replace human instruction. Empirical evaluations consistently report that large language models generate fluent but sometimes hallucinated or subtly incorrect chemistry content, particularly for visual and multi-representational reasoning tasks. The corpus is concentrated in higher education and high-income countries, and this pattern should be interpreted as a prominent tendency in the reviewed literature rather than a field-wide finding. Priorities for chemistry educators include critical AI literacy instruction, assessment redesign, teacher professional development, and explicit attention to equity.