Artificial intelligence and twice-exceptional (2e) learners in educational settings: a scoping review of an emerging evidence base (2020-2026).

Twice-exceptional (2e) students are intellectually or creatively gifted and also have one or more disabilities, and they require provision that develops talent and addresses disability at the same time. Artificial intelligence (AI) is increasingly promoted as a route to personalized instruction, and its adaptive character appears conceptually well suited to the heterogeneous profiles of 2e learners. Whether that promise has been examined empirically with this population has not been established. This scoping review asked whether and how AI technologies have been reported in educational research involving 2e learners between 2020 and the search date in 2026. Following PRISMA-ScR, a population-anchored search was conducted in ERIC in August 2026 and supplemented by hand searching of a themed journal issue and by reference checking, returning 65 records of which five were assessed at full text. Two studies met the eligibility criteria, both published in 2025 and both in the same themed journal issue: the evidence base is emerging rather than absent, but it is very small and has begun through editorial intervention rather than sustained accumulation. A further group of records sat close to the eligibility boundary and is reported in full so that the limits of the evidence are visible. Across the included studies, sample sizes are small, outcome measurement is uneven, and no study examines whether AI systems that adapt to observed performance interact with the masking that defines twice-exceptionality. An affordance-risk framework is proposed, with each proposition explicitly labeled as hypothesized rather than demonstrated, together with a research agenda for a field that is beginning rather than absent.