Creative Assignments and Who Gets Left Behind: A Systematic Review of Inclusion Readiness in Generative AI Teaching Practices in Business and Technology Higher Education

Generative artificial intelligence (GenAI) assignments are spreading rapidly in business and technology higher education, yet published accounts rarely report whether every student can take part on fair terms. This systematic review audited published GenAI assignments against the social, economic, institutional and environmental dimensions of pedagogical sustainability. Following PRISMA 2020, OpenAlex (2023–2026) was searched, 1092 peer-reviewed records were screened and 191 studies were included. Each assignment was coded for its creative family, access and fairness provisions, ethics content and assessment, and scored on a 0–5 inclusion-readiness index. An AI system served as primary coder; a human coder double-coded 30 studies and the author adjudicated all disagreements. Most assignments used GenAI as a tutor or thinking partner (52%). Provisions were scarce: 27% ensured free access, 2% offered a non-AI alternative task and 2% addressed disability. Privacy (53%) and opt-out (35%) appeared mainly as research-ethics safeguards rather than design features. Mean inclusion readiness was 1.30 of 5 (0.75 on design-only coding). Only one study in seven taught GenAI ethics, and environmental cost was taught once. Business courses favored choice and language support; technology courses favored central access. The index offers a measurable design and reporting checklist for sustainable GenAI pedagogy.