AI-Powered Digital Transformation in Mathematics Education as a Strategic Business Ecosystem: A Systematic Review of Governance, Capability and Equity Conditions

Source abstract

This systematic review examines artificial intelligence (AI)-powered digital transformation in mathematics education as a strategic business ecosystem issue rather than only a classroom technology concern. The objective is to synthesise how AI-supported pedagogies create educational value, what ecosystem risks accompany adoption, and which organisational capabilities and governance conditions enable responsible implementation. Guided by PRISMA 2020 principles, peer-reviewed empirical and conceptual studies published between 2018 and 2025 were identified from Scopus, Web of Science, ERIC, Education Source and Google Scholar. A total of 3,241 records were initially retrieved; after duplicate removal, screening and full-text eligibility assessment, 203 studies were included for structured extraction, quality appraisal and thematic synthesis. The evidence was analysed through a business ecosystem lens focusing on value co-creation, stakeholder interdependence, digital governance, teacher capability, infrastructure readiness and equity. The findings show that AI tools can strengthen adaptive practice, formative feedback, diagnostic analytics, multimodal representation and teacher decision-making when they are embedded in coherent institutional strategies. However, strategic value is weakened by digital inequality, data privacy risks, algorithmic opacity, cognitive offloading, platform dependence, weak curriculum alignment and insufficient teacher capability. The study contributes an ecosystem strategy framework that positions AI as a pedagogical and organisational mediator within a network of learners, teachers, institutions, technology providers, policy bodies, infrastructure actors and communities. It concludes that AI adoption in mathematics education should be strategy-led, ethically governed and capability-driven. Sustainable value creation requires inclusive infrastructure, teacher professional development, data governance, assessment redesign, transparent procurement and partnerships that protect educational equity while enabling innovation in resource-constrained and digitally uneven contexts.