Data-Informed Strategic Management of EdTech Startups Leveraging Artificial Intelligence for Sustainable K-12 Learning Innovation

Abstract

The rapid growth of educational technology (EdTech) startups has reshaped K-12 learning ecosystems, yet many ventures struggle to achieve long-term sustainability, scalability, and pedagogical impact. This review paper examines how datainformed strategic management, supported by artificial intelligence (AI), can enable EdTech startups to drive sustainable K12 learning innovation while balancing educational quality, financial viability, and ethical responsibility. The study synthesizes interdisciplinary literature spanning educational data analytics, AI-driven personalization, strategic management, and learning sciences to evaluate how data governance, predictive analytics, and adaptive intelligence inform decision-making across product design, curriculum alignment, user engagement, and organizational growth. The review highlights the strategic role of AI in optimizing instructional delivery through personalized learning pathways, early learning risk detection, and performance monitoring, while also supporting startup-level functions such as market positioning, resource allocation, and impact assessment. Particular attention is given to sustainability dimensions, including equitable access, data privacy, algorithmic transparency, teacher augmentation, and alignment with national education standards. The paper further identifies structural and contextual challenges faced by EdTech startups, such as data fragmentation, regulatory uncertainty, infrastructure gaps, and resistance to AI-enabled instructional change. By integrating strategic management theory with AIenabled educational innovation, this review proposes a conceptual framework linking data maturity, AI capability, and sustainable value creation in K-12 EdTech ventures. The findings offer actionable insights for founders, policymakers, investors, and educators seeking to design resilient, ethical, and learner-centered digital education solutions. The paper concludes by outlining future research directions for advancing evidence-based, AI-driven EdTech ecosystems that support inclusive and sustainable K-12 education.