Determinants of Ethical and Scalable AI for the Sustainable Development Goals: A Qualitative Framework from the Global South
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Artificial Intelligence (AI) is poised to aid in implementing the United Nations Sustainable Development Goals (SDGs), especially in Low- and Middle-Income Countries (LMICs) where developmental challenges are most evident. Yet the ethical, logistical, and governance challenges of applying AI in these settings remain underexplored. This research examines the factors that enable the scalable and ethically responsible deployment of AI in education, healthcare, and clean energy, contributing to SDG achievement. It also examines the changing nature of accountability, assurance and transparency in the sustainability reporting systems with the adoption of AI. Data collection was based on inductive exploratory design whereby semi-structured interviews were conducted on 37 actors (AI developers, policymakers, and community representatives) in five countries (India, Kenya, Bangladesh, Ghana and the Philippines). Thematic analysis identified four major themes influencing AI adoption: ethical concerns (e.g., bias, transparency), adoption barriers (e.g., infrastructure gaps, digital illiteracy), success enablers (e.g., institutional capacity, community involvement), and governance bottlenecks (e.g., lack of oversight, policy fragmentation). The findings, interpreted through accountability and assurance theory, show how ethical design, institutional readiness, and governance quality jointly determine the reliability and legitimacy of AI-driven sustainability data. Based on these insights, the paper develops a conceptual model for context-sensitive and ethically sound AI systems. The framework serves as a diagnostic and prescriptive tool for inclusive policy design, stakeholder engagement, and capacity-building. By extending accounting theory into the digital domain, it conceptualizes AI as both a technological and ethical actor within sustainability accounting systems, reinforcing transparency, comparability, and stakeholder trust.
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