Current Journal of Applied Science and Technology

Artificial intelligence (AI) has moved from a peripheral technical capability to a structural feature of digital ecosystems, reorganising how platforms, data infrastructures, and institutional actors coordinate value creation across economic, social, and environmental domains. This review synthesises recent peer-reviewed literature to examine how AI technologies are reshaping digital ecosystems in ways that bear on sustainable development. The review traces four interlinked themes: the architectural transformation of digital ecosystems from modular platforms towards AI-native, data-intensive coordination structures; the enabling contribution of AI to environmental, economic, and social dimensions of the Sustainable Development Goals; the material and environmental costs embedded in AI infrastructure, including energy demand, water consumption, and electronic waste; and the governance and equity challenges that determine whether AI-enabled digital ecosystems narrow or widen existing development gaps. Evidence from agriculture, circular economy platforms, and urban systems illustrates how sector-specific applications translate general-purpose AI capability into measurable sustainability outcomes, while also exposing persistent asymmetries in access, computational capacity, and regulatory readiness between advanced and developing economies. The review finds that AI's net contribution to sustainable development is neither uniformly positive nor uniformly negative but is contingent on governance quality, infrastructure transparency, and the extent to which efficiency gains are captured within circular and human-centric organisational models. The paper concludes that digital ecosystems reshaped by AI require deliberate institutional design, coordinated environmental accounting, and inclusive access mechanisms if their transformative potential is to translate into durable sustainability gains rather than a redistribution of ecological and social costs.