Leveraging artificial intelligence and the internet of things for environmental sustainability in developing and transitioning economies

Artificial intelligence (AI) and the Internet of Things (IoT) are widely viewed as enabling technologies for environmental sustainability in developing and transitioning economies; however, their realized impact depends on readiness conditions that extend beyond technical availability. This qualitative study investigates how AI–IoT initiatives translate into environmental outcomes in Kuwait, a context characterized by advanced connectivity alongside uneven digital culture and evolving regulatory preparedness. Data were generated from twelve purposively selected expert interviews spanning government and regulatory entities, private-sector implementation (ICT and banking), higher education, and environment-related practices. The interviews were analysed through a systematic thematic procedure supported by AI-assisted qualitative coding, triangulation across analytic outputs, and an auditable coding trial. Four interrelated themes emerged: (1) structural and operational barriers to adoption, (2) socio-ethical dimensions and technology acceptance, (3) environmental and operational impacts of AI–IoT adoption, and (4) institutional readiness and governance requirements, with cross-cutting readiness dynamics shaping all four dimensions. The findings indicate that AI–IoT systems can enable real-time monitoring, resource optimization, and pro-environmental behavioral nudges; however, the impact of these systems is constrained by limited technical literacy, fragmented coordination, outdated regulations, and low sustainability awareness. The study synthesizes these mechanisms into an integrated conceptual framework and a roadmap-oriented set of implications for accelerating sustainable digital transformation aligned with national agendas such as Kuwait Vision 2035. The study outcomes suggest that a national AI-IoT sustainability governance framework should be developed. There is a need for pilot projects at the sector level for environmental monitoring, the establishment of AI-IoT support centers within public institutions and universities, professional capacity-building programs, and targeted public awareness campaigns linking smart technologies to environmental responsibility.