Artificial intelligence and human intelligence in addressing climate change: a systematic literature review of approaches, innovations, emerging perspectives, and thematic analysis, Prof. Joseph Ntayi, James Mubangizi

Professor Joseph M. Ntayi
Faculty of Economics, Energy and Management Sciences, Makerere University Business School
Makerere University
Kampala
Uganda
ORCID:
James Mubangizi
Faculty of Economics, Energy and Management Sciences, Makerere University Business School
Makerere University
Kampala
Uganda
ORCID: 0009-0000-3471-806X

Purpose: This study presents a systematic literature review of how Artificial Intelligence (AI) and Human Intelligence (HI) are applied in addressing climate change, with a focus on key approaches, innovations, and emerging perspectives.
Methodology: The study reviewed 43 peer-reviewed articles and reports published between January 2015 and December 2025, following PRISMA and SALSA guidelines. Data were sourced from ScienceDirect, Taylor & Francis, Emerald, Google Scholar, and Google general searches. A thematic analysis was employed to synthesize the findings.
Findings: The review identifies diverse AI and HI approaches, including machine and deep learning, remote sensing, expert knowledge and scientific assessment, indigenous and local knowledge systems, policy, governance and institutional approaches, and Hybrid AI–HI Approaches. Key innovations include advanced decision-support, human-in-the-loop, participatory & collaborative, socio-technical & governance innovations. Emerging perspectives emphasize human-centered and ethical, equity, inclusion, and justice, interdisciplinary and systems, and adaptive and future-oriented perspectives. This study underscores that no single approach can fully address the complexity of climate change, emphasizing the need for integrated AI–HI approaches. Four critical knowledge gaps were identified, particularly regarding empirical evidence, integration of indigenous, local, and context-specific knowledge, interdisciplinary collaboration, and limited theory development.
Originality: This study offers a comprehensive thematic synthesis of AI–HI integration in climate change research, offering insights for researchers, policymakers, and industry stakeholders, and identifying priority areas for future research and practice
Keywords: Artificial Intelligence; Human Intelligence; Climate Change; Human–AI Integration; Systematic Literature Review.