<p>Climate-induced heat stress has emerged as a serious global challenge due to rising temperatures, frequent heatwaves, and rapid urbanisation. These changes pose significant risks to human health, urban infrastructure, and occupational safety. In response, technological innovations and artificial intelligence (AI)-driven approaches are increasingly being developed to monitor, predict, and mitigate heat-related impacts. This study presents a comprehensive bibliometric assessment of global research trends on technological and AI-driven strategies for mitigating climate-induced heat stress over 20 years (2005–2025). Bibliographic data were analysed using bibliometric techniques to examine publication growth, keyword evolution, thematic structures, leading countries, and major publication sources. The results show a slow growth in publications before 2015, followed by a sharp increase after 2018, with rapid expansion observed during 2020–2025. Machine learning and AI-based methods emerge as dominant analytical tools, widely applied in heatwave forecasting, urban heat island assessment, thermal comfort analysis, and early warning systems. Urban environments, public health, and buildings are identified as key application areas. Research output is largely concentrated in a few developed countries, while many heat-vulnerable regions remain underrepresented. The findings also indicate growing integration of bioclimatic design, green buildings, and nature-based solutions. Overall, this study highlights key advances, research gaps, and future directions for developing effective, equitable, and climate-resilient heat stress mitigation strategies.</p>