IDLab Seminar: AI Against Climate Risks
On January 23, 2026, a scientific seminar was held at the International Laboratory of Intangible-driven Economy (IDLab). During the seminar, laboratory researcher Michael Appiah presented a report on the role of artificial intelligence and digitalization in mitigating climate risks. The study addressed whether modern technologies can help countries adapt to the consequences of climate change.
The research was based on data from 22 countries worldwide, including OECD members, BRICS nations, and states in the MENA region — areas where AI technology adoption is particularly active. The authors analyzed how the development of artificial intelligence and digital infrastructure correlates with national resilience to climate threats.
The level of AI adoption was assessed using industrial robot deployment data collected by the International Federation of Robotics. Digitalization was measured through a composite index accounting for access to the internet, mobile communications, and broadband networks. Climate resilience was evaluated using the ND-GAIN index, which reflects both a country's exposure to climate risks and its adaptive capacity.
The findings revealed a notable distinction between the effects of AI and general digitalization. Modeling demonstrated that AI adoption consistently and statistically significantly reduces countries' climate vulnerability. By contrast, digitalization alone — without active AI utilization — does not exert a discernible impact on mitigating climate risks. AI remains an effective resilience-building tool even across varying levels of institutional quality and proves especially impactful in countries with high baseline climate vulnerability.
During the discussion, seminar participants examined the study's methodological limitations and explored alternative approaches to measuring digitalization and AI adoption levels. According to the organizers, the comments and suggestions raised may serve as a foundation for further refinement of the research and deeper analytical exploration.
