Empowering Climate Risk Management Through Generative AI Innovation

Michail Makris (), Andreas Fousteris () and Sotirios Bersimis ()
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Michail Makris: University of Piraeus, Department of Business Administration
Andreas Fousteris: University of Piraeus, Department of Business Administration
Sotirios Bersimis: University of Piraeus, Department of Business Administration

A chapter in Advanced Data Analytics, Machine Learning and AI in Business, 2026, pp 195-208 from Springer

Abstract: Abstract Generative AI represents a major leap in artificial intelligence, enabling systems to autonomously generate creative outputs. As organizations face increasing pressure to meet environmental goals and comply with evolving climate disclosure standards, this paper investigates the expanding role of Generative AI in enhancing corporate environmental performance, improving climate data quality, and streamlining regulatory reporting. In particular, Large Language Models (LLMs) demonstrate a unique ability to process and synthesize vast amounts of unstructured data, offering critical solutions. The study highlights how Generative AI can standardize fragmented climate reporting, bridge data gaps among SMEs, and improve the accuracy of risk assessments by reducing reliance on biased or inconsistent self-reported data. Additionally, the paper outlines future research directions and technological considerations, including ethical deployment and energy efficiency.

Keywords: Generative AI; Corporate Sustainability; Climate Risk Management; Large Language Models (LLMs); ESG Reporting; Climate Change Mitigation; Regulatory Compliance (search for similar items in EconPapers)
Date: 2026
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DOI: 10.1007/978-3-032-23493-3_12

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