Artificial Intelligence in Climate Finance: Enhancing Green Investment, Carbon Risk Assessment and Capital Allocation

Abstract

Artificial intelligence (AI) has increasingly become a transformative tool in climate finance,
enabling firms to enhance green investment strategies, assess carbon risk more accurately, and
optimize capital allocation. This study investigated the role of AI in promoting sustainable finance
by examining its impact on investment decisions, risk mitigation, and ESG evaluation. Data were
collected from multiple firms employing AI-based analytics to support green financial initiatives,
and analysed using descriptive statistics, frequency distributions, and comparative evaluation of
AI adoption levels, green investment allocation, and carbon risk assessment accuracy. The
findings indicated that firms with higher AI integration achieved more precise risk assessments,
allocated capital more efficiently to sustainable projects, and demonstrated improved resilience
to climate-related financial uncertainties. Despite these benefits, challenges were identified,
including limitations in data quality, algorithmic bias, disparities in institutional readiness, and
environmental impacts associated with energy-intensive AI computations. The study also
highlighted that effective AI adoption required robust data governance, standardized ESG
reporting frameworks, and employee training to maximize decision-making efficiency.
Recommendations emphasized ethical implementation, regulatory guidance, and the integration
of AI technologies with sustainability objectives to ensure both financial and environmental gains.
Future research should explore cross-sectoral adoption, longitudinal impacts, and advanced AI
methods such as reinforcement learning and blockchain-enabled analytics. Overall, the study
demonstrated that AI not only strengthens analytical capabilities but also fosters strategic
alignment between financial performance and environmental sustainability.