Artificial intelligence (AI) is rapidly transforming the ESG landscape, offering powerful tools to accelerate the energy transition. AI enhances sustainability efforts by processing vast datasets, verifying emissions claims, and predicting ESG risks in real time. In Asia, regulators like the Hong Kong Monetary Authority and the Monetary Authority of Singapore are leveraging AI to combat greenwashing and improve climate-related disclosures. These capabilities can help investors and companies align more effectively with net-zero targets.
However, AI’s environmental footprint raises serious concerns. The energy-intensive nature of training and operating AI models contributes significantly to global greenhouse gas emissions—data centers alone account for 2–3% of global emissions. As AI adoption grows, so does its demand for electricity and water, potentially undermining climate goals. Moreover, AI’s “black box” nature and potential for bias complicate ESG assessments, risking misinformed decisions and eroding trust.
AI could be a game-changer for net-zero, or it can be a growing liability. Will its energy demands outweigh its climate benefits? Can we trust AI to guide sustainability decisions when its own footprint is unclear? As we race toward a greener future, how we design, govern, and deploy AI will shape the outcome.