AI Driving ESG Performance: A Case Study of Geelys Mergers and Acquisitions

Under the global wave of sustainable investment,Environmental, Social and Governance disclosure quality has become a key factor in the success or failure of mergers and acquisitions. However, traditional due diligence data is fragmented and disclosed with a lag, which amplifies risk premiums. This study adopts a single case study method, taking Geely Autos cross-border mergers and acquisitions from 2017 to 2024 as an example, to systematically analyze the causal chain between artificial intelligence, Environmental, Social and Governance disclosure quality and Merger and Acquisition Performance. The research finds that AI, through a three-step closed loop of full-domain data capture, semantic alignment, and reliable output, has increased the coverage of Merger and Acquisition Performance disclosure from 78% to 99.1% and reduced the error rate from 3.9% to 0.85%. Additionally, the event window of mergers and acquisitions has significantly expanded, with positive impacts on Return on Assets and stock price volatility. The research provides theoretical guidance for enterprises and regulators.