Natural capital represents the stock of natural resources and ecosystems that sustain human life and economic activity by providing essential ecosystemic services such as carbon sequestration, water purification, soil fertility, and biodiversity preservation. The degradation of these resources poses a significant challenge to long-term sustainability, driving global initiatives such as the United Nations’ System of Environmental-Economic Accounting (SEEA) and the Sustainable Development Goal 15 (SDG 15). While SEEA provides a structured framework for integrating natural capital into economic decision-making, its implementation faces barriers related to data availability, ecosystem valuation, and regulatory complexity. In response, Artificial Intelligence (AI), particularly Large Language Models (LLMs) and Computer Vision (CV), has emerged as a transformative tool to enhance environmental accounting and natural capital management. This paper explores the integration of AI-driven technologies in natural capital accounting, examining both opportunities and challenges in leveraging LLMs and CV for enhancing environmental governance, optimizing resource management, and data-driven decisions. While AI presents unprecedented potential for supporting corporate and governmental contributions to SDG 15, its effective implementation depends on data quality, algorithmic transparency, and ethical governance frameworks. A multidisciplinary approach is essential to ensure that AI serves as a reliable tool for achieving sustainable ecosystem management. Ultimately, the synergy between AI, SEEA methodologies, and advanced ecosystem modelling represents a scalable, science-driven approach to conservation, redefining the role of businesses, policymakers, and international institutions in global sustainability efforts.