The global push toward environmental, social, and governance (ESG) transparency is compelling corporations to evolve beyond conventional financial accounting into more integrated, sustainability-centric reporting systems. Traditional reporting frameworks often fail to capture the dynamic, multi-dimensional nature of ESG impacts, leading to fragmented disclosures and delayed insights. Harnessing Big Data and Artificial Intelligence (AI) offers a transformative pathway to revolutionize sustainability accounting by delivering real-time, high-resolution, and predictive insights into corporate performance across financial and non-financial dimensions. Big Data enables the continuous aggregation of diverse datasets from enterprise systems, supply chains, IoT sensors, regulatory filings, and social media. These data streams, when processed through AI-powered platforms, generate actionable intelligence that enhances ESG measurement accuracy, streamlines reporting, and uncovers material risks and opportunities. AI models can automate the classification of sustainability metrics, detect anomalies in disclosures, and forecast ESG trends, significantly reducing reporting lag and improving data integrity. Furthermore, AI supports dynamic integrated reporting by aligning sustainability data with financial KPIs, enabling corporations to produce cohesive narratives that reflect long-term value creation and stakeholder impacts. Emerging regulatory frameworks, such as the International Sustainability Standards Board (ISSB) guidelines, are accelerating the need for such intelligent reporting systems. This paper examines how leading firms are embedding AI and Big Data into their sustainability accounting functions, discusses implementation challenges such as data governance and model transparency, and highlights the potential of these technologies to shape the next generation of accountable and adaptive corporate reporting.