Artificial Intelligence Application in sustainability reporting: A Comprehensive Literature Review

In recent years, there has been an increasing pressure from stakeholders and regulators for accountability and thus, transparency has been placed as a cardinal corporate responsibility. However, with the technological rapid evolution, rise of data quantity, complexity, ever changing standards as well as regulations and normative following by the risk of greenwashing, conventional or traditional methods often struggle to address those challenges. In response, this structured literature review is important as it examines the transformative potential of AI (AI) in the domain of sustainability reporting. The thesis addresses challenges in the sustainability reporting domain by integrating AI technologies to enable the organizations to enhance the accuracy and the integrity of sustainability reporting. As mentioned previously, despite the rapid development of AI critical gaps persist in understanding how AI impacts practical applications, alignment with regulations, auditability, and ethical considerations within ESG frameworks.. This structured literature review (SLR) explores the intersection of AI and sustainability reporting, delving into the definitions, background, and implications of this synergy. The SLR begins by defining AI, drawing on the Organisation for Economic Co-operation and Development (OECD) definition, and sustainability reporting, highlighting its role in communicating a company's sustainability journey. It then transitions into the context of sustainability reporting within the legislative landscape, discussing the evolution from voluntary to mandatory practices and the impact of digital technologies on this transformation. The benefits of AI in sustainability reporting are thoroughly examined, including improved efficiency, accuracy, and predictive analytics capabilities asAI's role in aligning with Sustainable Development Goals (SDGs) and addressing global sustainability challenges is underscored, demonstrating its potential to drive positive change. Conversely, the challenges associated with AI implementation in sustainability reporting are critically analyzed. Issues such as data privacy, model complexity, ethical considerations, and stakeholder perspectives are explored, emphasizing the need for a nuanced understanding of AI's role in this evolving field. A significant focus is placed on 'digital sustainability,' a paradigm where the convergence of sustainability and digital transformation is illuminated. The review discusses the emergence of this concept and its implications for the future of corporate responsibility and technological prowess. Best practices for integrating AI into sustainability reporting are outlined, leveraging interdisciplinary research to guide ethical, stakeholder-centric reporting. The review synthesizes these findings, contemplating the implications for organizations and the broader impact on authentic sustainability practices. The review concludes by summarizing the key insights, proposing future research trajectories, and reflecting on the thesis's contribution to the ongoing discourse on AI and sustainability reporting. It anticipates outcomes that include identifying trends, patterns, and inconsistencies in the existing literature, thereby guiding future research and contributing to the dynamic and evolving field.