Opportunities and challenges to improve accounting and accountability of Corporate Social Responsibility with artificial intelligence: insights from scientific mapping

Abstract

This article applies bibliometric analysis as a framework to explore the potential applications of emerging artificial intelligence (AI) tools for enhancing the accounting and accountability of Corporate Social Responsibility (CSR). Bibliometric analysis mapped scientific trends and identified emerging and relevant topics related to AI, accounting/accountability, and CSR. The opportunities and challenges of AI in promoting transparency, informed decision-making, and stakeholder engagement are discussed in the context of thematic networks and strategic diagrams that illustrate the research findings. The results indicate that emerging AI technologies are still specialized and peripheral to the core research in CSR, but opportunities exist to improve CSR accounting by generating automatic and more reliable CSR reports with large language models (LLMs) and through the application of AI inspired by biological processes for optimal decision-making. Machine learning and deep learning, in turn, can be applied to understand stakeholder attitudes and for algorithmic auditing, thus promoting the engagement and responsibility of stakeholders and increasing the accountability of CSR. The study also discusses potential risks and biases that can arise when implementing AI technologies for the accounting/accountability of CSR.