AI-powered information and Big Data: current regulations and ways forward in IFRS reporting

Abstract

PurposeWith the help of “self-learning” algorithms and high computing power, companies are transforming Big Data into artificial intelligence (AI)-powered information and gaining economic benefits. AI-powered information and Big Data (simply data henceforth) have quickly become some of the most important strategic resources in the global economy. However, their value is not (yet) formally recognized in financial statements, which leads to a growing gap between book and market values and thus limited decision usefulness of the underlying financial statements. The objective of this paper is to identify ways in which the value of data can be reported to improve decision usefulness.Design/methodology/approachBased on the authors' experience as both long-term practitioners and theoretical accounting scholars, the authors conceptualize and draw up a potential data value chain and show the transformation from raw Big Data to business-relevant AI-powered information during its process.FindingsAnalyzing current International Financial Reporting Standards (IFRS) regulations and their applicability, the authors show that current regulations are insufficient to provide useful information on the value of data. Following this, the authors propose a Framework for AI-powered Information and Big Data (FAIIBD) Reporting. This framework also provides insights on the (good) governance of data with the purpose of increasing decision usefulness and connecting to existing frameworks even further. In the conclusion, the authors raise questions concerning this framework that may be worthy of discussion in the scholarly community.Research limitations/implicationsScholars and practitioners alike are invited to follow up on the conceptual framework from many perspectives.Practical implicationsThe framework can serve as a guide towards a better understanding of how to recognize and report AI-powered information and by that (a) limit the valuation gap between book and market value and (b) enhance decision usefulness of financial reporting.Originality/valueThis article proposes a conceptual framework in IFRS to regulators to better deal with the value of AI-powered information and improve the good governance of (Big)data.

The AI ESG protocol: Evaluating and disclosing the environment, social, and governance implications of artificial intelligence capabilities, assets, and activities

“…It is also worth noting that there is a lot of research on how AI can be used in ways relevant to the world of ESG, for example in accounting (Bose & Bhattacharjee, 2022), in generating ESG ratings (Crona & Sunsdström, 2023), and for addressing the need to find a way to properly value data and AI capabilities in financial reporting (Leitner‐Hanetseder & Lehner, 2022). However, the AI ESG protocol here developed focuses on providing a method for evaluating and disclosing the ESG related impacts of using AI, and these other areas of AI use are consequently not directly relevant.…”

“…These relate to how a company, for example, develops products where its development capabilities are used to provide customers with new ways to utilize their data in order to optimize various processes. AI and data have become key enablers of the digital transformation (Holmström, 2022;Sivarajah et al, 2017;Verhoef et al, 2021) as they impact a company's growth and capacity for innovation and value generation (Leitner-Hanetseder & Lehner, 2022;Wamba-Taguimdje et al, 2020). Being able to communicate technology related soft assets to investors and other stakeholders is imperative for allowing markets to correctly value an entity and for enabling good governance (Leitner-Hanetseder & Lehner, 2022).…”

“…AI and data have become key enablers of the digital transformation (Holmström, 2022; Sivarajah et al, 2017; Verhoef et al, 2021) as they impact a company's growth and capacity for innovation and value generation (Leitner‐Hanetseder & Lehner, 2022; Wamba‐Taguimdje et al, 2020). Being able to communicate technology related soft assets to investors and other stakeholders is imperative for allowing markets to correctly value an entity and for enabling good governance (Leitner‐Hanetseder & Lehner, 2022). Since AI and data are intimately related to a company's environment, social, and governance (ESG) performance due to the impacts of data‐based AI systems on both people and the natural world—through, for example, biased and discriminatory systems or the carbon footprint of training algorithms (Crawford, 2021)—understanding the ESG related risks and impacts of these technologies is consequently crucial for internal decision‐makers, markets, and other stakeholders.…”

The digitalization of sustainability reporting processes: A conceptual framework

“…Integrating digital tools in sustainability reporting processes should represent an effective way to avoid some of the main issues identified by practitioners and policymakers about the lack of comparability and reliability (Leitner‐Hanetseder & Lehner, 2022). However, despite the increasing awareness of the need to digitalize sustainability information, only a few studies have considered the enabling role covered by digital transformation on sustainability reporting practices (Lombardi & Secundo, 2020; Schmitz & Leoni, 2019).…”