Purpose The ability of generative artificial intelligence (AI) tools such as ChatGPT to produce convincing, human-like text has major implications for the future of corporate reporting, including sustainability reporting. As the importance of sustainability reporting continues to grow, this study aims to critically analyse the benefits and pitfalls of automated text generation and processing. Design/methodology/approach This study develops a conceptual framework to delineate the field, assess the implications and form the basis for the generation of research questions. This study uses Alvesson and Deetz’s critical framework, considering insight (a review of literature and practice in the field), critique (consideration of the influences on the production and use of non-financial information and the implications for assurers of such information) and transformative redefinition (considering the implications of generative AI for sustainability reporting and proposing a research agenda). Findings This study highlights the implications of generative AI for sustainability accounting, reporting, assurance and report usage, including the risk of AI facilitating greenwashing, and the importance of more research on the use of AI for these matters. Practical implications The paper highlights to stakeholders the implications of AI for all aspects of sustainability reporting, including accounting, reporting, assurance and usage of reports. Social implications The implications of AI need to be understood in society, which this paper facilitates. Originality/value This study critically analyses the potential use of AI for sustainability reporting, construct a conceptual framework to delineate the field and develop a research agenda.
(2024). How will AI text generation and processing impact sustainability reporting? Critical analysis, a conceptual framework and avenues for future research [journal article - articolo]. In SUSTAINABILITY ACCOUNTING, MANAGEMENT AND POLICY JOURNAL. Retrieved from https://hdl.handle.net/10446/263869
How will AI text generation and processing impact sustainability reporting? Critical analysis, a conceptual framework and avenues for future research
Molinari, Matteo
2024-01-01
Abstract
Purpose The ability of generative artificial intelligence (AI) tools such as ChatGPT to produce convincing, human-like text has major implications for the future of corporate reporting, including sustainability reporting. As the importance of sustainability reporting continues to grow, this study aims to critically analyse the benefits and pitfalls of automated text generation and processing. Design/methodology/approach This study develops a conceptual framework to delineate the field, assess the implications and form the basis for the generation of research questions. This study uses Alvesson and Deetz’s critical framework, considering insight (a review of literature and practice in the field), critique (consideration of the influences on the production and use of non-financial information and the implications for assurers of such information) and transformative redefinition (considering the implications of generative AI for sustainability reporting and proposing a research agenda). Findings This study highlights the implications of generative AI for sustainability accounting, reporting, assurance and report usage, including the risk of AI facilitating greenwashing, and the importance of more research on the use of AI for these matters. Practical implications The paper highlights to stakeholders the implications of AI for all aspects of sustainability reporting, including accounting, reporting, assurance and usage of reports. Social implications The implications of AI need to be understood in society, which this paper facilitates. Originality/value This study critically analyses the potential use of AI for sustainability reporting, construct a conceptual framework to delineate the field and develop a research agenda.File | Dimensione del file | Formato | |
---|---|---|---|
2024_De Villiers Dimes and Molinari.pdf
Solo gestori di archivio
Versione:
publisher's version - versione editoriale
Licenza:
Licenza default Aisberg
Dimensione del file
373.51 kB
Formato
Adobe PDF
|
373.51 kB | Adobe PDF | Visualizza/Apri |
Pubblicazioni consigliate
Aisberg ©2008 Servizi bibliotecari, Università degli studi di Bergamo | Terms of use/Condizioni di utilizzo