Unleashing efficiency and insights: Exploring the potential applications and challenges of ChatGPT in accounting

Purpose This study aims to explore ChatGPT in the context of the UK higher education (HE) and accountancy profession. Design/methodology/approach Narrative research that applies deductive thematic analysis to investigate secondary data produced by the UK HE governing bodies, the ancient UK universities, accountancy bodies and BIG4s. Findings Discussions held by the governing bodies of HE in the UK follow the advice found in the literature on how to acknowledge contributions from artificial intelligence. However, these discussions are informal. Universities provide guidance on the use of ChatGPT; however, these documents differ, compromising a consistent approach across institutions. Similarly, accountancy researchers lack uniform guidance. This is concerning because the data analysis indicates that ChatGPT’s limitations may have a detrimental impact on compliance with the UK Concordat to support research integrity. Moreover, accountancy bodies are predicting major changes in the accountancy profession due to automation, which will potentially change the job market and the content of qualification examinations. BIG4s have begun automating, with some negative impacts already evident. Thus, the field should be ready for future challenges. Originality/value This study explores ChatGPT in the context of the UK HE and accountancy profession. It provides a detailed analysis of the risks and opportunities associated with the use of ChatGPG, while also providing suggestions for risk mitigation to assist accountancy students, researchers and practitioners.

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Artificial intelligence as an enabler for entrepreneurial finance: a practical guide to AI-driven video pitch evaluation for entrepreneurs and investors

Giuggioli,

Pellegrini,

Giannone

2024

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PurposeWhile different attempts have been made to use artificial intelligence (AI) to codify communicative behaviors and analyze startups’ video presentations in relation to crowdfunding projects, less is known about other forms of access to entrepreneurial finance, such as video pitches for candidacies into startup accelerators and incubators. This research seeks to demonstrate how AI can enable the startup selection process for both entrepreneurs and investors in terms of video pitch evaluation.Design/methodology/approachAn AI startup (Speechannel) was used to predict the outcomes of startup video presentations by analyzing text, audio, and video data from 294 video pitches sent to a leading European startup accelerator (LUISS EnLabs). 7 investors were also interviewed in Silicon Valley to establish the differences between humans and machines.FindingsThis research proves that AI has profound implications with regards to the decision-making process related to fundraising and, in particular, the video pitches of startup accelerators and incubators. Successful entrepreneurs are confident (but not overconfident), engaging in terms of speaking quickly (but also clearly), and emotional (but not overemotional).Practical implicationsThis study not only fills the existing research gap but also provides a practical guide on AI-driven video pitch evaluation for entrepreneurs and investors, reshaping the landscape of entrepreneurial finance thanks to AI. On the one hand, entrepreneurs could use this knowledge to modify their behaviors, enabling them to increase their likelihood of being financially backed. On the other hand, investors could use these insights to better rationalize their funding decisions, enabling them to select the most promising startups.Originality/valueThis paper makes a significant contribution by bridging the gap between theoretical research and the practical application of AI in entrepreneurial finance, marking a notable advancement in this field. At a theoretical level, it contributes to research on managerial decision-making processes – particularly those related to the analysis of video presentations in a fundraising context. At a practical level, it offers a model that we called the “AI-enabled video pitch evaluation”, which is used to extract features from the video pitches of startup accelerators and incubators and predict an entrepreneurial project’s success.

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Unleashing efficiency and insights: Exploring the potential applications and challenges of ChatGPT in accounting

Cited by 7 publications

References 36 publications

ChatGPT’s crystal ring: simulating auditors’ use of machine learning in stock price prediction

ChatGPT’s crystal ring: simulating auditors’ use of machine learning in stock price prediction

ChatGPT: reflections from the UK higher education institutions, accountancy bodies and BIG4s

Artificial intelligence as an enabler for entrepreneurial finance: a practical guide to AI-driven video pitch evaluation for entrepreneurs and investors

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