Theophanis C. Stratopoulos

The integration of generative AI into accounting and finance practice has intensified a longstanding professional obligation to exercise independent judgment and take responsibility for analytical conclusions. Large language models are prone to producing plausible but incorrect outputs, yet professionals remain accountable for decisions informed by those outputs. This accountability creates an educational challenge: preparing graduates to critically evaluate AIgenerated analyses, identify errors, and take professional responsibility for their conclusions. The challenge is compounded by the verification paradox, in which students are expected to evaluate AI-generated content concerning material they are still mastering. This paper presents an AIassisted pedagogical platform designed to address this paradox by asking students to evaluate AI-generated reports containing deliberately seeded errors, an approach we term adversarial pedagogy. Using a design science research framework, the paper examines the platform's design principles, pilot evaluation, and implications for accounting education.

As technological advancements reshape the accounting profession, the School of Accounting and Finance (SAF) at the University of Waterloo integrated Data Analytics and Emerging Technologies (AET) into its curriculum. This initiative equips students with essential and advanced AET skills, employing tools like spreadsheets, Tableau, Alteryx, R, Python, RPA, and blockchain. This paper builds on our experiences to provide a framework to help educators integrate AET into the accounting program at their institutions. We outline the strategic development and implementation challenges experienced in developing our program. JEL Classifications: M41.

This study investigates the link between a firm's IT Capability and its Environmental, Social, and Governance (ESG) performance, addressing the empirical gap concerning the impact of technology investments on ESG outcomes. There are two competing views regarding this link. While some argue that technology investments enhance ESG performance, others highlight potential drawbacks, such as the rebound effect where increased overall energy use offsets anticipated energy savings. The research analyzes a dataset of 14,075 firm-year observations from 2010 to 2020, using a composite index to measure IT Capability, including the expertise of IT executives, ERP system adoption rate, IT staff quality, and IT spending. ESG performance is assessed with Refinitiv Eikon scores across environmental, social, and governance dimensions. Results show a positive association between IT Capability and ESG performance, especially in environmental performance and subcategories such as emission reduction and sustainable resource usage. These insights are important for managers and investors, highlighting that enhancing IT Capability can boost ESG and economic performance. The study underscores the strategic importance of IT in achieving broader ESG goals and encourages further exploration into how IT affects ESG practices.

This paper provides a review of recent publications and working papers on ChatGPT and related Large Language Models (LLMs) in accounting and finance. The aim is to understand the current state of research in these two areas and identify potential research opportunities for future inquiry. We identify three common themes from these earlier studies. The first theme focuses on applications of ChatGPT and LLMs in various fields of accounting and finance. The second theme utilizes ChatGPT and LLMs as a new research tool by leveraging their capabilities such as classification, summarization, and text generation. The third theme investigates implications of LLM adoption for accounting and finance professionals, as well as for various organizations and sectors. While these earlier studies provide valuable insights, they leave many important questions unanswered or partially addressed. We propose venues for further exploration and provide technical guidance for researchers seeking to employ ChatGPT and related LLMs as a tool for their research.

Studies which examine the effect of IT on firm performance make the implicit assumption that the choice of industry classification (e.g., SIC instead of NAICS) and the level of aggregation (e.g., 2-digit SIC instead of 4-digit SIC) is unlikely to affect the results. Given that practically none of the studies in our literature review has tested the robustness of their results to an alternative industry classification method, we do not know whether this choice matters (i.e., we don’t know whether the evidence generated from this stream of research is robust). To answer this question, we replicated three studies (Bharadwaj 2000; Chae et al. 2014; Santhanam and Hartono 2003) and found that results are likely to differ if we change the classification method and/or the level of aggregation within a given industry classification method. We encourage IT researchers to replicate prior studies to assess the sensitivity of their results to such choices as well as encouraging future studies to consider implementing robustness checks. The need to consider such robustness checks spans all fields (e.g., accounting, strategic management, and marketing) that use statistical analysis which requires control for role of industry.

SYNOPSIS: Several studies have pointed to the transformative effects of blockchain on a wide spectrum of firms, industries, and professions. Despite the arguable consensus within the business community that blockchain will have a real impact on the way firms do business, views diverge when it comes to the timing of diffusion (i.e., when blockchain will achieve mass adoption). We propose that information gathering helps potential adopters form expectations regarding payoffs from blockchain adoption. Information-gathering activities and the resulting information sources, such as web searches, news articles, book titles, and corporate disclosures, can proxy the expectations of potential adopters. Corporate disclosures directly reflect firms' expectations and interests in the new technology. We leverage the corporate disclosure data from the SEC Edgar database to identify the current stage of blockchain adoption. Our analysis shows that while blockchain adoption is still nascent, the focus has been shifting from cryptocurrencies to business applications. Data Availability: Data are available from public sources cited in the text. JEL Classifications: M15.

The objective of these teaching notes is to provide an outline for offering blockchain related foundational knowledge to accounting students so they can evaluate and prepare for the effect of blockchain on the accounting profession. The approach is driven by the following principle: Given that accounting students do not want to become programmers or cryptographers, what is the essential blockchain knowledge that they need to know? Based on my own teaching and research experience, I propose and explain how I use a combination of storytelling and scaffolding approach to focus on the delivery of the following topics: (1) why study blockchain? (2) general foundational knowledge (i.e., element of complete transactions and double spending), (3) interactive exercises to explain technical knowledge on topics such as hashing and proof-of-work (mining), and (4) blockchain implementation in a supply chain setting.

We introduce a data analytics course that accounting students complete during the first semester of their undergraduate program at the School of Accounting and Finance at the University of Waterloo. The course positions analytics as equally important to their future professional success as financial accounting, basic business concepts, and economics. We offer our approach, which could be adopted by any business school that currently requires an introductory course in mathematics for business. Our choices regarding content and delivery method were driven by our aim to help students develop a data analytics mindset from the beginning and in parallel with building their accounting knowledge. We wanted to build on industry standard tools (i.e., spreadsheets) but at the same time to prepare students for a changing environment that is not hindered by data size or software capabilities and emphasize the importance of tool ambidexterity. This means the need to create future professionals who are versatile and capable to switch/leverage the most appropriate tool for each project.