The aim of this workshop is to bring together Accounting Information Systems (AIS) researchers and representatives from accounting firms and organizations to have a conversation on Al related opportunities and challenges for accounting practice and research.
Registration Information:
- The workshop will be held on Wednesday, December 7, 12:00 – 15:00 pm (EST).
- It will be offered through the University of Waterloo over Zoom.
- Advance registration is required. If you are a member of one of the groups listed below and qualify for a discount, please send an emailadvising which group you belong to so we can send you the proper code.
- The registration fee is $50 but discounts are available as follows:
- 100% discount to students
- 100% discount to members of the AAA AIS Section and AAA SET Section
- 50% discount to ISACA Toronto Chapter members, IIA Canada/Toronto Chapter members and CPA Canada members.
This workshop qualifies for 3 hrs of CPD credit.
Co-sponsored by the AIS section of the AAA and the UW CISA
Workshop Description and Objectives
Workshop Description and Objectives
The aim of the workshop is to bring together Accounting Information Systems (AIS) researchers, and representatives from leading accounting firms to have a conversation on the implications of AI for the accounting profession and related research opportunities. Through this interaction we hope to achieve the following objectives:
- Provide an opportunity for accounting professionals to articulate some of the issues/challenges they face.
- Provide an opportunity to researchers interested in these topics/ideas to start exploring the possibility of collaboration with practitioners on addressing these research questions.
- Convert these research topics/ideas into research papers to be published in JIS on the implications of AI adoption for the accounting profession to expand our understanding of this growing area of activity.
Background:
Anecdotal and empirical evidence seem to indicate that growing adoption of artificial intelligence (AI) within accounting firms and/or accounting departments leads to improvements in efficiency (better or more services with fewer accounting professionals). For example, in an interview with the Wall Street Journal, the leader of Microsoft's Modern Finance project explained that Microsoft leverages a host of technologies, including AI to keep a tight lid on finance headcount. A study on the effect of AI on audit quality and efficiency reports that “… A one-standard-deviation increase in the share of AI workers over the past three years predicts a decrease of 5.7% in the number of junior accounting employees three years later and an even larger decrease of 11.8% four years later (Fedyk et al. 2021, 37). While the percentage of AI workers among all employees in the large six audit firms is relatively low - it has been around half percent or less - there is a clear upward trend (Fedyk et al. 2021). If this trend continues and AI workers were to continue to grow, would this signal the beginning of an era of diminishing demand for new accounting professionals and/or a shift in the required skill set of new accounting employees? An article in the Accounting Today used the analogy of the uncanny valley - a term for the feelings of eeriness and revulsion in humans when confronted with humanlike machines — to describe how accounting professionals feel about AI enabled process automations. However, Prof. Brynjolfsson in his testimony to the US congress and a recent article (2019; 2022) argues that there is a better alternative. When AI is focused on augmenting humans, rather than replacing humans, it can lead to new capabilities, new products, and new services.
Structure-Timeline of the Workshop:
Wednesday, December 7, 12:00 - 15:00 pm (EST Canada and US)
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12:00-12:10 |
Welcome by Efrim Boritz on behalf of UWCISA and JIS – Workshop introduction by Theo Stratopoulos |
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12:10-13:10 |
Industry panel – presentations and individual Q&A
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13:10-13:30 |
Open Q&A for all members of the industry panel |
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13:30-13:40 |
Break |
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13:40-14:30 |
Journalist/Academic panel – presentations and individual Q&A
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14:30-14:40 |
Open Q&A for all members of the Journalist/Academic panel |
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14:40-14:50 |
Open Q&A period for all panelists |
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14:50-15:00 |
Closing remarks |
University of Waterloo Senior Co-Editors of the Journal of Information Systems
CPA Ontario Chair in Accounting
Executive Director, UW CISA
jeboritz@uwaterloo.ca
PricewaterhouseCoopers Chair of Information Systems
tstratopoulos@uwaterloo.ca
Industry Panel:
Samantha Bowling, CPA CFE CGMA
Samantha has been a partner in Garbelman Winslow in Maryland, USA since 2005, having joined the firm back in 1993. In 2018 she won the CPA.com Innovative Practitioner of the Year Award for innovative use of Artificial Intelligence (AI) and in 2019 was named by the American Institute of CPAs (AICPA) as one of the Most Powerful Women in Accounting. She was Chair of the Maryland Association of CPAs (MACPA) from July 2018-2019 and has been appointed to the AICPA Auditing Standards Board (ASB) for 2021-2024. She is the current Chair of the ASB’s inaugural Technology Working Group Task Force.
Samantha and her team at Garbelman Winslow have successfully integrated artificial intelligence in auditing for small businesses. Using an external AI platform, the firm has improved its audit process and helped reduce the risk of material misstatements for its clients.
https://twitter.com/@sbowling.cpa
https://linkedin.com/samanthabowlingcpa
Nat D’Ercole, Deloitte & Omnia AI Data Transformation and Ecosystems & Alliances Leader
Nat is a trusted advisor to the CFO and CIO in the modernization of analytics and information management capabilities. He provides executable advice to modernize information systems and processes for decision-making and compliance. He excels in leading transformative programs grounded in financial data management intersected with operations.
Over his 27 year career, his clients include CFOs from global and mid-market enterprises in financial services, media and entertainment, manufacturing and public sector in Canada, US, UK and the Caribbean. Nat's strong network and experience enable him to add exceptional value in any business analytics modernization project while serving clients. His specializations includes analytics strategy, selections, operating models, financial automation and control, advanced budgeting/forecasting, data governance, master data management, financial and management reporting, complex consolidations and self-serve analytics across leading and emerging big data technology solutions.
Nat is an active board member of the Schulich Masters of Business Analytics program.
Annie Veillet, Partner, One Analytics, PwC Canada
Annie leads the National Advanced Data Analytics and AI practice at PwC and brings over 15 years of experience in the planning and execution of complex AI, Automation and Analytics solutions. She co-led the development of PwC’s Global Responsible AI Toolkit, which recently won four awards (including the Outstanding Achievements - overall category winner) at the CogX 2020 Summit.
She has worked with various publicly listed clients in Canada, the US, and Australia across the retail, manufacturing, financial services, oil and gas, telecommunications, and aerospace industries. Annie is a strategic thinker that brings extensive experience leading the implementation of enterprise-wide projects through all phases of their lifecycle through my excellent managerial, interpersonal, and communication skills.
Recently, Annie was recognized by Re-Work, a UK-based organization, as one of the Top 30 Influential Women Advancing AI in Montreal.
Annie also mentors women in AI through various programs, including one offered by the Alberta Machine Intelligence Institute (AMII).
Ray Yu, Deloitte Innovation and Analytics
Ray is a Senior Manager leading Audit Innovation and Analytics team at Deloitte. He has over 10 years’ experience in providing data analytic services to more than 100 audit teams across Canada. Ray is a subject matter expert in AI / machine learning, automation, and visualizations. He is passionate about integrating advance technologies with audit. His work includes:
- Work with engagement teams to brain-storm analytics to improve quality and efficiency in audit
- Collaborating with different parties to bring innovations and new technologies to audit practice
- Help audit teams automate data preparation and data cleansing process
- Facilitating learning sessions to train auditors with analytics skills
Ray holds an MBA from Queens University and a master’s degree in computer science from University of Illinois at Urbana-Champaign.
Journalist/Academic Panel:
Chris Gaetano, Accounting Today
Chris Gaetano is the technology editor for Accounting Today. He brings with him more than a decade of experience covering the accounting profession as part of the NYSSCPA's Trusted Professional. Prior to that, he was a local news reporter at Greater Media Newspapers in New Jersey. He graduated from Rowan University, in Glassboro, NJ.
Steve G. Sutton, PhD
Steve is a Research Professor in the Digaudit Group at NHH Norwegian School of Economics and Professor Emeritus in Accounting in the Kenneth G. Dixon School of Accounting at the University of Central Florida. Professor Sutton has authored/co-authored 5 books, 4 research monographs and more than 150 articles in a broad range of accounting (e.g. The Accounting Review, Auditing: A Journal of Practice & Theory, Behavioral Research in Accounting, Journal of the American Taxation Association), information systems (e.g. MIS Quarterly, Journal of the Association for Information Systems, European Journal of Information Systems), production/operations management (e.g. Decision Sciences), and accounting information systems journals (e.g. International Journal of Accounting Information Systems, Journal of Information Systems, Journal of Emerging Technologies in Accounting). His research has been funded by grants totaling over $1.25 million from organizations such as the Institute of Internal Auditors Research Foundation, KPMG Foundation, Australian Research Council and FINRA Investor Education Foundation. His current research focuses on the impact of intelligent systems on expert decision makers and explores how we keep the human relevant in accounting and auditing decision making amidst the rapid advances of artificial intelligence.
Professor Sutton was the founding editor of the International Journal of Accounting Information Systems and its predecessor, Advances in Accounting Information Systems–serving over 20 years as editor. His research teams exploring AI in accounting have received the AIS Section notable contribution to the literature award four times (1996 for paper on ethical and epistemological issues in audit AI use, 1999 for paper on the Theory of Technology Dominance, 2011 for paper on differential use of AI explanation facilities between novice and expert professionals, and 2020 for paper on importance of absorptive capacity on assimilation of BI for effective management control systems). He also received the SET Section 2002-03 Outstanding Researcher Award for cumulative contributions to AI research and 2012 Outstanding Educator Award for his teaching of Ph.D. students in AI and emerging technologies research.
Chanyuan (Abigail) Zhang, PhD
Abigail is a visiting assistant professor at the Department of Accounting and Information Systems at Rutgers Business School. She received a PhD in accounting from Rutgers Business School in May 2022. Her research examines the implications of emerging technologies, especially Artificial Intelligence (AI), Machine Learning (ML), and Robotic Process Automation (RPA), in accounting and auditing.
Since 2017, Abigail has been working with several CPA firms to explore the use of emerging technologies, especially RPA, in their audit procedures. Abigail is the coauthor and instructor for the American Institute of CPA (AICPA) audit automation course modules.
Abigail has taught Introduction to Managerial Accounting (undergraduate), Auditing (undergraduate), Robotic Process Automation in Accounting and Assurance (master’s), and Information Technology in Accounting and Assurance (MBA). She is currently teaching Accounting Information Systems at Rutgers Business School – New Brunswick.
References:
Acemoglu, D., and P. Restrepo. 2019. Automation and New Tasks: How Technology Displaces and Reinstates Labor. Journal of Economic Perspectives 33 (2): 3–30.
Agrawal, A., J. Gans, and A. Goldfarb. 2018. Prediction Machines: The Simple Economics of Artificial Intelligence. Harvard Business Press.
Agrawal, A., J. S. Gans, and A. Goldfarb. 2019. Artificial Intelligence: The Ambiguous Labor Market Impact of Automating Prediction. Journal of Economic Perspectives 33 (2): 31–50.
Baird, A., and L. Maruping. 2021. The Next Generation of Research on IS Use: A Theoretical Framework of Delegation to and from Agentic IS Artifacts. Management Information Systems Quarterly 45 (1): 315–341.
Balakrishnan, T., M. Chui, B. Hall, and N. Henke. 2020. Global survey: The state of AI in 2020. Survey. McKinsey Digital. McKinsey.
Berente, N., B. Gu, J. Recker, and R. Santhanam. 2021. Special Issue Editor’s Comments: Managing Artificial Intelligence. Management Information Systems Quarterly 45 (3): 1433–1450.
Bogert, E., A. Schecter, and R. T. Watson. 2021. Humans rely more on algorithms than social influence as a task becomes more difficult. Scientific Reports 11 (1): 8028.
Brock, J. K.-U., and F. von Wangenheim. 2019. Demystifying AI: What Digital Transformation Leaders Can Teach You about Realistic Artificial Intelligence. California management review 61 (4): 110–134.
Bughin, J., E. Hazan, S. Ramaswamy, M. Chui, T. Allas, P. Dahlström, N. Henke, and M. Trench. 2018. Artificial intelligence the next digital frontier? McKinsey and Company Global Institute.
Daws, R. 2020. AI dominates Gartner’s latest Hype Cycle for emerging technologies. AI News. https://artificialintelligence-news.com/2020/08/18/ai-gartner-hype-cycle-emerging-technologies/.
Di Vaio, A., R. Hassan, and C. Alavoine. 2022. Data intelligence and analytics: A bibliometric analysis of human–Artificial intelligence in public sector decision-making effectiveness. Technological Forecasting and Social Change 174: 121201.
Diorio, S. 2020. Realizing the Growth Potential of AI. Forbes, May 8, sec. Thought Leaders.
Economist. 2022a. Huge “foundation models” are turbo-charging AI progress. The Economist, June 11.
———. 2022b. How smarter AI will change creativity. The Economist, June 11.
Forman, A.S., N.M. Glasser, R.J. O’Hara, A.J. Franchilli and R.D. Madia. 2022. NYC Issues Proposed Rules for Its Automated Employment Decision Tools Law. National Law Review. Volume XII, Number 269; available at NYC DCWP Automated Employment Decision Tools Legislation (natlawreview.com)
Faraj, S., S. Pachidi, and K. Sayegh. 2018. Working and organizing in the age of the learning algorithm. Information and organization 28 (1): 62–70.
Fedyk, A., T. Fedyk, J. Hodson, and N. V. Khimich. 2021. Is Artificial Intelligence Making Audit Firms More Efficient? SSRN Scholarly Paper. Rochester, NY: Social Science Research Network.
Fjeld, J., Nele Achte, Hannah Hilligos, Adam Nagy, and M. Srikumar. 2020. Principled Artificial Intelligence: Mapping Consensus in Ethical and Rights-based Approaches to Principles for AI. Berkman Klein Center for Internet & Society. Cambridge, Mass: Harvard University.
Fuegener, A., J. Grahl, A. Gupta, and W. Ketter. 2021. Will Humans-in-the-Loop Become Borgs? Merits and Pitfalls of Working with AI. Management Information Systems Quarterly 45 (3): 1527–1556.
Fügener, A., J. Grahl, A. Gupta, and W. Ketter. 2022. Cognitive Challenges in Human–Artificial Intelligence Collaboration: Investigating the Path Toward Productive Delegation. Information Systems Research 33 (2): 678–696.
Gartner. 2022. Top Strategic Technology Trends for 2022. Gartner. https://www.gartner.com/en/information-technology/insights/top-technology-trends.
Gray, G. L., V. Chiu, Q. Liu, and P. Li. 2014. The expert systems life cycle in AIS research: What does it mean for future AIS research? International Journal of Accounting Information Systems 15 (4). 2013 Research Symposium on Information Integrity & Information Systems Assurance: 423–451.
Jacobsen, R., L. Bysted, P. Johansen, E. Papachristos, and M. Skov. 2020. Perceived and Measured Task Effectiveness in Human-AI Collaboration. In , 1–9. CHI EA ’20. ACM.
Lebovitz, S., N. Levina, and H. Lifshitz-Assaf. 2021. Is AI Ground Truth Really True? The Dangers of Training and Evaluating AI Tools Based on Experts’ Know-What. Management Information Systems Quarterly 45 (3): 1501–1526.
Loten, A. 2022. VCs Target AI Accounting Startups as Companies Look to Control Spending in Uncertain Economy. Wall Street Journal, June 13, sec. C Suite.
Loucks, J., S. Hupfer, D. Jarvis, and T. Murphy. 2019. Future in the balance? How countries are pursuing an AI advantage. Deloitte Insights. https://www2.deloitte.com/content/www/us/en/insights/focus/cognitive-technologies/ai-investment-by-country.html.
O’Neil, C. 2016. Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. New York: Crown.
Pachidi, S., H. Berends, S. Faraj, and M. Huysman. 2021. Make Way for the Algorithms: Symbolic Actions and Change in a Regime of Knowing. Organization Science 32 (1): 18–41.
Redden, J., J. Brand, and V. Terzieva. 2020. Data Harm Record. Data Justice Lab. https://datajusticelab.org/data-harm-record/.
Sutton, S. G., M. Holt, and V. Arnold. 2016. “The reports of my death are greatly exaggerated”—Artificial intelligence research in accounting. International Journal of Accounting Information Systems 22. 2015 Research Symposium on Information Integrity & Information Systems Assurance: 60–73.
Trentmann, N. 2022a. Microsoft Keeps Its Finance Head Count Flat With AI, Bots and Other Tech; The new tools help automate tasks. But “we love Excel,” says Cory Hrncirik, who leads Microsoft’s Modern Finance project. Wall Street Journal (Online), February 10, sec. C Suite.
———. 2022b. Google Finance Head: An
Workshop Recording & Presentations:
The recording of this workshop held December 7, 2022 is only available to registrants and requires a password:
tba
Presentation slides:
- tba