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With the popularization of generative AI like ChatGPT, artificial intelligence’s potential to disrupt the accountancy profession is globally relevant. Responding to this surge in interest, IMA (Institute of Management Accountants) recently released a report titled “The Impact of Artificial Intelligence on Accounting and Finance: A Global Perspective” which discussed recent advancements in AI’s ability to transform management accounting work.

To introduce the concept of AI, the report breaks down the technology into three types: weak AI, strong AI, and super AI. Susie Duong, IMA’s Senior Director of Research and Thought Leadership, elaborated on what the report means by these categories: “The AI models we see on the market today are all weak AI,” she explained. “Within certain contexts, this AI can perform certain tasks much, much faster than people. But the limitation is that they can only perform within that pre-programmed context. On the other hand, strong AI and super AI are still conceptual models. Strong AI would be AI with intelligence capabilities similar to a human’s, and super AI would be able to surpass human intelligence. So far, we’re not there yet.”

The kind of AI on the market now is capable of stimulating creative innovation, however. “The Impact of Artificial Intelligence on Accounting and Finance: A Global Perspective” investigated the possibilities of the AI available today for accounting and finance professionals. Interviewing around 40 experts, IMA reported that folks using AI found it was generally good at tasks like processing accounts payable and receivable and procurement—lower-level but time-intensive tasks. AI also has the potential to help untangle complicated tax compliance issues, especially for organizations operating in multiple jurisdictions, and to customize reports based on their intended audiences so that relevant data is brought to the fore for audiences most likely to need to see it.

So, AI has a multitude of applications. Still, many finance and accounting professionals have been reluctant to adopt it into their workflow. Ms. Duong mentioned two anecdotes she knew of that illustrate hangups when it comes to emerging technology. First, a CFO IMA interview shared that his company consistently faced a supply chain management issue for several years. They could not accurately track the inventory movement—there was always a mismatch between what was on paper and what came into the warehouse. Then, last year, they took pictures of their inventory and fed those pictures into a machine learning program to train it to identify and count inventory. The program was able to successfully identify the issue but even so, senior leadership pushed back against implementing the program. They had their own theories about where the supply chain issue originated, and the AI’s results contradicted those theories. The leadership team felt like their integrity was being challenged (and perhaps their professional pride was hurt as well.)  

Ms. Duong had a second story about reluctant adopters, with similar themes. Another organization was looking to adopt AI in its accounting process. The technology providers came to implement the system, which required staff to pilot the software and help the software learn. However, those staff who were asked to train the AI were the ones whose roles overlapped with the function of the AI. They were naturally concerned that the AI was going to make them redundant, and adjusted certain parameters so that the AI gave results that were not optimal or as accurate as the results produced by human staff.

This reluctance also stems from the risks of AI. IMA’s report sorts the kinds of risks associated with AI into four broad categories: human, technology & data, operational, and ethical/governance concerns. Interestingly, these challenges were recognized by the experts IMA spoke to for the report with differing levels of severity depending on the region. The Asia Pacific and North American regions recognized the human-related risks (such as illustrated by Ms. Duong’s stories about reluctant adopters) as the most challenging. For India, the technology and ethical/governance concerns were more prominent—data safety and security, as well as hiring the right talent to work on data governance policies, was a major concern. For Europe, operational challenges were more often cited.

But there may be a major risk in ignoring AI adoption as well, and that’s losing the battle for talented young professionals. Artificial intelligence, according to Ms. Duong, makes the connection between tech and finance and accounting stronger. “It’s likely that we will attract people into accounting because they have a background in computer science or data analytics. With the adoption of this technology, the boundary between tech and accounting is getting blurry.”

A friend of Ms. Duong’s in Singapore recently texted her a screenshot of a university webpage  On the page, there was a double degree listed called “Accountancy, AI and Data Science.” The degree is offered through the school’s Department of Computer Science and its Department of Accounting. It’s an example of how technology is going to change what the talent pool looks like. Even outside of computer science departments, students are already using AI for their coursework. In a few years, many of those students will enter the workforce and expect the organizations they work for to have AI-integrated workflows that do away with tedious tasks so that they can instead spend time upskilling and driving business decisions. According to Ms. Duong, there is no better time to start thinking about AI adoption and governance than the present.

Professional accountancy organizations (PAOs) have an important role in helping to prepare their members utilize AI. First, PAOs should consider offering relevant training for upskilling and reskilling professional accountants to get them ahead of the AI adoption curve. Ms. Duong also recommended monitoring AI trends and breakthroughs and communicating the changing technological landscape in reports and webinars so that members know the implications of emerging technology and use cases.

In conclusion, Susie Duong mentioned two things that accountants need to know about AI as it exists now: First, have a solid understanding of data. “Make sure that you understand data and have strong data skills. That’s what you will need to work with AI. That’s what will feed the AI and what you’ll use to interpret results.” Second, be curious. “Have an open mind and be open to changes,” Ms. Duong advised. “Find every opportunity to learn.”

Susie Duong wears a gray suit jacket and glasses and is smiling at the camera
Qi “Susie” Duong

Senior Director of Research and Thought Leadership

Qi “Susie” Duong is IMA’s senior director of research and thought leadership. She began her journey at IMA as a director of research, conducting research for the betterment of the accounting and finance profession. In her current leadership role, Susie oversees IMA’s research agenda, focusing on delivering cutting-edge thought leadership research and developing actionable solutions for the profession. She has taken on other roles at IMA, such as managing editor of the IMA Educational Case Journal (IECJ®) and liaison to the IMA Research Foundation and the IMA Committee on Academic Relations. Prior to joining IMA, Susie has served as an accounting professor in the United States and Singapore. Additionally, she has accumulated experience in public accounting and in the professional education sector.

Susie holds a Ph.D. in accounting from the University of North Carolina at Chapel Hill, an M.Phil. in accounting from the University of Hong Kong, and a BBA in accounting from Fudan University, China. She is also a CMA, a CPA, a CIA (Certified Internal Auditor), and an EA (Enrolled Agent).

Annie Brinich

Annie Brinich is a communications manager at the International Federation of Accountants. She manages and edits IFAC's Knowledge Gateway.