Accounting Educators

Strategies for Incorporating AI into the Classroom

The new CPA licensure requirements are expected to have a considerable influence on the course contents taught in accounting classes in the coming years. Some colleges have already started to incorporate data analytics in their accounting curriculum, collaborating with statistics and data science faculty or as standalone initiatives within accounting departments. For example, recent classes give students access to online resources for learning to use standard tools, such as Microsoft Excel and Access, as well as business intelligence software, such as PowerBl or Tableau, and audit software, such as ACL and IDEA, a part of their course materials and assignments.

Colleges have similarly begun to recognize the role of information technology in accounting curricula, in part due to pressures from accrediting bodies to enhance the technological content of accounting courses, including the issuance of the 2013 revised standards of The Association to Advance Collegiate Schools of Business (AACSB) requiring accredited accounting programs to incorporate technology and data analytics learning in their curriculum.

Changes in accounting programs due to advances in technology and data analytics and the challenges related to the implementation of these changes are discussed in several articles in the literature. For example. Professors J. P. Krahel of Loyola University and Miklos Vasarhelyi (2014) of Rutgers University discussed that the accounting information systems (AIS) field is undergoing extensive changes in response to emerging and rapidly changing technologies.

Professors Josette R. E. Pelzer and Roxane M. DeLaurell (2018) of College of Charleston discussed strategies to implement new AACSB requirements related to technology and data analytics in the accounting curriculum when resources are constrained, especially within the context of a teaching-focused institution.

Introducing information technology and data analytics in accounting programs is still a work-in-progress due to colleges’, faculty’s, and students’ resource constraints. But colleges face even greater challenges now. Al and machine learning are taught in computer science or software engineering departments. Bringing Al and machine learning into the accounting classroom will require cross-departmental collaboration beyond the traditional boundaries of business schools. Universities should develop courses, projects, and case studies involving cooperation among faculty and students from departments of software engineering, data science, and accounting. In this way, accountants should be trained alongside and work closely with data scientists and Al system engineers.

Furthermore, as accountants spend more time in value-added services and business performance-enhancing activities because of Al, colleges will need to increase “soft skills” training. Development of critical thinking, problem-solving, judgment, and effective communication skills will ensure that accounting students gain an adequate understanding of business operations and organizational leadership. This will require increased collaboration and linkages among departments such as accounting, finance, MIS, and strategic management within business schools.

Adequate incentives should be implemented to foster needed cross-departmental collaboration. Faculty from non-accounting departments should be incentivized to work with accounting faculty and practitioners to help design and teach courses that are relevant for accountants. Academic career paths should offer more opportunities for faculty to teach in multiple departments. Given the social realities that academia traditionally favors professors who specialize in one discipline (e.g., computer science, data science, accounting, finance, strategic management), interdisciplinary research should be better encouraged than it is today.

In a recent article, accounting Ph.D. student C. Zhang (Rutgers University) and Professors J. Dai (Southwestern University of Finance and Economics, China) and Miklos Vasarhelyi (Rutgers University) analyzed the impact of disruptive technologies (Al, RPA, blockchain, and other emerging technologies) on accounting education (2018). The authors specifically cited the lack of qualified faculty members with a strong background in both technology and accounting as one of the biggest challenges faced by universities today.

They added: “Although basic courses, like IT and statistics, can be offered by professors in each discipline, innovative courses that bridge technology and accounting should be taught by faculty with expertise in both domains” (p. 24).

An innovative course that bridges technology and accounting would be, for example, a course that blends technology into a traditional accounting course. The authors suggest it later in their article by stating:

Business school accounting programs are encouraged to open new courses related to IT and data analytics to diversify the course pool. Alternatively, accounting educators may also feel it useful to blend big data analytics and IT into existing traditional accounting courses such as financial accounting, managerial accounting, auditing, and taxation, (p. 26)

This line of thought is indicative of where future accounting faculty is headed and illustrates the need for accounting faculty to acquire technology skills as part of their core. The skills of accounting faculty must be like what will be expected from the accounting profession moving forward.

These skill changes do not necessarily mean that every accounting faculty needs to rewrite their course materials. Faculty should leverage existing online resources and online tutorials available on the internet (for free or for a fee) and incorporate them into their curricula. Online resources and videos may include:

• • Online materials from other faculty members within the school (shared video library within the school or university),
• • Online videos from online continuing education providers (e.g., Coursera, Udemy, Lynda, O’Reilly)
• • Online materials from other external sources, such as other universities, professional organizations, and technology and service providers

These online resources could be leveraged to help upskill accounting faculty and incorporate these resources as part of students’ assignments and exercises, case studies, and projects that would require the use of modern technologies.

Upskilling would involve a general shift of teaching methods from traditional, passive learning methods to more active learning methods. Options include experiential learning (i.e., learning-by-doing, learning from direct experience), project-based learning, and collaborative learning, where students are expected to think rather than to memorize. Considering the increased scope of learning requirements of accountants and the pace at which technologies evolve, the focus of higher education should be on teaching students how to learn rather than teaching them what to learn.

As Zhang et al. suggested in the conclusion of their article (2018): “Educators should also encourage a philosophy of lifelong learning and teach students to learn new things and adapt to the changing environment, cultivating accountants who are prepared for the future” (p. 26).

AI Training for Faculty

As discussed earlier, collaboration with computer science or software engineering departments and online resources (as mentioned in the previous section) can be used by accounting faculty to learn about new Al and machine learning technologies. Understanding how Al and ML apply to accounting is a critical part of a professional’s upskilling efforts.

Also, as Al technologies increase and become more embedded in existing applications across all business areas (e.g., enterprise resource planning, accounting, data analytics), software vendors will inevitably serve as a useful source of information and training opportunities.

Beyond understanding the concepts and how they apply to accounting, faculty should also consider experimenting with some of these technologies to learn how to use them in simple exercises and projects, by working collaboratively with practitioners. Cross-training on the use of these technologies could be achieved by collaborating with adjunct and practice-oriented faculty with experience implementing these technologies in the real world.

Other suggestions include incenting some faculty members to serve as “early adopters,” as suggested in Smith (2017). In this article, Professor Sean Stein Smith of Lehman College in New York City suggested:

Ask for faculty volunteers. Have some faculty members act as “early adopters” who can then share their knowledge and experience with the rest of the department. Seek out faculty and instructors willing to experiment and up for the challenge of learning new technology tools. Consider offering a course release or other incentive to help address time constraints. Asking for volunteers demonstrates the organization's intent toward integrating these tools and allows the most interested individuals to step forward, (para. 10)