Image Credit: Image Created by Man Fung LO Using DALL-E 3.
GIC director EUR ING Dr Man Fung Lo explores key research related to AI and business curriculum development, introduces two models for integrating AI into the curriculum, and shares practical recommendations to help educators and industry prepare students in their career development for an AI-driven future.
Recently, I had the opportunity to serve on an academic programme validation panel and an advisory board, where we considered and advised on curriculum and course design relevant to AI. During the preparation for these roles, I conducted a literature review on how AI has been integrated into curricula in the higher education sector. This review prompted me to reflect on my role as an educator and the importance of developing an AI-embedded curriculum that benefits our students in their career development.
In this article, I would like to share students’ perceptions of various emerging technologies, such as AI and data analytics, in the business education curriculum. I will then present two models that help guide educators in incorporating AI into the curriculum, followed by some studies related to recommendations for different majors within business education. Finally, I will offer my suggestions for educators and the industry to work on collaboratively.
The presence of AI has presented both opportunities and challenges across various sectors, including marketing, human resources, banking, IT management and education (Ooi et al., 2025). Abdelwahab et al. (2023) raised an important question regarding whether higher education institutions are adequately equipping the next generation with the essential knowledge, skills and attributes necessary to work in AI-driven environments. The study identified four AI-specific skills crucial for Industry 4.0: (i) digital and data literacy skills; (ii) problem-solving, conflict resolution, analytical and mathematical skills; (iii) computer, systems, engineering, programming, mathematical and technical skills; and (iv) life skills and soft skills, such as innovation, social and emotional learning, collaboration, communication and interpersonal skills. The research team gathered opinions from final-year students and recent graduates of business programmes from 27 institutions, revealing that these students felt their institutions “are not optimally equipped at this time and/or have not optimally utilized their facilities to adequately prepare them for AI work environments” (Abdelwahab et al., 2023, p.23).
Similarly, Tominc and Rožman (2023) conducted a study examining the perceptions of both undergraduate and postgraduate students from various business majors, including finance, banking, marketing, and entrepreneurship, regarding different aspects of AI. The findings show that postgraduate students have a more positive attitude toward AI and its potential benefits for businesses than undergraduate students. Therefore, more opportunities should be offered for undergraduate students to “engage with AI-related topics and gain hands-on experience through projects, internships, or workshops” (Tominc & Rožman, 2023, p.15).
Another recent study collected empirical data from business graduates of Egyptian universities and emphasized that incorporating data analytics into the business curriculum is a necessity (Diab & El Sayad, 2025). Both studies by Abdelwahab et al. (2023) and Tominc and Rožman (2023) recommend that higher education institutions should increase awareness of AI for both students and educators — its impacts and potentials in the business world — and update curricula to incorporate AI across all modules. This approach aims to equip students with AI-specific skills essential for Industry 4.0, which are highly valued by employers.
To meet societal needs, it’s clear that immediate action is necessary to reimagine the business curriculum. Nithithanatchinnapat et al. (2024) noted that revamping the business curriculum typically takes considerable time and suggested adopting an incremental approach to integrate AI into existing courses. In the initial phase, educators could infuse AI into current course content, while later phases would focus on developing a new business education model.
During my review, one notable study worth referencing is the development of “AI Across the Curriculum” by the University of Florida (UF) (Southworth et al., 2023). The UF AI Literacy Model, inspired by the model from Ng et al. (2021), categorizes AI Literacy into Enabling AI, Knowing & Understanding AI, Using & Applying AI, Evaluating and Creating AI and AI Ethics. It facilitates educators in reviewing course offerings to identify gaps or needs, ensuring AI learning opportunities are integrated. Those interested can refer to another report by UF for more information.
Another study by Hashmi and Bal (2024) proposed an “Educational Toolbox” that offers recommendations for increasing AI integration in the curriculum. The toolbox is comprised of two dimensions: (i) “AI human enhancing” versus “AI human replacing” and (ii) “Existing skill in the curriculum” versus “New skill in the curriculum” (Table 1). For illustration, an example of “amplifying knowledge” provided by the authors suggests that computer science students could first learn the basics of computer programming, followed by strategically embedding AI tools in the curriculum to enable faster and more efficient coding. More examples are available in this study for further exploration. Notably, I want to highlight that these studies all emphasize the importance of including ethics training in the curriculum.
Table 1. Educational Toolbox by Hashmi and Bal (2024)
| Existing skill in curriculum | New skill in curriculum | |
| AI human enhancing | Amplifying knowledge:
|
Curriculum addition:
|
| AI human enhancing | Diminished focus:
|
Ethics and foundations training:
|
Source: Adopted from Hashmi and Bal (2024)
When Xu and Babaian (2021) discussed the topic of AI in business curricula, they noted that AI education in business and management schools faces more challenges compared to other schools. One potential reason is the limited literature on teaching AI-related topics in business curricula, much of which is outdated. To address this, more scholars and researchers have conducted studies examining the role of AI in developing business education curricula. I would like to take this opportunity to thank them for their valuable insights. Below are highlights of these studies in selected majors:
- Marketing: In the technology-augmented marketing era, Grewal et al. (2025) summarized novel topics for marketing education, including AI, robots, digital marketing, big data and marketing analytics, and sustainable development, to help educators reimagine existing marketing courses. The study also emphasized the evolution of pedagogy in marketing education, including increased use of digital tools, various teaching modalities (in-class, online synchronized and online asynchronous), and experiential learning. Additionally, Barger et al. (2024) shared new course descriptions after introducing AI, along with suggestions for AI course content and assignments for selected marketing courses.
- Accounting: Mohamed Saad (2025) investigated the impact of AI on accounting jobs and academic programmes, urging higher education to adapt accounting education to meet the challenges posed by AI-driven job landscapes. Mohamed Saad (2025) suggested incorporating real-life AI-powered data analysis and financial reporting projects into the accounting curriculum to enhance students’ understanding of AI’s application in accounting data analytics. Engaging students with real-world AI data analytic projects helps them recognize challenges associated with using AI-infused accounting software. Similarly, Amin et al. (2025) conducted a bibliometric analysis on accounting education literature, highlighting the growing importance of emerging technologies on accountants’ digital skills. This study recommended that higher education institutions prepare graduates for the digital age by reimagining the curriculum to include new courses or electives on ABCD technologies (AI, Blockchain, Cloud computing, and Data analytics).
- Information Systems: A significant initiative in Information Systems (IS) curriculum analysis is the MaCuDE project (Management Curriculum for the Digital Era) (Lyytinen et al., 2021; Lyytinen et al., 2023a; Lyytinen et al., 2023b). The project offered recommendations to extend the future IS curriculum into areas such as business analytics, cybersecurity, digital design and artificial intelligence. Within this project, competency levels are classified into Awareness, Novice, Intermediate, Advanced, and Proficient. Lyytinen et al. (2023b) proposed that all business undergraduates should have an Awareness level of Big Data, IT Infrastructure and Artificial Intelligence, a Novice level in Systems Development and Deployment, and an Intermediate level for Data Analytics and Individual Analytics/Programming Skills. IS majors are expected to have a Novice level in Big Data and IT Infrastructure, a Novice level in Artificial Intelligence, Intermediate in Data Analytics, Business Continuity and Information Assurance, and Systems Development and Deployment, and an Advanced level in Individual Analytics/Programming Skills. More details about postgraduate programs are available in this study for further exploration.
To sum up, I gained a lot from reading this literature while preparing my advisory work on curriculum and course design. Reflecting on these experiences, I have a few humble suggestions. It is crucial for educators, researchers, higher education institutions, employers, industry, and professional bodies to work collaboratively to meet the new demands of the AI-driven workplace and design (and redesign) the most suitable and state-of-the-art curriculum for our next generation.
First, tech companies could continue to support educators in teaching their students to learn cutting-edge digital tools and AI platforms. For instance, Alteryx offers its SparkED Education Program, SAS Institute provides the SAS Academic Programs, and Tableau (from Salesforce) offers its Academic Programs (in alphabetical order), among others. Second, as stated in the literature, professional and accreditation bodies also play an important role in curriculum development and design, such as AACSB (Amin et al., 2025; Lyytinen et al., 2023b), ACS, BCS and CIPS (in alphabetical order) (Hol, 2024). Continuous efforts between these bodies and higher education institutions should be made on curriculum development. Inspired by Nithithanatchinnapat (2024), I recognize the importance of scholarly activities related to the role of AI in the education curriculum development. It is crucial for all educators and scholars to jointly continue their good work in this area of research.
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Image Credit: Image Created by Man Fung LO Using DALL-E 3.
References
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Amin, H. M., Hassan, R. S., Ghoneim, H., & Abdallah, A. S. (2025). A bibliometric analysis of accounting education literature in the digital era: current status, implications and agenda for future research. Journal of Financial Reporting and Accounting, 23(2), 742-768. https://doi.org/10.1108/JFRA-12-2023-0802
Barger, V. A., Chennamaneni, P. R., Dahl, A. J., & Peltier, J. W. (2024). A How-To-Guide For Bringing Artificial Intelligence Into Life In Your Marketing Curriculum: A Blueprint For Student Learning And Success. Marketing Education Review, 1-10. https://doi.org/10.1080/10528008.2024.2430259
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