AI Challenges to Business and Society

Course Directors: Rui Sun (SSE), Joanna Zukowska (SGH Warsaw School of Economics)

Some general things

• The course will be given online via Teams.
• No written individual examination on literature, only group and individual assignments.
• It is a CIVICA course given online jointly by the Warsaw School of Economics (SGH) and the Stockholm School of Economics (SSE) for students at both schools.
• The course is also included in the SSE Sustainability Track.
• Presence at meetings (seminars and lectures) is mandatory. See “Course structure” below for necessary absences.
• There is a limit as to the number of students we can accept.

Course objective

The aim of the course is to make students learn about and arrive at deeper insights in, and understanding of the pros and cons / pitfalls, threats, and opportunities / advantages and disadvantages of AI concerning different applied areas related to business and society and how to manage such challenges

Course Content and Structure

The course focuses on four different applied areas of AI:

1. AI challenges in Human Resource Management: The module will cover how AI can be applied to the four main pillars of HR: Recruitment and selection, onboarding, motiva­tion, and commu­nication with feedback. The module will present selected AI tools to support the implementation of HR tasks for the mentioned purposes. Attention will also be paid to the limitations and risks of AI in these contexts.
2. AI challenges in Online Communication: The module will cover how AI is used for different communication purposes focusing on marketing (especially the distribution of ads), diffusion of news, and dissemination of misinformation and disinformation, respectively, online. Possible positive or negative consequences – advantages and disadvantages – to business and society by such activi­ties, leading to threats or opportunities, will be discussed as well as how to best manage these challenges.
3. AI challenges in Education: The module will cover how AI can be applied in major areas concer­ning development and education, including coaching, mentoring, tutoring, work­-shops, and lectu­ring. The module will present selected AI tools to support the imple­mentation of tasks in these areas. Attention will also be paid to the limitations and risks of AI.
4. AI challenges in Intellectual Property: The module will cover how AI development relies on openly sourced publicly available content, and how the emergence of AI-based tools may influ­ence the open-source community. We will also discuss copyright challenges in intel­lectual right protection of AI-generated works, and how using AI to aid the creation of innovations may challenge existing mechanisms of IP protection.

How the course is structured

The course starts with a lecture introducing AI as such – what it is – and how it can be and is used by companies and other parts of society. The use of AI within each applied area will then be taught following the same structure over a three-week period:

First a lecture introducing the use of AI within the applied area, followed by a seminar a week later with some practices of generative AI tools and possibly a guest lecturer from a company or other parts of the society about experienced challenges within the applied area and how they have been dealt with. Second, throughout the three-week period, a group assignment where each group shall study an AI challenge of their own choice to companies/organizations and the society, respec­tively, within the applied area, arriving at recommendations for managing the challenge by companies/organizations and the society, respectively. The analysis and recom­mendations shall then be presented at a seminar at the end of the three-week period for discussion. Finally, the course will end with a final summarizing seminar and the turning in of an individual assignment. See the schedule and “Examination” for further information.

The students will be grouped in different groups twice, once for the first two modules (applied areas) and once for the last two modules aiming at optimizing the diversity as to school, country of origin, and gender of the students in the groups.

Participation in all meetings (lectures and seminars) is mandatory!

In total, up to three absences are allowed during the course – no more. If being absent more than once, you need to do an individual assignment for each following time you are absent.

Course Administrator: Rebecca.Gruvhammar@hhs.se

After the course, the students should be able to:

1. identify,
2. analyze, and
3. manage …

… pros and cons / pitfalls, threats, and opportunities / advantages and disadvantages of the use of AI in four different applied areas related to business and society: Human resources, AI-based online communications, education, and intellectual property.

Being a Civica course in collaboration between SSE and SGH, an additional ILO, although not examined, is to get experience from collaborating online – virtually – in an inter­cultural environ­ment, learning how to cooperate in productive and ethical ways across borders, and improving social skills in such a context.

General entry requirements

There is a lot of new articles published every week about the applied areas – topics – in the course, why you should consider those below as suggestions. You should especially look for other articles that more precisely concern the AI challenges you have chosen for your assignments. The articles should be available on Google Scholarr or via your school library.

Please note: Beware of hallucinations!

For example, ChatGPT-generated articles quite often do not exist. Using such is considered cheating.

Some suggested articles

1) AI challenges in Business and Society – an introduction:

• Deng, J., & Lin, Y. (2022). The benefits and challenges of ChatGPT: An overview. Frontiers in Compu­ting and Intelligent Systems, 2(2), 81-83.
• Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Dwivedi, R., Edwards, J., Eirug, A., Galanos, V., Vigneswara Ilavarasan, P., Janssen, M., Jones, P., Kumar Kar, A., Kizgin, H., Kronemann, B., Lal, B., Lucini, B., Medaglia, R., Duan, Y., & Williams, M. D. (2021). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, 101994.
• Khan, F. A., Aslam, A., & Aslam, A. (2023). Socio-Economic Shocks Due to Advancement in Artificial Intelligence Techniques. Recent Trends in Artificial Intelligence & it's Applications (e-ISSN: 2583-4819), 2(1), 10-18.
• Peres, R., Schreier, M., Schweidel, D., & Sorescu, A. (2023). On ChatGPT and beyond: How generative artificial intelligence may affect research, teaching, and practice. International Journal of Research in Marketing.
• An online “course” at SSE about AI:
• Plus: Literature searched by the students.

2) AI challenges in Human Resource Management:

• Al Qasem, A. S., & Abdalla, R. (2025). Precision management of workforce learning in organizations: A comprehensive systematic review of emerging models and roadmap. Heliyon, 11(10).
• Budhwar, P., Chowdhury, S., Wood, G., Aguinis, H., Bamber, G. J., Beltran, J. R., … & Varma, A. (2023). Human resource management in the age of generative artificial intelligence: Perspectives and research directions on ChatGPT. Human Resource Management Journal, 33(3), 606-659.
• Chowdhury, S., Dey, P., Joel-Edgar, S., Bhattacharya, S., Rodriguez-Espindola, O., Abadie, A., & Truong, L. (2023). Unlocking the value of artificial intelligence in human resource management through AI capability framework. Human Resource Management Review, 33(1), 100899.
• Jiang, Y., Cai, Z., & Wang, X. (2025). Leverage generative AI for human resource management: Integrated risk analysis approach. International Journal of Human Resource Management, 36(11), 1929-1959.
• Johnson, B.A.M., Coggburn, J.D., Llorens, J.J. (2022). Artificial Intelligence and Public Human Resource Management: Questions for Research and Practice. Public Personnel Management, 2022, Vol. 51(4) 538–562.
• Palos-Sánchez, P.R., Baena-Luna, P., Badicuc, A., Infante-Moro, J.C. (2022). Artificial Intelligence and Human Resources Management: A Bibliometric Analysis. Applied artificial intelligence, vol. 36, No 01.
• Yang, X.; Yan, S. (2024) Encourage or Reject Employee Involvement: Value Creation in Human Resource Management in the AI Era—An Evolutionary Game Analysis of Enterprises and Employees. Behav. Sci.
• Plus: Literature searched by the students.

3) AI challenges in AI-based online communications - PRELIMINARY:

• Aïmeur, E., Amri, S., & Brassard, G. (2023). Fake news, disinformation and misinformation in social media: a review. Social Network Analysis and Mining, 13(1), 30.
• Boerman, S. C., S. Kruikemeier & F. J. Zuiderveen Borgesius (2017). Online Behavioral Advertising: A Literature Review and Research Agenda, Journal of Advertising, 46:3, 363-376.
• Choi, H. Carl F. Mela, Santiago R. Balseiro, Adam Leary (2020) Online Display Advertising Markets: A Literature Review and Future Directions. Information Systems Research 31(2):556-575.
• De Bruyn, A., Viswanathan, V., Beh, Y. S., Brock, J. K. U., & Von Wangenheim, F. (2020). Artificial intelligence and marketing: Pitfalls and opportunities. Journal of Interactive Marketing, 51(1), 91-105.
• Pérez-Escolar, M., Lilleker, D., & Tapia-Frade, A. (2023). A systematic literature review of the phenomenon of disinformation and misinformation. Media and Communication, 11(2), 76-87.
• Whyte, Christopher. "Deepfake news: AI-enabled disinformation as a multi-level public policy challenge." Journal of cyber policy 5, no. 2 (2020): 199-217.
• Plus: Literature searched by the students.

4) AI challenges in Education:

• Ajani, O.A., Akintolu, M., Afolabi, O. (2024) The emergence of artificial intelligence in the higher education: Prospects and challenges of AI. International Journal of Research In Business and Social Science. 13(8) (2024) 157-165.
• Gillani, N., Eynon, R., Chiabaut, C., & Finkel, K. (2023). Unpacking the “Black Box” of AI in Education. Educational Technology & Society, 26(1), 99-111. https://doi.org/10.30191/ETS.202301_26(1).0008
• Holmes, W., & Tuomi, I. (2022). State of the art and practice in AI in education. European Journal of Education, 57(4), 542-570.
• Jordan, A., Dockens, A. L., Pierson, N. A., & Ren, X. (2025). Editorial: AI’s impact on higher education: transforming research, teaching, and learning. Frontiers in Education.
• Limna, P., Jakwatanatham, S., Siripipattanakul, S., Kaewpuang, P., & Sriboonruang, P. (2022). A review of artificial intelligence (AI) in education during the digital era. Advance Knowledge for Executives, 1(1), 1-9.
• Sejdiu, N. P., & Sejdiu, S. (2025). The quiet transformation of higher education in the the AI era. Open Research Europe.
• Xie, H., Hwang, G. J. & Wong, T. L. (2021). Editorial Note: From Conventional AI to Modern AI in Education: Re-examining AI and Analytic Techniques for Teaching and Learning. Educational Technology & Society, 24 (3), 85–88.
• Plus: Literature searched by the students.

5) AI challenges in Intellectual Property:

• Appel, G., Neelbauer, J., & Schweidel, D. A. (2023). Generative AI has an intellectual property problem. Harvard Business Review, 11.
• Burtch, G., Lee, D., & Chen, Z. (2024). The consequences of generative AI for online knowledge communities. Scientific Reports, 14(1), 10413.
• Gans, J. S. (2024). Copyright policy options for generative artificial intelligence (No. w32106). National Bureau of Economic Research.
• Hui, X., Reshef, O., & Zhou, L. (2024). The short-term effects of generative artificial intelligence on employment: Evidence from an online labor market. Organization Science.
• Mahari, R., Fjeld, J., & Epstein, Z. (2023). Generative AI is a minefield for copyright law. The Conversation.
• Plus: Literature searched by the students.

The only grade granted is Pass

All assignments as well as individual contributions when presenting and discussing these will be graded accordingly:

• The group assignments will be graded with a maximum of 20 points each: 4 x 20 = 80 points: 2 points of the 20 will be used for the quality of the presentation and 3 points for individual contributions (judged by the teacher during the presentation seminar).
• The final individual assignment will be graded with a maximum of 20 points.

For SSE students to pass the course:

Passing all four group and the final individual assignments (> 50% of points of each assignment) as well as having participated in the lectures and seminars in the specified way.

For SGH students to pass the course:

• Having participated in the lectures and seminars in the specified way.
• At least a total of 51 points to pass the course.
• All four group assignments and the final individual assignments must be passed.
• The SGH general grading scheme will be used for final course grade based on the total points achieved.

Instructions for the group assignments

• Carried out in groups of 5-6 students from both universities (two different groups during the course, two assignments for each group).
• For each assignment within each applied area, the group should:

1. Identify a case where AI is or could be used and describe how AI is or could be used by whom for what purposes.
2. Analyze the pros and cons / pitfalls, threats and opportunities / advantages and disadvan­tages of this use of AI to businesses and the society, respectively.
3. Suggest how businesses and society, respectively, should deal with or manage the cons, disadvantages, pitfalls, or threats (being challenges).

The group assignment reporting

• Your main findings are to be reported as a PowerPoint presentation that should take a maxi­mum of 10 minutes to present. Make sure to cover all three points listed above: 1. Identify and describe, 2. Analyze, and 3. Suggest.
• First page should have the group’s number and a group name (of your own choice), and the names of the students contributing to the assignment and their registration numbers.
• After your analysis and solutions, use one slide to summarize your own use of AI when working on the assignment. (See below for an AI use report for each assignment.)
• The last slide should show a reference list. (Beware of hallucinations! AI-generated references are considered cheating.)
• Each slide should be accompanied by a text explaining and motivating everything in the slide, making its content clear to anyone who doesn't listen to the presentation.
• Submit in due time on Teams, both your presentation and your AI use report about your own use of AI when working with the assignment. See the schedule for submission deadlines: Always two days before the presentation seminars at 12.59.

An AI use report

You are encouraged to use generative AI-tools such as ChatGPT, Microsoft Copilot (protected version available to SSE students by logging in at SSE), Google Gemini or Claude, but with some restrictions (see below), and for each assignment you need to submit a report where you should:

1. Describe what AI tools have been used and how – no word limit, by be precise. Also attach on Appendix with screen shots of all prompts used and the results.
2. Discuss in what ways these tools have contributed to increasing the quality of your analysis and solutions – maximum 100 words,
3. Analyze what potential risks found with using AI – maximum 100 words,
4. Describe what measures you have taken to reduce these risks – maximum 100 words.
5. Conclude what you have learnt from using AI tools when working on the assignment.

Check the specific and general rules for the use of AI at SSE and SGH, respectively (available in Teams).

Limitation of use of generative AI in the course

You may only use AI for the following:

1. Finding an interesting case. You still need to check and validate all facts – you cannot trust the information you get about the case.
2. Language check. You still need to go through all suggested changes and agree or disagree with them.

You must not do the following:

1. You must not enter the instructions for the assignments as prompts. It is your output that is examined, not the output from AI tools. The use of AI for analysis and results is considered cheating and will be reported.
2. You must not use AI tools for creating your slides since those are the output that are examined.
3. You must not upload copy-write articles or other texts into an AI tool which may violate copyrights

At the presentation seminars

• Each group will have a maximum of 10 minutes to present their challenge analysis.
• Another group will be appointed as opponent, having read the presenting group’s presentation and prepared questions based on it, then leading the discussion for another 10-15 minutes.

Instructions for the final individual assignment

By the end of the course, each student must also submit an individual assignment concerning testing and analyzing the output of different generative AI tools:

1. Ask each of the following generative AI tools (i.e., four different tools in all) – ChatGPT (or Copilot), Claude, Mistral, and DeepSeek – one of the following three questions:

• What should I do to improve my understanding of how artificial intelligence transforms business models and decision-making?
• What should I do to enhance my awareness and understanding of the ethical and social implications of AI in business and society?
• What should I do to develop my ability to lead or manage AI-driven initiatives in a business or social organization?

2. Then ask five following-up questions to the first output you get from each of the AI tools you are testing. It’s important that you use the same following-up questions for each AI tool! Examples of such questions to ask are:

1. How can I stay updated with rapidly changing AI technologies in business contexts?
2. How can I evaluate the real value AI brings to organizational strategy and performance?
3. How can businesses balance innovation with social responsibility when using AI?
4. How can I personally contribute to promoting ethical AI use in my professional environment?
5. How can bias and discrimination in AI systems be recognized and mitigated?

3. Then ask the very first question again.

4. Analyze the output in the following two ways:

• Analyze for each tool how the output changes from the first to the last question asked. What can you conclude about each AI tool? Any general conclusion concerning this?
• Compare the output of the different tools for the first and the last question asked. What conclusions can you make.

5. Finally, discuss your findings regarding the use of different AI tools from an individual, a business, and a societal perspective, respectively (a maximum of 600 words).

Find the course schedule in TimeEdit

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