Art der Arbeit:

• Bachelorarbeit Wirtschaftsinformatik
• Masterarbeit Wirtschaftsinformatik

Status:

Themenangebot

Ansprechpartner*in:

• Ali Ergün

Kurzfassung

This topic can be adressed in a thesis from different perspectives, such as:

• How does (generative) artificial intelligence impact team dynamics and performance?
• How does (generative) artificial intelligence impact leadership (incl. role, style and skills)?
• How does (generative) artificial intelligence impact organizational culture?

Setting the changes in team as the fundament for this thesis topic, leadership and culture are additional topics that can be added as requested.

Next to literature analysis (which need to consist of all three questions), empirical investigations are preferred such as quantitative research designs (e.g., survey, (online)experiments) or qualitative research designs (e.g., expert interviews).

Kurzfassung in Englisch:

Motivational introduction into the topic:

Having understood the significant effects of artificial intelligence (AI) on operational efficiency (Cui et al., 2024), organizations strategically focus on deploying and providing artificial intelligence in their processes and structures. Organizational members across departments now routinely and increasingly interact with conversational AI to reduce highly repetitive tasks and focus more on higher-level cognitive tasks at work, with 88% of AI users coming from non-technical professions (De Smet et al, 2023). AI interactions are likely to become even more common as generative AI is increasingly used in roles and functions previously reserved for humans, such as HR, IT, finance, or customer service and support (Tey et al, 2024). Estimations of the World Economic Forum indicate that until 2020, AI-driven automation will autonomously take over one-third of all work tasks (Di Battista et al., 2025). 

The use of GenAI brings implications for the working environment that are important today and in the future in order to generate hoped-for efficiencies: the way of working through the use of AI in business processes is changing and interpersonal collaboration in teams is being influenced as AI is used alongside human colleagues for monitoring, coordination and operational work. With AI being increasingly embedded in collaborative processes, this technology challenges, the understanding of the technology itself (Larson & DeChurch, 2020), traditional notions of teamwork (Richter & Schwabe, 2025), and intragroup processes (Zercher et al. 2023). 

Sources:

Cui, et al. (2024). The effects of generative ai on high skilled work: Evidence from three field experiments with software developers. Available at SSRN 4945566.

De Smet, A., Durth, S., Hancock, B., Baldocchi, M., & Reich, A. (2023). The human side of generative AI: Creating a path to productivity. McKinsey & Company 

Di Battista, A., Grayling, S., Játive, X., Leopold, T., Li, R., Sharma, S., & Zahidi, S. (2025, January). Future of jobs report 2025. In World Economic Forum, Geneva, Switzerland. www.weforum.org/publications/the-future-of-jobs-report-2025/digest/.

Larson, L., & DeChurch, L. A. (2020). Leading teams in the digital age: Four perspectives on technology and what they mean for leading teams. The leadership quarterly, 31(1), 101377.

Richter, A., & Schwabe, G. (2025). “There is No ‘AI’in ‘TEAM’! Or is there?”–Towards meaningful human-AI collaboration. Australasian Journal of Information Systems, 29.

Tey, K. S., Mazar, A., Tomaino, G., Duckworth, A. L., & Ungar, L. H. (2024). People judge others more harshly after talking to bots. PNAS nexus, 3(9), pgae397-

Zercher, D., Jussupow, E., & Heinzl, A. (2023). When AI joins the Team: A Literature Review on Intragroup Processes and their Effect on Team Performance in Team-AI Collaboration. ECIS 2023 Research Papers. 307. https://aisel.aisnet.org/ecis2023_rp/307