Paper Number
ECIS2025-1099
Paper Type
CRP
Abstract
Habits play a critical role in decision-making, affecting both our personal and professional lives. While good habits improve efficiency and decision quality, bad habits can reinforce biases and hinder adaptability. Artificial intelligence (AI) offers the potential of habit engineering: it can promote beneficial behavioral changes. This study examines how AI influences the habits of decision-makers and how organizations can use AI to foster effective routines. Through a case study at Allianz Global Investors (AGI), we analyze the impact of AI-driven advice on traders’ decision-making processes in a high-stakes environment. The results highlight AI’s ability to disrupt established habits, encouraging greater reflection and improved performance in trading decisions. This research contributes to the literature on habit engineering and organizational AI by highlighting the need for careful monitoring and evaluation of AI systems to balance efficiency and adaptability, ensuring that habits remain aligned with organizational goals and long-term success.
Recommended Citation
Walenta, Danilo Constantin; Sturm, Timo; Scholz, Yven; and Buxmann, Peter, "Make Up Your Mind! Habit Engineering With Artificial Intelligence in the Context of Trading" (2025). ECIS 2025 Proceedings. 3.
https://aisel.aisnet.org/ecis2025/bus_analytics/bus_analytics/3
Make Up Your Mind! Habit Engineering With Artificial Intelligence in the Context of Trading
Habits play a critical role in decision-making, affecting both our personal and professional lives. While good habits improve efficiency and decision quality, bad habits can reinforce biases and hinder adaptability. Artificial intelligence (AI) offers the potential of habit engineering: it can promote beneficial behavioral changes. This study examines how AI influences the habits of decision-makers and how organizations can use AI to foster effective routines. Through a case study at Allianz Global Investors (AGI), we analyze the impact of AI-driven advice on traders’ decision-making processes in a high-stakes environment. The results highlight AI’s ability to disrupt established habits, encouraging greater reflection and improved performance in trading decisions. This research contributes to the literature on habit engineering and organizational AI by highlighting the need for careful monitoring and evaluation of AI systems to balance efficiency and adaptability, ensuring that habits remain aligned with organizational goals and long-term success.
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