Paper Number
1567
Paper Type
Short
Description
The advent of Artificial Intelligence (AI) challenges our understanding of firms’ knowledge search behavior. While scholars agree on the transformational potential of AI, recent conceptual research offers opposing perspectives on how AI shapes corporate search activities. Through the lens of managerial attention, we examine how AI as a strategic choice affects corporate exploration and exploitation. An analysis of S&P 1500 firms from 2013 to 2021 reveals that AI directs managerial attention toward novel opportunities and the realization of existing ones, thus simultaneously increasing exploration and exploitation. We further find that under high technological turbulence, firms increase their AI activities for explorative purposes. Overall, we contribute to the literature on search behavior, attention-based view, and AI by highlighting the role of a strategic AI orientation for corporate search. Furthermore, we refine the measurement of AI orientation by developing a dictionary based on unsupervised topic modeling eligible for computer-aided textual analysis.
Recommended Citation
Eicke, Ann-Katrin Maren; Sabel, Christopher; and Nüesch, Stephan, "Algorithm-driven Search: An Attention-based View on Artificial Intelligence for Organizational Exploitation and Exploration" (2022). ICIS 2022 Proceedings. 5.
https://aisel.aisnet.org/icis2022/governance_is/governance_is/5
Algorithm-driven Search: An Attention-based View on Artificial Intelligence for Organizational Exploitation and Exploration
The advent of Artificial Intelligence (AI) challenges our understanding of firms’ knowledge search behavior. While scholars agree on the transformational potential of AI, recent conceptual research offers opposing perspectives on how AI shapes corporate search activities. Through the lens of managerial attention, we examine how AI as a strategic choice affects corporate exploration and exploitation. An analysis of S&P 1500 firms from 2013 to 2021 reveals that AI directs managerial attention toward novel opportunities and the realization of existing ones, thus simultaneously increasing exploration and exploitation. We further find that under high technological turbulence, firms increase their AI activities for explorative purposes. Overall, we contribute to the literature on search behavior, attention-based view, and AI by highlighting the role of a strategic AI orientation for corporate search. Furthermore, we refine the measurement of AI orientation by developing a dictionary based on unsupervised topic modeling eligible for computer-aided textual analysis.
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