Paper Type
Complete
Abstract
This paper conceptualizes how explainability of AI-decision automation systems enable organizations to balance speed and slow decision-agility in ways that foster balanced decision agility (BDA) and enhance firm performance. Focusing on decision agility, we argue that organizational decision making and response to changes in dynamic environments is not just about rapid responsiveness. It also involves strategic pauses, reflection and course-correction while accelerating – agile manifestations missing in the AI-agility-performance scholarship. Using explainability as an IT governance balancing mechanism, we propose BDA as a formative integration of speed decision-agility and slow decision-agility, ultimately enhancing better performance. Theoretically, the paper contributes to Information Systems and strategic management literature by moving beyond the speed dominant view of agility towards a balanced decision agility comprising of speed and strategic slowness of decision-making. Practically, the paper potentially provides organizations with a framework to achieve BDA under uncertainty, thereby minimizing blind acceleration and reducing costly decisions.
Paper Number
1626
Recommended Citation
Gbogbolu, Abel and Yang, Alan T., "Balancing Speed and Slow Decision-Making Agility: The Role of AI-Explainability as an IT Governance Mechanism" (2026). AMCIS 2026 Proceedings. 4.
https://aisel.aisnet.org/amcis2026/agile/agile/4
Balancing Speed and Slow Decision-Making Agility: The Role of AI-Explainability as an IT Governance Mechanism
This paper conceptualizes how explainability of AI-decision automation systems enable organizations to balance speed and slow decision-agility in ways that foster balanced decision agility (BDA) and enhance firm performance. Focusing on decision agility, we argue that organizational decision making and response to changes in dynamic environments is not just about rapid responsiveness. It also involves strategic pauses, reflection and course-correction while accelerating – agile manifestations missing in the AI-agility-performance scholarship. Using explainability as an IT governance balancing mechanism, we propose BDA as a formative integration of speed decision-agility and slow decision-agility, ultimately enhancing better performance. Theoretically, the paper contributes to Information Systems and strategic management literature by moving beyond the speed dominant view of agility towards a balanced decision agility comprising of speed and strategic slowness of decision-making. Practically, the paper potentially provides organizations with a framework to achieve BDA under uncertainty, thereby minimizing blind acceleration and reducing costly decisions.
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