As artificial intelligence (AI) continues to accelerate organizational decision-making processes, managers are increasingly confronted with dual-path challenges and opportunities. This paper introduces a dual-path process theory examining the effects of AI-induced temporal compression – a continuous acceleration of decision cycles – on managerial cognition, emotions, and behavior. We propose that temporal compression creates two distinct paths: a toll path characterized by cognitive overload, emotional stress, and reactive, short-term decision-making; and a capability development path, where successful temporal recalibration enables managers to leverage AI for enhanced cognitive efficiency, emotional resilience, and adaptive strategic behaviors. Drawing on bounded rationality, cognitive load theory, and resilience theory, we extend existing frameworks to account for the risks and benefits of AI-driven environments. The theory provides new insights into how managers’ ability to recalibrate their cognitive and emotional resources determines their success in navigating AI-induced pressures. Our work highlights the need for organizational strategies that support recalibration to maximize AI’s potential while mitigating its cognitive toll, thus sustaining both operational efficiency and long-term strategic outcomes.
