Organizational learning with artificial intelligence: Balancing new tensions between explorative and exploitative learning through hybridization

Abstract

To realize the potential of artificial intelligence (AI), organizations must manage the paradoxical tensions that arise when using it in pursuit of innovation. Studies suggest that the adoption of AI introduces new avenues for explorative and exploitative learning in organizations, prompting a reassessment of how these competing learning modes interact. Drawing on interview data, we identify a set of new tensions that arise when AI is used to support organizational learning. We conceptualize these tensions as paradoxes of autonomy (autonomy vs. control), rationality (formal vs. substantive), transparency (opacity vs. accountability), and opportunity (internal vs. external learning). We contribute to the emerging literature on the role of AI in organizational learning by showing why organizational learning with AI benefits from a hybridization approach that integrates the distinctive yet complementary learning capacities of humans and AI. Hybridization creates conditions to enact coping solutions for the paradoxes identified. • Explores new tensions arising from explorative and exploitative learning with AI. • Interviews revealed four AI-related paradoxes. • Organizational learning benefits from a balanced integration of human and AI learning affordances. • Hybridization enables human-AI collaborative agency to navigate the organizational learning paradoxes of AI. • Offers suggestions for managing organizational learning with AI in practice.

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