Preserving Human Creativity and Judgment in AI-Driven Firms

Domitilla Magni ()
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Domitilla Magni: Catholic University of the Sacred Heart, Department of Economics and Business Management Sciences

Chapter 9 in AI-Driven Business Models, 2026, pp 99-105 from Springer

Abstract: Abstract The preceding chapters have examined how AI reshapes organizational architectures and introduces new categories of risk that require deliberate governance. A further dimension of organizational transformation, analytically distinct yet deeply connected to both, concerns the fate of human creative and judgmental capacities within firms increasingly organized around algorithmic intelligence. This chapter addresses a question that is at once theoretical and managerial: as AI systems assume expanding roles in pattern recognition, prediction, and operational decision-making, what becomes of the distinctively human contributions—reativity, moral reasoning, intuition, and interpretive judgment—that have historically constituted the core of professional and managerial work? The argument developed here resists two symmetrical distortions that recurrently appear in both academic and practitioner debates. The first is the substitution thesis, which holds that sufficiently advanced AI will eventually replicate or surpass human cognitive capacities across all organizationally relevant domains, rendering human judgment progressively redundant. The second is the irreplaceability thesis, which holds that human creativity and judgment are categorically beyond algorithmic reach, such that concerns about their erosion are misplaced. Both positions are analytically inadequate. The substitution thesis underestimates the structural dependence of algorithmic systems on human-defined objectives, interpretive frames, and institutional contexts. The irreplaceability thesis underestimates the degree to which human cognitive practices are already shaped, constrained, and in some cases diminished by the organizational integration of AI. A theoretically adequate account must engage the actual mechanisms through which human and algorithmic cognition interact within organizational settings, and must identify the conditions under which this interaction enhances or degrades the quality of human judgment and creative output.

Date: 2026
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DOI: 10.1007/978-3-032-35262-0_9

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