Purpose The purpose of this paper is to show that knowledge contributing to innovation and decision-making must integrate rational and emotional thinking. This highlights the fundamental importance of integrating and balancing AI-based technologies with distinct human traits. For this reason, it is argued that while Artificial Intelligence (AI) primarily strengthens innovation through rational, analytical cognitive capabilities, it is essential to balance this perspective with the aesthetic, emotional, and experiential dimensions, which are essential for human-centered innovation and decision-making. In this view, the paper introduces the Knowledge Convergent Innovation Model as a conceptual framework illustrating the logic of integrating AI with Aesthetic Technologies (AT) to enhance organizational innovation capacity. Design/methodology/approach Adopting a knowledge-based view of innovation and conceptualizing innovation as a cognitive process that integrates rational and emotional capabilities, this study proposes a conceptual framework that explains the importance of integrating these dimensions to develop human-centered organizational innovation capacity. Drawing on science and technology studies (STS), the framework treats technology as embodied knowledge that extends human cognition and action, enabling a distinction between AI (rational knowledge) and AT (emotional/experiential knowledge). The study employs a case study to provide insights that support the proposed model. The case of Elica, a global Italian company, highlights how arts-based management operates as a form of AT in organizational innovation. Findings The paper presents the Convergent Knowledge Innovation model as a logical framework for explaining the importance of integrating AI and AT as complementary technologies to build organizational innovation capacity. Indeed, AI augments cognitive rational capacities, while AT strengthens emotional and experiential human cognitive capacities. The Elica case illustrates the role of AT in fostering innovation and supports the argument that sustainable innovation requires a dialogic integration of rational and aesthetic thinking to generate functional and emotionally resonant outcomes. Research limitations/implications While the paper is grounded in the knowledge-based view and science and technology studies, it employs a qualitative research approach to provide insights that support its conceptual arguments. Although the case study of Elica provides empirical evidence, it also highlights the limitations of case-study methods. While it supports conceptual development and managerial insight, further research could expand empirical testing across industries and organizational contexts and examine how different configurations of AI–AT integration influence organizational innovation capacity. Practical implications The study offers managers implications for the importance of adopting AI as a cognitive technology that must be harmonized with AT to unlock innovation capacity. In practice, this involves: (1) bundling functionality and aesthetics in products, services, and workplace solutions; (2) complementing AI’s computational strengths with AT’s capacity to nurture imagination, decision-making, and engagement; and (3) using AI–AT integration as a strategic route to sustainable, human-centric value creation, aligning operational sustainability with ethical and experiential considerations. Social implications The integration of AI and AT is essential to drive innovation that can truly address the challenges and problems of today's complex social and economic environment. By deploying the cognitive power of AI and the sensitivities associated with AT, organisations can face weak problems and identify possible solutions to complex challenges. Originality/value The paper proposes the Convergent Knowledge Innovation model, which extends the knowledge-based view of innovation by structurally integrating rational and emotional cognition. It also extends science and technology studies by framing AI and AT as complementary forms of embodied knowledge, offering a holistic approach to building sustainable organizational innovation capacity.
Schiuma et al. (Wed,) studied this question.