Document Type
Article
Source of Publication
Journal of Innovation and Knowledge
Publication Date
9-1-2026
Abstract
Artificial intelligence (AI) has become an integral component of innovation infrastructure, facilitating information retrieval, knowledge recombination, and decision support. While these applications accelerate innovation cycles, they simultaneously obscure evidential provenance, compromise output reliability, and diffuse accountability when algorithmic insights fail. To address these vulnerabilities, this paper introduces the concept of epistemic resilience, defined as an organizational and ecosystem capability to preserve, adapt, and restore trustworthy knowledge processes amid technological disruption, uncertainty, and epistemic risk. Synthesizing literature across innovation management, organizational learning, knowledge management, social epistemology, research integrity, and human–AI collaboration, this study conceptualizes AI-driven innovation as a sociotechnical knowledge process wherein computational acceleration remains contingent upon the integrity of the underlying epistemic environment. We propose a governance framework structured around four interdependent pillars: epistemic culture and virtues; data and model governance; critical AI literacy and human–AI judgment; and aligned incentives and leadership. Operating across individual, team, organizational, and ecosystem levels, these pillars facilitate the prevention, detection, adaptation, and remediation of epistemic breakdowns. By prioritizing adaptive learning, accountability, trust, and systemic recovery over static oversight, this framework delineates epistemic resilience from adjacent domains such as research integrity, data governance, AI ethics, regulatory compliance, and conventional risk management. Ultimately, this paper establishes a conceptual foundation for trustworthy, AI-augmented innovation and outlines an empirical agenda for operationalizing and cultivating epistemic resilience within organizations.
DOI Link
ISSN
Publisher
Elsevier BV
Disciplines
Computer Sciences | Social and Behavioral Sciences
Keywords
Artificial intelligence, Epistemic resilience, Human–AI collaboration, Innovation management, Knowledge management, Trust
Scopus ID
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Recommended Citation
Ryan, James C.; Cappuccio, Massimiliano; Georgiadou, Effrosyni; and Lanteri, Alessandro, "Epistemic resilience in AI-driven innovation" (2026). All Works. 8421.
https://zuscholars.zu.ac.ae/works/8421
Indexed in Scopus
yes
Open Access
yes
Open Access Type
Gold: This publication is openly available in an open access journal/series