Document Type

Article

Publication Date

Summer 5-1-2025

Abstract

This paper explores the transformative impact of artificial intelligence (AI) on organizational teamwork, decision-making, and resilience. This paper furthur reviews recent literature on the integration of Artificial Intelligence (AI) in various organizational functions, focusing on its impact on innovation management, leadership paradigms, and organizational resilience. We provide groundwork required to enhance frameworks that can integrate cognitive scaffolding with antifragile team dynamics, employing behavioral economics and neurocognitive principles. We introduce methodologies for enhancing team resilience through adaptive AI systems, cross-training interventions, and pre-mortem simulation techniques. The framework addresses key challenges in confirmation bias mitigation, cultural dimension alignment, and vigilance decrement prevention. This paper explores how cognitive scaffolding mechanisms within organizations enhance team antifragility, enabling dynamic adaptation and growth under stress.We further synthesize findings from studies exploring the adoption of generative AI tools like ChatGPT by innovation managers, the potential of AI in enhancing resilience for small businesses in the context of Industry 5.0, and the evolving role of leadership in the age of AI. Furthermore, we examine the significance of human factors such as emotional intelligence, empathy, and self-compassion in navigating the integration of AI and fostering innovation and resilience within teams and organizations. This review highlights the complex interplay between technological advancements and essential human capabilities in shaping the future of work and organizational success. Through systematic analysis of 32 peer-reviewed studies (2016-2025), we surveyed and found how AI cognitive scaffolding systems improve team antifragility by 214% when combined with human emotional intelligence. Our review by studying research reveals that hybrid AI-human decision models achieve 38% faster response times while maintaining 89% prediction accuracy in behavioral assessments. The paper introduces a novel cultural alignment metric (Cdiff ) for global teams and evaluates four STAR framework variants for AI-enhanced workforce development.

Program or Discipline Name

Computer and Information Sciences

Secondary Program or Discipline Name

Information Systems and Information Technology

Publication Title

International Journal of Computer Applications

Start Page No.

9

End Page No.

26

ISSN

0975-8887

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

DOI

10.5120/ijca2025925036

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