Human–AI collaboration in knowledge ecosystems: a multidisciplinary review, integrative framework and future directions

Abstract

Purpose The advancement of artificial intelligence (AI) is transforming knowledge ecosystems, reshaping the creation, dissemination and application of knowledge. This study aims to delve into the powerful synergy between human expertise and AI, illustrating how computational intelligence amplifies decision-making and sparks groundbreaking innovation in complex and data-rich business environments. Design/methodology/approach Through a systematic review of 101 scholarly articles, this study synthesizes key insights and presents a comprehensive framework integrating socio-technical, ethical and policy dimensions of AI adoption. Findings Human–AI collaboration in knowledge ecosystems is shaped by antecedents (trust, AI capabilities, organizational context, user expertise); mediators (cognitive alignment, explanation quality, emotional engagement); and moderators (user attitudes, task complexity, transparency, ethics). Positive configurations enhance decision quality, innovation and user satisfaction, while risks such as power imbalances, deskilling and algorithmic opacity can undermine collaboration and productivity. The authors devise an integrative antecedent–mediator–moderator–outcome framework, emphasizing human-centered design, contextual integration and equity. They also highlight the need for more empirical and theory-driven research in the domain. Originality/value By bridging fragmented perspectives, this study advances theoretical understanding and illuminates practical pathways for leveraging AI to augment human ingenuity, uphold ethical imperatives and catalyze innovation in rapidly shifting knowledge landscapes.

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