The AI trust factor: an MCA analysis of automation and decision-making in entrepreneurship

This study conducts a comprehensive examination of the interrelationships among artificial intelligence (AI), trust, entrepreneurship, and decision-making in orga - nizational settings, employing a Multiple Correspondence Analysis (MCA) of 31 peer-reviewed articles published between 2020 and 2025. Building on a systematic literature review and the HOMALS technique, the research identifies four thematic clusters that structure the contemporary conceptual space of AI in business environ - ments: ethical-social governance, strategic-technological core, digital infrastructure, and decision-oriented automation. The findings expose a latent structural tension between technocratic efficiency and ethical legitimacy, highlighting the need for hybrid models that integrate algorithmic capabilities with principles of responsible governance. Within this framework, variables such as user acceptance, transpar - ency, and hybrid cognitive architectures emerge as key dimensions for understand - ing and designing AI-mediated decision processes in entrepreneurial contexts. The study proposes a conceptual model that articulates these dimensions and provides a theoretical basis for future investigations and practical initiatives aimed at the reflexive, responsible, and sustainable implementation of intelligent technologies in contemporary business ecosystems. Highlights ● This study maps the conceptual structure of research on artificial intelligence, trust, and decision-making in entrepreneurial contexts using Multiple Corre - spondence Analysis. The findings show that the literature is organized around interrelated configurational patterns rather than isolated constructs, with trust- related dimensions acting as central mechanisms linking technological adoption, governance, and decision legitimacy. The analysis reveals a persistent tension between technocratic logics focused on automation and efficiency and ethical– institutional logics emphasizing transparency, accountability, and legitimacy. Within this structure, entrepreneurial research increasingly converges toward Accepted: 15 January 2026 / Published online: 7 February 2026 © The Author(s) 2026 The AI trust factor: an MCA analysis of automation and decision-making in entrepreneurship María Fernández-Fernández1 · Álvaro Hernández-Tamurejo1 · Paula González-Padilla1 Extended author information available on the last page of the article 1 3 International Entrepreneurship and Management Journal (2026) 22:34 hybrid human–AI decision architectures, underscoring the relevance of augmen- tation strategies over full automation. Methodologically, the study demonstrates the value of MCA as an exploratory tool for structuring fragmented and rapidly evolving research domains, offering insights relevant for both future scholarship and entrepreneurial practice.