Enhancing venture support through a hybrid human–AI mentoring model: a mixed-methods study of growth stages and resource needs in the Japanese context

Purpose This study aims to investigate the synergistic potential of human mentors and generative artificial intelligence (GenAI) in supporting venture firms across various growth stages. By examining the evolving resource needs of startups, the research develops a hybrid mentoring model designed to address these requirements within the distinctive institutional framework of the Japanese venture support ecosystem. Design/methodology/approach Adopting an exploratory sequential mixed-methods design, this study provides nuanced insights into this emerging phenomenon. The first phase consisted of a quantitative survey with 16 portfolio firms of a government-backed investment fund in Japan to identify shifting mentoring needs. This was followed by a qualitative phase involving semi-structured interviews with four veteran mentors, analyzed through the steps for coding and theorization method. The conceptual framework integrates the resource-based view, social capital theory and mentoring theory to articulate the complex interplay between artificial intelligence (AI)-driven analytical support and human-centric guidance. Findings Quantitative results reveal a significant shift from technology-focused needs in the seed stages to governance and human resource priorities during growth phases. Qualitative findings indicate that while GenAI enhances information processing and structural social capital, human mentors provide inimitable experiential knowledge and relational social capital, specifically by fostering affective trust. The evidence suggests that AI acts as a resource optimizer rather than a substitute for human intuition, establishing a foundational perspective for validating these dynamics across diverse institutional settings. Originality/value The study proposes a pioneering “hybrid human–AI mentoring model” tailored to the Japanese context, where long-term trust and government-led coordination play a pivotal role. It contributes to the entrepreneurship literature by defining the critical boundary between AI's analytical efficiency and human empathy, thereby providing a strategic roadmap for venture capital firms and incubators to optimize their support systems in similar institutional settings.