The Adoption of AI-based Assistants in Startup Innovation: Configuring Human–AI Agency in Entrepreneurial Work

Advances in large language models have made AI-based assistants widely available for knowledge-intensive work, yet their role in entrepreneurial innovation remains poorly understood. This study examines how startup founders use AI-based assistants across innovation activities and what requirements founders articulate. We conduct semi-structured interviews with 19 founders of German startups and analyze their accounts through the lens of human-AI collaboration and digital agency. The findings reveal four task domains in which founders rely on AI-based assistants, each characterized by a distinct distribution of human and AI agency, and three interaction and control patterns that govern how founders calibrate delegation and oversight over time. These configurations clarify when AI-based assistants meaningfully augment entrepreneurial work, when their contribution remains limited, and when expectations are unmet. The study contributes to research on human-AI collaboration and digital entrepreneurship and informs the design of AI-enabled tools that better support early-stage innovation.