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Abstract Artificial intelligence (AI) is increasingly embedded within entrepreneurial practice, reshaping opportunity recognition, innovation processes, and venture-level decision-making. This transformation creates a clear need for entrepreneurship education (EE) to adopt theoretically coherent and developmentally structured approaches to AI integration. Although scholarship recognises the growing importance of AI-related knowledge, applied integration, and responsible judgement, integrative frameworks explaining how these capabilities can be progressively cultivated within EE remain limited. This paper addresses that gap by developing the AI-Enabled Entrepreneurial Learning Progression Framework. Building on the established about–for–through tradition, the framework reconceptualises AI integration as a staged capability-development process rather than a discrete curricular addition. It articulates how AI capability can be systematically developed from conceptual literacy and analytical understanding to applied integration and evaluative judgement, and ultimately to entrepreneurial capability, identity formation, and responsible agency within AI-enabled venture contexts. By aligning learning purpose, learning development, pedagogical orientation, AI positioning, curriculum focus, teaching activities, and assessment across stages, the framework advances a theory-building account. It explains how AI reshapes the developmental logic of EE. It provides a structured foundation for curriculum design and assessment alignment and establishes a platform for future empirical research on AI-enabled entrepreneurial capability formation.
Bell et al. (Thu,) studied this question.