AI-Enabled Practice-Based Learning: Integrating the Entrepreneurship Competency Framework in Business Education

Artificial intelligence (AI) is reshaping business practice and redefining how future professionals engage with complex, ill-structured organisational problems. While AI adoption in higher education is accelerating, there remains limited empirical understanding of how competency frameworks can structure students’ use of AI within authentic, practice-based learning environments. This gap presents challenges for educators seeking pedagogical approaches that balance innovation with ethical and reflective practice. This paper presents a qualitative case study using a cohort of an undergraduate business module that integrates AI-enabled practice-based learning with the Entrepreneurship Competency Framework (ECF). The ECF is introduced as a shared language and reflective scaffold that supports students’ inquiry, decision-making, and collaborative judgement. The research involved 72 students working in teams on real organisational challenges, students used generative AI tools to support problem identification, ideation, analysis, and iterative refinement, while critically engaging with responsible AI considerations including ethical use, bias awareness, and data integrity. Data were generated through student reflective outputs and focus groups with undergraduate students and business educators. This enabled analysis of how AI-enabled practice-based learning influenced engagement, judgement, and perceptions of relevance to professional practice. The findings illustrate how competency frameworks such as the ECF can scaffold students’ critical and responsible engagement with AI in complex, real-world problem-solving contexts. Also, AI could be positioned not only as an object of learning but as a sociomaterial actor that mediates sense-making and shapes inquiry within the learning environment. The paper proposes an empirically grounded pedagogical model that conceptualises the interdependence of practice-based learning, generative AI, and competency-based scaffolding. The model offers practical and transferable guidance for educators and institutions designing AI-enabled curricula that prepare students for a future ethical, collaborative, and judgement-oriented demands of AI-mediated work.