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.