The rapid advancements in Artificial Intelligence (AI) are transforming educational landscapes and pedagogical frameworks across disciplines. In this conceptual paper, we explore the intersection between AI integration and entrepreneurial education, focusing on how AI-enhanced learning design can support the development of entrepreneurial mindsets in secondary and higher education. Entrepreneurship is increasingly recognized not merely as a vocational skillset but as a fundamental 21st-century competence encompassing creativity, innovation, opportunity recognition, and adaptive problem-solving. Yet, conventional pedagogical approaches often struggle to replicate the dynamic, uncertain, and iterative nature of real-world entrepreneurial processes. This paper argues that AI technologies can help bridge this pedagogical gap by enabling learning environments that are personalized, adaptive, and experience-rich.

We introduce a conceptual framework grounded in constructivist learning theory, experiential education, and the emerging paradigm of AI-enhanced learning design. Central to our proposal is the AIEE Model (Artificial Intelligence for Entrepreneurial Education), which comprises four interrelated pillars:
(1) Intelligent Personalization,
(2) Interactive Simulation & Decision-Making,
(3) Generative Co-Creation, and
(4) Reflective Feedback Loops.

Each dimension reflects how AI capabilities can be systematically embedded in the design of entrepreneurship learning experiences to enhance learners’ engagement, autonomy, and critical thinking.

The paper presents a best-practice guide tailored for educators, instructional designers, and curriculum developers, outlining effective strategies for the integration of AI-driven tools such as conversational agents, virtual pitch coaches, business model generators, and intelligent assessment systems. These tools are examined through applied use cases and instructional scenarios that simulate authentic entrepreneurial challenges—from ideation and market analysis to pitch preparation and iterative prototyping.

Furthermore, the paper discusses the ethical and instructional design implications of incorporating AI into entrepreneurship education. Attention is given to algorithmic transparency, data privacy, and the need to safeguard the human-centric elements of creative learning. The proposed model promotes a balanced approach to AI-enhanced learning design, where AI systems serve as facilitators and augmenters of human potential, rather than as replacements for instructional interaction. The educator’s role is redefined as a learning architect and entrepreneurial mentor who orchestrates AI capabilities in alignment with pedagogical goals.

This conceptual contribution aims to inform both educational theory and practice by offering a structured, theoretically grounded, and practically relevant model for integrating AI into entrepreneurship education. It contributes to the discourse on the responsible and pedagogically meaningful use of emerging technologies in learning design and provides actionable insights for stakeholders seeking to foster entrepreneurial competence in the digital era. The paper is particularly relevant for scholars, educators, policy-makers, and instructional designers involved in curriculum innovation, digital transformation, and the future of entrepreneurship education.

Keywords: Artificial Intelligence in Education, Entrepreneurial Mindset, AI-Enhanced Learning Design, Experiential Learning.