Introduction

Target Audience

Undergraduate and graduate students

Identified Learning Need

Entrepreneurship is a significant challenge for people who want to start a business. For college students, most of them are interested but delay action, thinking they must finish school first. Other barriers include lack of funding, support, and confidence, along with fear of failure and limited opportunities. Also, students do not understand entrepreneurship well because of their inadequate work experience (Iwu et al., 2020). For startup founders and career changers, they may find it difficult to perform key tasks in the early stage of entrepreneurship, which involves finding and assessing potential business ideas, and securing financial, material, human, and informational resources necessary to start the business (Seibert, Nielsen, & Kraimer, 2021, p. 1224).

Rationale for AI Assistance

Based on the student’s chosen business field, AI can facilitate immersive entrepreneurship simulations where users take on the role of entrepreneurs and engage with AI-driven characters acting as investors, customers, and suppliers. Immersive simulations powered by AI allow learners to engage in scenario-based learning, enhancing their ability to apply theoretical knowledge to real-world challenges (Huang, Spector, & Yang, 2007). Through these interactive scenarios, users can practice essential business negotiation skills in realistic environments. AI allows the creation of dynamic, real-time virtual scenarios tailored to individual learners’ needs. This flexibility supports diverse entrepreneurial activities, such as identifying business opportunities, evaluating risks, and managing resources. As Bell (2023) emphasizes, AI can foster more authentic learning experiences by providing students with immediate feedback, which is critical for developing decision-making and critical thinking skills​. Additionally, through simulated dialogues, role-playing, and other modes, generative AI can help students improve communication and problem-solving skills (Zheng, Shen, Chen, Che, & Zhu, 2024).

Modalities

1. Interactive:

• Decision Simulations: Users interact with the AI, make decisions, and see the consequences, which is a form of interactive learning.
• Negotiation and Communication Practice: Interacting with virtual characters to practice negotiation and communication skills.

2. Text-based:

• Theoretical Learning and Case Studies: Text-based materials are used to provide business theories, success stories, or failure cases, helping users understand the related concepts.
• Decision Prompts and Feedback: AI provides decision prompts, feedback, and suggestions in written form to help users reflect and improve.

3. Contextual Learning:

• Simulating Real Business Scenarios: Through scenario simulations, users face real business challenges (e.g., funding negotiations, customer needs analysis), helping them apply the knowledge they’ve learned to practice.

Evidence of Entrepreneurship Difficulties

• 50% of startups fail within five years due to funding shortages, market demand issues, and poor management; only 12% secure funding.
• Studies show students lack experience, and career changers face role identity conflicts.
• Paul Graham (Co-founder of Y Combinator) highlights the high trial-and-error costs for startups, especially in negotiations.

Competitive analysis

Conclusion: AI’s core strengths lie in dynamic high-fidelity scenario generation, real-time decision feedback, and cost-effective trial-and-error environments, addressing the limitations of traditional methods (rigidity, generalization, and resource dependency). This positions AI as a critical tool for building systemic entrepreneurial competencies.

Key Insights from Survey

• Motivation: Target users are driven by self-actualization, seeking to fulfill personal goals and values through entrepreneurship.
• Challenges: The main barriers are a lack of resources, management experience, and uncertainty about business opportunities.
• Learning Preferences: Users prefer active, social, and immersive learning methods—practical experiences and simulations.
• Needs: Users seek both theoretical and practical knowledge, emphasizing peer interaction, expert guidance, and case-based learning.
• Desired Features: Users value direct engagement with industry experts, interactive scenario analysis, and simulations focused on resource management.

Learner Needs

• Learners seek both theoretical and practical knowledge.
• Learners lack of resources, management experience, and uncertainty about business opportunities.
• Learners need expert guidance.

Personas

User Journey Map

Reference

Bell, R., & Bell, H. (2023). Entrepreneurship education in the era of generative artificial intelligence. Entrepreneurship Education, 6(3), 229-244.

Huang, R., Spector, J. M., & Yang, J. (2007). Artificial intelligence in education: Challenges and opportunities for sustainable development. Educational Technology Research and Development, 55(6), 675-689.

Iwu, C. G., Muresherwa, G., Nchu, R., & Eresia-Eke, C. E. (2020). University students’ perception of entrepreneurship as a career option. Academia, (20-21), 177-201.

Seibert, S. E., Nielsen, J. D., & Kraimer, M. L. (2021). Awakening the entrepreneur within: Entrepreneurial identity aspiration and the role of displacing work events. Journal of Applied Psychology, 106(8), 1224.

Zheng, K., Shen, Z., Chen, Z., Che, C., & Zhu, H. (2024). Application of AI-empowered scenario-based simulation teaching mode in cardiovascular disease education. BMC Medical Education, 24(1), 1003.