ENTREPRENEURSHIP AND VENTURE CAPITAL

The course examines how entrepreneurs identify, validate, build, and finance ventures. Students develop an AI-enabled startup throughout the semester using customer discovery, MVP experimentation, quantitative validation, and venture capital frameworks.

Not requested

1. Opportunity Recognition and Evaluation Systematically identify, assess, and prioritize AI-enabled entrepreneurial opportunities by applying opportunity recognition frameworks, innovation theories, and market attractiveness criteria. 2. Customer Discovery and Validation Design and conduct customer discovery processes, including interviews, focus groups, and qualitative analyses, to identify customer pain points, validate assumptions, and generate evidence-based entrepreneurial insights. 3. Venture Design and Development Develop an AI-enabled venture concept by designing value propositions, business models, and minimum viable products (MVPs) using entrepreneurial, technological, and strategic management frameworks. 4. Quantitative Market Validation Design and implement quantitative validation studies, including surveys and market experiments, to evaluate customer demand, willingness to pay, product-market fit, and venture scalability. 5. Venture Capital Readiness and Investment Communication Critically evaluate venture growth potential, financing requirements, and investment attractiveness, and effectively communicate an evidence-based venture opportunity through professional investor-oriented reports and venture capital pitches.

Class Dynamic This is not a course about entrepreneurship; it is an entrepreneurship course. Students are expected to continuously test assumptions, gather evidence, iterate solutions, and build an AI-enabled venture. Weekly milestones and checkpoints mirror startup acceleration programs. Class Culture Feedback is direct, evidence-based, and action-oriented. Students are expected to engage with potential customers, test ideas outside the classroom, and continuously update their startup tracker. Search Fund Alternative Track Students who do not wish to develop a startup project may pursue a Search Fund project focused on Entrepreneurship Through Acquisition opportunity identification, industry attractiveness, target screening, and post-acquisition value creation.

Manuals: Blank (2013) Ries (2011) Neck, Neck & Murray (2018) Cheek (2024) Aulet (2024) Osterwalder & Pigneur (2010) Creswell (2021) Books and articles Drucker (1985) Gregersen, Christensen & Dyer (2009) Chesbrough (2003) Jacobides et al. (2018) Smith & Smith (2019) Professional readings Harvard Business Review AI & Entrepreneurship Collection McKinsey How to build businesses faster and better with AI (2026) BCG AI-First Companies Reports (2026) OECD Venture Capital and AI Reports (2021) World Economic Forum AI Entrepreneurship Reports (2025)

Entrepreneur Venture Project Students individually develop an AI-enabled venture. The venture must use AI as a core component of the value proposition rather than merely as a productivity tool. Students maintain a weekly tracker documenting: Opportunity hypotheses Customer insights Interview findings Market assumptions MVP iterations Survey results Product-market-fit indicators Venture capital readiness

The course assessment is structured as follows: Venture Creation Project: 30% and Final Examination: 70% The Venture Creation Project is composed of six equally weighted deliverables: Deliverable 1: Opportunity Recognition — 5% Deliverable 2: Customer Discovery — 5% Deliverable 3: Problem Validation — 5% Deliverable 4: AI MVP Development — 5% Deliverable 5: Quantitative Validation — 5% Deliverable 6: VC Investment Pitch — 5% The written final examination accounts for 70% of the final grade and is structured around the following areas: Part A: Entrepreneurship and Opportunity Recognition Part B: Customer Discovery and Validation Part C: AI Entrepreneurship Case Analysis Part D: Venture Capital and Financing Decisions

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