AI Opportunity Scoring Matrix
Move beyond gut feeling. Use this data-driven framework to systematically score your AI startup ideas and focus your energy on the opportunities with the highest potential for success.
| Sub-Category | Score (1-10) | Weighted Score | Scoring Guidelines |
|---|---|---|---|
| 1. Market Size & Growth Potential (Weight: 25%) | |||
| Total Addressable Market (TAM) | 0.00 | 1-2: Niche, shrinking market. 5-6: Established, slow-growth market. 9-10: Large, globally relevant, and growing market. | |
| Market Growth Rate (CAGR) | 0.00 | 1-2: Declining/flat market. 5-6: Moderate growth (5-10% CAGR). 9-10: Rapidly expanding market (>20% CAGR). | |
| Niche Accessibility | 0.00 | 1-2: Dominated by incumbents. 5-6: Competitive but with entry points. 9-10: Clearly defined, underserved niche. | |
| Section 1 Total: | 0.00 / 25 | ||
| 2. Founder-Market Fit (Weight: 20%) | |||
| Domain Expertise | 0.00 | 1-2: No experience. 5-6: Some professional experience. 9-10: Recognized expert who has lived the problem. | |
| Passion & Resilience | 0.00 | 1-2: A fleeting interest. 5-6: Genuinely interested. 9-10: An obsession you'd work on for a decade. | |
| Network Advantage | 0.00 | 1-2: No connections. 5-6: Some relevant contacts. 9-10: Deep network of customers, partners, investors. | |
| Section 2 Total: | 0.00 / 20 | ||
| 3. AI Differentiation Factor (Weight: 20%) | |||
| Core Value Proposition | 0.00 | 1-2: AI is a nice-to-have. 5-6: AI significantly improves an existing process. 9-10: The business cannot exist without AI. | |
| Competitive Moat | 0.00 | 1-2: Thin wrapper on a public API, easily replicated. 5-6: Unique workflow. 9-10: Proprietary process, difficult to copy. | |
| Data Moat Potential | 0.00 | 1-2: Public data only. 5-6: Personalizes experiences. 9-10: Creates powerful feedback loop where usage makes AI smarter. | |
| Section 3 Total: | 0.00 / 20 | ||
| 4. Monetization Viability (Weight: 15%) | |||
| Revenue Model Clarity | 0.00 | 1-2: No clear plan. 5-6: Standard SaaS model but unvalidated pricing. 9-10: Clear, tiered pricing aligned with value. | |
| Willingness to Pay | 0.00 | 1-2: Solves a minor inconvenience. 5-6: Addresses a known problem. 9-10: Solves a "hair-on-fire" problem customers are already paying to solve. | |
| Scalability of Model | 0.00 | 1-2: Revenue tied to manual effort. 5-6: Semi-automated. 9-10: Fully automated with near-zero marginal costs. | |
| Section 4 Total: | 0.00 / 15 | ||
| 5. Technical Feasibility (Weight: 10%) | |||
| No-Code/Low-Code Viability | 0.00 | 1-2: Requires custom models. 5-6: Partially prototyped. 9-10: Effective MVP can be built in weeks with no-code tools. | |
| Data Availability | 0.00 | 1-2: Requires massive, proprietary datasets. 5-6: Uses public data. 9-10: Relies on foundation models or user-generated data. | |
| MVP Simplicity | 0.00 | 1-2: Complex, multi-feature platform needed. 5-6: MVP has 3-4 core features. 9-10: Value tested with a single workflow. | |
| Section 5 Total: | 0.00 / 10 | ||
| 6. Risk Profile (Ethical & Regulatory) (Weight: 10%) | |||
| Regulatory Hurdles | 0.00 | 1-2: Heavily regulated space (e.g., medical diagnostics). 5-6: General regulations (GDPR/CCPA). 9-10: Low-regulation space. | |
| Data Privacy Complexity | 0.00 | 1-2: Requires highly sensitive data (medical, financial). 5-6: Uses standard customer data. 9-10: Minimal personal data required. | |
| Potential for Misuse | 0.00 | 1-2: High potential for harmful content. 5-6: Moderate potential needing guardrails. 9-10: Low risk of misuse. | |
| Section 6 Total: | 0.00 / 10 | ||
Final Opportunity Score
0 / 100