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As Wall Street and global research firms release a flood of AI-driven industry disruption forecasts, corporate planning teams at domestic SMEs (50-300 employees) must report their company's AI risks to the board. However, professional consulting costs 30-50 million KRW (~$22,500-$37,500) per engagement, and without internal analytical capability, Report preparation takes 2-4 weeks.
A SaaS that takes a company's industry sector, revenue structure, and workforce composition as input, then auto-generates a customized AI risk Report (executive summary, department-level impact assessment, response roadmap) based on the latest AI trend research and industry-specific AI replacement rate data. Quarterly update reports are automatically published.
| N Novelty | 1-5 | How uncommon the service is in market context. |
| U Urgency | 1-5 | How urgently users need this problem solved now. |
| M Market | 1-5 | Market size and growth potential from proxy indicators. |
| R Realizability | 1-5 | Buildability for a small team with realistic constraints. |
| V Validation | 1-5 | Validation signal quality from competition and demand data. |
| Tech Complexity | / 40 | Difficulty of core implementation stack. |
| Data Availability | / 25 | Practical availability and cost of required data. |
| MVP Timeline | / 20 | Expected time to ship a usable MVP. |
| API Bonus | / 15 | Bonus for viable public API leverage. |
| Competition | / 20 | Signal quality from competitor landscape. |
| Market Demand | / 20 | Demand proxies from search and mention patterns. |
| Timing | / 20 | Fit with current shifts in tech, behavior, and regulation. |
| Revenue Signals | / 15 | Reference evidence for monetization viability. |
| Pick-Axe Fit | / 15 | How well the concept serves participants in a trend. |
| Solo Buildability | / 10 | Practicality for lean-team implementation. |