Building a useful prototype is becoming easier. Building a durable and trustworthy company remains difficult.
Technical risks
Models can produce incorrect information, behave inconsistently, misunderstand context, or fail when the environment changes. Latency, cost, privacy, and dependency on a model provider also matter.
Business risks
A feature may be copied by a larger platform. Customers may experiment without adopting. The product may save time without creating enough financial value to justify a purchase.
Regulatory and social risks
Healthcare, finance, employment, education, and government applications may affect rights or safety. Data use, explanations, auditability, and human appeal mechanisms become central product requirements.
Sources of defensibility
- Exclusive or difficult-to-create data
- Deep integration into customer workflows
- Distribution and trusted customer relationships
- Domain expertise and regulatory knowledge
- Continuous evaluation using real outcomes
- Network effects or marketplaces
- Operational excellence in handling exceptions
A proprietary model is one possible advantage, but it is not the only one—and often not the first one.