Insurers often treat AI adoption like a vendor selection exercise. AI models evolve too quickly for long-term dependency on any single model. Switching models currently requires retooling integrations and rebuilding workflows. Vendors retire older models faster than ever with little notice. Insurance workflows demand different kinds of intelligence for different tasks. No single AI model performs every enterprise task well. Domain-specific models are growing in interest and capability. Model independence allows deploying and switching models without operational disruptions. Competitive advantage in insurance comes from institutional intelligence, not the model itself. A model-independent platform enables matching the best model to each task.

• 50%+ of enterprise generative AI models to be domain-specific by 2027
• 1% of enterprise generative AI models were domain-specific in 2024