In the world of GenAI, few innovations have reshaped the ecosystem as rapidly and profoundly as the Model Context Protocol. Born from a simple insight at Anthropic in mid-2024, MCP addressed a fundamental challenge: how might we connect the growing constellation of AI models to the digital tools and data they need to be truly useful?

The chain reaction model for AI adoption illuminates how AI can transform organizations far beyond their initial implementation points. Just as one neutron can trigger a cascade of reactions in nuclear physics, strategic AI interventions at key points can create powerful ripple effects throughout an organization—amplifying value, accelerating innovation, and sometimes, if poorly managed, triggering organizational meltdowns.

Companies focused on AI feature development (e.g. offering an AI-powered app or service) often incur high variable costs to serve each customer or query, chiefly due to cloud compute usage and data processing. On the other hand, those in the infrastructure or data-management layer operate with high upfront costs but more scalable cost leverage. The result is a paradox, the AI Value Capture Paradox: AI application providers find their operational costs scaling nearly linearly with usage, whereas infrastructure providers enjoy economies of scale and can achieve better margins as utilization grows…