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TLDR: Dynamic Packaging as the Foundation for AI Monetization AI is rewriting the rules of software economics, value creation, and customer engagement. Dynamic pricing alone is not enough. Product leaders must embrace dynamic packaging —the modular, outcome-driven assembly of AI components, features, data, and technology assets—anchored in a robust commercial architecture that defines value metrics, monetization rules, and governance from the outset. Dynamic packaging is key

Software-as-a-Service (SaaS) pricing is built on four key fundamentals: product structure (value alignment), portfolio structure (customer alignment), pricing structure (metrics alignment), and cost structure (margin alignment). However, the rise of AI-driven platforms is fundamentally challenging these pillars. Here we examine how AI disrupts each pricing fundamental, with real-world examples. Value alignment: Customers continue to pay as they continue to benefit Traditional

Why Traditional SaaS Pricing Models Fall Short and How Commercial Architecture Must Lead for AI Success AI pricing is one of the toughest puzzles facing the software industry today. It’s not just that AI breaks all four pillars of SaaS pricing—it’s the deeper, architectural struggle at the heart of the problem. Specifically, the challenge lies in making the commercial architecture of a multi-product, AI-powered platform align with its existing portfolio and technical architec

AI pricing is not a tweak to existing SaaS models; it’s a structural problem that demands a new commercial architecture. AI breaks the four fundamentals of SaaS pricing— value, customer, metric, and margin alignment —and exposes an architectural mismatch: teams typically design AI on top of a technical architecture that was built for different value flows. The result is pricing that doesn’t map to outcomes, metrics that don’t reflect customer willingness to pay, and revenue m