The generative AI boom has forced a hard reset on product roadmaps across the software industry. However, while engineering teams race to deploy LLMs and copilots, the billing engine often remains a silent bottleneck in the back office.
Moreover, legacy infrastructure is hitting a wall as companies shift from simple subscriptions to complex consumption models such as monetizing token usage, API calls, and compute time.
According to Shakir Karim, Senior Vice President of Product Management at Zuora, the problem is about the fundamental architecture of how organizations define a product. In a recent discussion on the state of monetization with ERP Today, Karim outlined why the era of the static SKU is ending and what needs to replace it.
The Breaking Point
For decades, billing systems were built on rigid logic. If organizations wanted to sell a software license in a new currency or with a slight pricing variation for a specific region, they created a new Stock Keeping Unit (SKU). That logic worked for static boxes. However, it collapses under the weight of AI consumption models.
“Legacy billing systems are typically built around static fields,” Karim explained. “The minute you introduce AI-driven usage, such as tokens or API calls, these systems require massive custom code just to keep up.”
The Shift: From Hard-Coding to Attributes
Karim noted that the solution lies in shifting from static definitions to dynamic attributes.
In Zuora’s vision of a modern Monetization Catalog, companies no longer need to duplicate SKUs for every scenario. “Instead, Dynamic Pricing changes this model by letting teams describe offers using flexible attributes, such as customer type, region, IP range, or usage characteristics, rather than duplicating SKUs for every scenario,” he said.
“This removes the operational drag of rigid product structures,” Karim added. “It allows pricing to evolve without a proportional increase in system complexity.”
Bridging the Product-Finance Divide
Perhaps the most significant friction point in SaaS monetization is the tug-of-war between speed and compliance.
Historically, a product leader’s idea for a pricing change was often killed by the reality of downstream reconciliation. If the billing system couldn’t track it, Finance wouldn’t approve it—or IT would be stuck maintaining custom hooks to make it work.
Karim argued that a unified catalog solves this dilemma by democratizing the billing engine. “The Zuora Monetization Catalog allows business users, such as pricing managers, to design, price, and launch offers within a set of governed rules,” he said.
Additionally, because the logic is unified, a rule changed in the catalog automatically propagates to the storefront, CPQ, billing, and revenue recognition.
“Revenue recognition doesn’t require manual updates because it queries the current catalog state when processing transactions,” Karim explained. “This ends the era of pricing living in one system while revenue rules live in disconnected spreadsheets.”
Unbundling the Good-Better-Best Tier
Finally, this architectural shift changes how software is packaged. “Features and Entitlements introduce a more granular way to define what customers actually get access to,” Karim observed. This creates new opportunities to unbundle platforms or tailor plans more precisely to customer needs.
He concluded, “Each tier becomes a curated set of entitlements rather than a fixed product. This makes it easier to adjust what sits in each tier, run targeted upsell tests, or introduce intermediate options without creating new SKUs.”
What This Means for ERP Insiders
Legacy SKU sprawl is an innovation blocker. Continuing to use legacy billing logic results in SKU Sprawl, leading to high operational costs because every pricing experiment requires engineering time to hard-code new SKUs. For ERP users, this means the system ceases to be an enabler and instead actively slows down business agility.
Structured metadata unlocks internal AI capabilities. Moving to a catalog built on structured metadata rather than brittle code is a prerequisite for AI readiness. When product data is machine-readable, organizations can deploy internal copilots. These AI agents can autonomously perform tasks that previously required manual auditing, such as detecting stale SKUs, generating product descriptions, and surfacing pricing insights.
Modernization preserves data lineage and compliance. A significant fear regarding migration—breaking historical reporting—is unfounded with modern architectures. New systems allow historical billing documents to remain anchored to their original data while new logic layers are added on top. This ensures that ERP users can innovate their pricing models without losing the data lineage required by auditors.
