Last week on the Value Threading blog, I published an article titled “The Massive Unfunded AI Liability No One Is Talking About.” That piece suggested that the true costs and future liabilities of large language models (LLMs) and AI are not fully understood or accounted for.
A key proposal in that article was the foundational need to accurately measure costs as a starting point for any optimization model, using chargebacks to users or internal divisions.
This challenge is intensified by an inevitable market change: the massive, ongoing shift to B2B e-commerce. As enterprises move complex purchasing and service consumption online, they demand the same real-time visibility, self-service capabilities, and granular usage tracking they experience as consumers. Legacy billing systems and manual sales processes cannot keep pace with the velocity and complexity of modern B2B digital service delivery, making the need for an agile solution more critical than ever.
That proposal resonated with some of my “Telco” friends this week, who raised a similar challenge regarding cloud services. Telcos are increasingly reselling bundled cloud and AI solutions—specifically on the B2B side—combining software, connectivity, and infrastructure into single, complex offerings.
This raises a critical question: Can companies simultaneously manage complex internal chargebacks while billing customers for the same granular usage?
Implementing this structure would provide near-real-time business metrics while driving new e-commerce revenue streams.
The Dual-Purpose Advantage
The ability to deploy a dual-purpose system is where significant operational efficiency lies. We are discussing a model that provides “two birds with one stone” billing: it enables accurate, auditable external invoicing for B2B customers, while simultaneously generating the necessary metrics for internal chargebacks and cost attribution across different business units. This holistic approach ensures that every AI token consumed or API call made is accounted for financially, linking revenue directly to operational cost metrics in real time.
Introducing “Edge Billing”
The term “Edge Billing” has been used in specific tech circles, but it is far from a mainstream concept. Given the industry’s current needs, I believe it is time to push this concept into the open.
Why now? Because so many companies need to expand their e-commerce offerings in both B2B and B2C markets. AI solutions are a prime opportunity, but there are also numerous associated cloud-based PaaS (Platform-as-a-Service) solutions—and specifically in Telcos, NaaS (Network-as-a-Service) or IaaS (Infrastructure-as-a-Service) offerings.
The Power of Consumption-Based Models
This aligns closely with the shift toward consumption-based billing.
Imagine a set of APIs that embed customer charge models and internal chargeback models, running concurrently. This is, in effect, performing billing and costing at the edge—right at the point where the digital consumption occurs. Add the necessary security and orchestration, and you can deliver a robust marketplace of offerings with near-real-time data that shows effectiveness and profitability.
The key outcome here goes beyond optimizing the sales and operational models. The cost and timeline to deploy such a solution are significantly lower than attempting the extensive customization required for legacy internal billing or BSS (Business Support Systems). Sure, those core systems are still required to complete the final order-to-cash process—handling payments, cash reconciliation, revenue management, and compliance. But Edge Billing provides the agile, real-time metering that legacy systems cannot easily support, bridging the gap between innovative new services and established financial operations.
