Have you considered the potential of shared infrastructure for AI and RAN workloads? If so, you’re not alone. A recent Heavy Reading survey indicated 82% of operators expect to see this kind of infrastructure deployment before the 6G cycle begins in 2030.
I’m Kai Mao, head of AI RAN strategy for 1Finity, here for an open dialogue about monetizing AI RAN for Enterprise.
What is the Business Case for AI-RAN?
While there is growing interest in AI RAN, there’s also some hesitancy. MNOs want to minimize investment and risk and are cautious about new revenue models.
So, what is the business case? In this case, MNOs minimize risk by investing and deploying according to actual customer opportunities.
AI RAN on shared infrastructure is the best way to meet Enterprise customer demands. Enterprise customers value AI in multiple applications, most often for data analytics and video surveillance; driven by specific needs such as safety, security, efficiency, and quality assurance.
Applying AI can improve business performance and customer satisfaction. Requirements are primarily driven by data protection and digital sovereignty. Business data is tightly protected in terms of storage and data access. This affects AI deployment and underlying infrastructure.
Connectivity is Critical
As AI develops from generative to agentic to physical applications, more dependence on connectivity will result, driving the need for reliability, mobility, latency and location awareness.
Shared compute infrastructure for AI and RAN workloads consolidates resources, maximizes pooling gains, enables cloud best practices, economies of scale, and monetization.
Monetization Models
AI RAN can enable MNOs to capture over-the-top revenue, which de-risks investment and improves return on investment. Three main monetization models are emerging:
- First, providing custom AI applications to enterprises, leveraging shared infrastructure to host applications for specific business needs.
- Second, segmenting available compute infrastructure for GPU as a Service directly to customers or on the open market.
- Third, pooling diverse compute capacity for AI as a Service, offering real-time inference for new AI applications.
How to Realize the Benefits of AI-RAN
With this in mind, how can MNOs realize these benefits in a scalable, repeatable manner?
This is where 1Finity comes in.
As a pioneer in AI RAN, we’ve collaborated with ecosystem partners to develop and build one of the world’s first full-stack AI RAN architectures, including radios, transport, servers, and customizable applications.
The solution’s pre-integrated, scalable, repeatable reference architecture eases deployment and allows MNOs to provide new AI services directly to Enterprise customers.
If you’re ready to start the journey now, you’re primed to get ahead of the competition. And we’re here to support you.
Let’s continue this open dialogue. Come talk to 1Finity.
