The Carrier Ethernet market is undergoing a significant shift as AI workloads demand new performance validation from network infrastructure.
Mplify, the alliance formerly known as MEF (Metro Ethernet Forum), is responding with a dual certification strategy that preserves decades of carrier investment while creating a pathway for AI-ready transport validation.
This week, the organization announced two certification tracks: Carrier Ethernet for Business, available now as a rebrand of MEF 3.0 certification, and Carrier Ethernet for AI, targeted for a second-quarter 2026 launch. The move addresses a fundamental question facing service providers: how to monetize existing Ethernet infrastructure for AI transport alongside the industry’s focus on high-bandwidth wavelength services.
“Three years ago, we said we’re going to start pivoting to NaaS, and all of this work is supporting that, including the AI element,” Kevin Vachon, chief operating officer of Mplify, told Network World.
Carrier Ethernet for Business: Rebrand with recertification path
Carrier Ethernet for Business maintains identical technical requirements to MEF 3.0 certification. Service providers already certified under MEF 3.0 can transition to the Mplify certification at no additional cost.
The transition offers a practical benefit: recertification with updated test dates. Some existing MEF 3.0 certifications are five years old. The new program allows providers to show fresh certification records without infrastructure changes.
“We didn’t want to just put a different sticker on it,” Vachon said. “We wanted to give the opportunity for operators to recertify their infrastructure so at least you’ve now got this very competitive infrastructure.”
Testing occurs on live production networks. The automated testing platform can be completed in days once technical preparation is finished. Organizations pay once per certification with predictable annual maintenance fees required to keep certifications active. Optional retesting can refresh certification test records.
Carrier Ethernet for AI
The Carrier Ethernet for AI certification takes the business certification baseline and adds a performance layer specifically designed for AI workloads. Rather than creating a separate track, the AI certification requires providers to first complete the Carrier Ethernet for Business validation, then demonstrate they can meet additional stringent requirements.
“What we identified was that there was another tier that we could produce a standard around for AI,” Vachon explained. “With extensive technical discussions with our membership, our CTO, and our director of certification, they identified the critical performance and functionality parameters.”
The additional validation focuses on three key performance parameters: frame delay, inter-frame delay variation, and frame loss ratio aligned with AI workload requirements. Testing uses MEF 91 test requirements with AI-specific traffic profiles and performance objectives that go beyond standard business service thresholds.
The program targets three primary use cases: connecting subscriber premises running AI applications to AI edge sites, interconnecting AI edge sites to AI data centers, and AI data center to data center interconnections.
The certification validates transport performance across geographically distributed, multi-provider environments. With hundreds of carriers maintaining standards-based network-to-network interfaces, the interoperability element becomes relevant for AI workloads spanning multiple carrier domains.
The certification focuses on inference workloads rather than training.
“Right now, the first generation is really on the inference workloads and not on the training side,” Vachon said. A future certification tier may address training requirements.
Market outlook
The certification program could help service providers make the most of their existing Carrier Ethernet infrastructure for AI applications. The $57 billion annual Carrier Ethernet market has built an extensive global footprint over two decades.
Mid-tier operators may use certification for differentiation. “You have those that will use this type of certification to show differentiation. ‘Hey, I might be small or midsize, but I can meet all of these,'” Vachon said.
Larger carriers may evaluate certification more selectively. “You have others to say, ‘I know I can meet all of these standards, and I may not need to get certified against them,'” Vachon noted.
The program connects to Mplify’s broader NaaS for AI strategy. The alliance’s LSO API standards support automated provisioning and management of network services, potentially enabling dynamic bandwidth allocation for distributed AI workloads. Mplify’s technical leadership is in early discussions with organizations focused on data center interconnect and GPU networking.
“Leadership is great if you put out blueprints and white papers and things like that, but if you have real, live work that directly supports that, then you’re doing something,” Vachon said.