Ericsson goes with custom silicon (rather than Nvidia GPUs) for AI RAN
Ahead of MWC Barcelona 2026, Ericsson unveiled its initial suite of AI-RAN products at a pre-event briefing in London, emphasizing a strategy anchored in proprietary, purpose-built silicon to enhance radio access network (RAN) performance. While the wireless industry is finally moving to virtualized/cloud RAN utilizing general-purpose processors from Intel, Ericsson is defending its continued investment in custom silicon for specialized, high-performance tasks.
Concurrently, the company is demonstrating a strong push toward software-defined flexibility, ensuring its proprietary RAN algorithms and AI-native software are portable across diverse, open silicon platforms. Ericsson was exploring the use of Nvidia’s Arm-based Grace CPU, rather than the Hopper-branded GPU, but has opted for custom silicon (ASICs) instead.
Ericsson’s RAN portfolio currently diverges into two primary architectures. The majority of its footprint relies on ASICs—developed through internal design and external partnerships with Intel. The alternative is Cloud RAN, which pairs Ericsson’s software stack with Intel Xeon processors. Despite the industry’s promise that virtualization would decouple hardware from software, Intel remains Ericsson’s sole silicon partner for production-grade deployments.
This hardware lock-in was underscored during Ericsson’s recent London event, where documentation confirmed “commercial support” exclusively for Intel, while AMD, Arm, and NVIDIA remain relegated to “prototype support.” Despite years of industry rhetoric regarding silicon diversity in the vRAN ecosystem, tangible progress remains stalled. Furthermore, the integration of AI into RAN software introduces new layers of complexity that may further entrench hardware dependencies.
Industry observers remain skeptical of Ericsson’s ambition for a “unified software stack” across heterogeneous hardware platforms. While hardware-software disaggregation is achievable in the higher layers (L2/L3), Layer 1 (L1)—the most compute-intensive portion of the stack—remains heavily optimized for specific silicon. Ericsson’s initial strategy relied on the portability of L1 code across x86 architectures (via AMD) or the adoption of Arm’s SVE2 (Scalable Vector Extension) to match Intel’s AVX-512 capabilities. However, achieving high-performance parity across these platforms without significant refactoring remains a significant engineering hurdle.
A critical bottleneck in PHY Layer (L1) processing is Forward Error Correction (FEC), which traditionally necessitates dedicated hardware acceleration. Ericsson initially addressed this using a lookaside acceleration model, offloading FEC tasks to discrete PCIe-based Intel accelerators. In recent iterations, Intel has moved toward a more integrated System-on-Chip (SoC) approach, embedding the accelerator directly onto the CPU die (e.g., vRAN Boost).
The primary challenge for Ericsson lies in achieving silicon parity across the AMD and NVIDIA ecosystems. While AMD’s FPGA-based accelerators have faced scrutiny regarding power efficiency, NVIDIA’s GPU-based offloading was previously viewed as cost-prohibitive for standard FEC. However, the rise of AI-RAN has recalibrated these economic models, as telcos explore the dual-use potential of GPUs for both RAN and AI workloads. Emerging platforms, such as Google’s Tensor Processing Units (TPUs), have also been identified by Ericsson leadership as viable long-term options.
Despite ambitions for a unified “single software track,” Ericsson’s technical roadmap suggests a more nuanced reality. While L2 and higher layers aim for a universal codebase across hardware platforms, L1 necessitates concurrent feature development and platform-specific tailoring. As CTO Erik Ekudden noted, maximizing the efficiency of advanced accelerators requires a degree of software customization that challenges the ideal of total hardware-software disaggregation.
Ericsson executives are keen to avoid what Executive VP Per Narvinger describes as a “native implementation,” which would create silicon vendor lock-in. To prevent that the company is prioritizing Hardware Abstraction Layers (HALs). Key initiatives include the adoption of the BBDev (Baseband Device) interface to decouple RAN software from underlying silicon. Furthermore, potential integration with NVIDIA’s CUDA platform is being evaluated to provide the necessary abstraction for heterogeneous compute environments, though this remains contingent on broader industry standardization.
Ericsson’s AI strategy mirrors this modular approach. By leveraging AI as a functional abstraction layer, the company aims to simplify software portability across diverse platforms while maintaining AI control loops for real-time network management. Unlike competitors tethered to high-TDP GPUs, Ericsson maintains that AI-RAN is commercially viable on general-purpose and purpose-built silicon. Recent London showcases highlighted AI-driven gains in spectral efficiency, channel estimation, and beamforming without external acceleration. A production-ready AI-native link adaptation model recently delivered a 10% spectral efficiency improvement in field tests and is now integrated into the latest baseband portfolio.
As for radios—a domain less susceptible to full virtualization—Ericsson is embedding Neural Network Accelerators (NNA) directly into its radio-unit ASICs. These programmable matrix cores are optimized for Massive MIMO inference, enabling sub-millisecond beamforming and channel estimation while adhering to strict site power envelopes. New AI‑ready radios, feature Ericsson custom silicon with neural network accelerators. They are said to boost on‑site AI inference capabilities in Massive MIMO radios, enabling real‑time optimization and full stack, fully distributed AI.
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References:
https://www.lightreading.com/5g/ericsson-does-ai-ran-minus-nvidia-in-push-for-5g-silicon-freedom
RAN silicon rethink – from purpose built products & ASICs to general purpose processors or GPUs for vRAN & AI RAN
Analysis: Nokia and Marvell partnership to develop 5G RAN silicon technology + other Nokia moves
China gaining on U.S. in AI technology arms race- silicon, models and research
Marvell shrinking share of the RAN custom silicon market & acquisition of XConn Technologies for AI data center connectivity
Intel FlexRAN™ gets boost from AT&T; faces competition from Marvel, Qualcomm, and EdgeQ for Open RAN silicon
Lumen launches Multi-Cloud Gateway (MCGW) and expands metro fiber network after selling consumer FTTH business to AT&T
Lumen Technologies has announced a new Multi-Cloud Gateway (MCGW) and expanded its metro fiber optic network across 16 major U.S. markets, delivering up to 400G b/sec connectivity to support high-speed AI data processing. This initiative provides a software-defined, self-service platform for secure, private, and flexible connections between enterprise data centers and cloud providers.
Lumen says the new MCGW product and expanded fiber footprint will simplify how data moves across hybrid environments by bringing both centralized multi-cloud routing and high-capacity private metro connectivity. The result will be a more consistent, controllable networking foundation for AI and other modern workloads. This expansion is part of a broader strategy where Lumen plans to reach 58 million fiber miles by 2031 to meet the soaring demand for AI-ready infrastructure.
“Moving data across hybrid environments is a lot like managing air traffic – you need clear routes, predictable timing, and the ability to adjust when conditions change. Most legacy networks weren’t built for that level of coordination,” said Jim Fowler, Lumen chief technology and product officer. “With our expanded network fabric, Lumen gives enterprises a way to move data securely, effortlessly, and consistently across clouds, data centers, and edge locations, designed to reduce the complexity that hold AI-driven operations back.”
Multi-Cloud Gateway: Multi-Cloud Gateway (MCGW) is a core element of Lumen’s shift to cloud-based telecom. Built as a software-defined, self-service routing layer on Lumen’s global fiber network, MCGW provides private, high-capacity connectivity among enterprises, hyperscalers and emerging cloud platforms. It turns traditional telecom interconnection into a programmable cloud fabric, allowing customers to dynamically connect cloud-to-cloud and cloud-to-enterprise environments, optimize traffic for performance and cost, and support advanced use cases such as AI workload distribution and real-time data exchange. By unifying connectivity, routing and policy, MCGW is designed to reduce operational complexity, speed time to service and lower total cost of ownership.
Lumen Multi-Cloud Gateway:
Image credit: Lumen Technologies
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Metro Ethernet & IP Services: Expanded high-capacity, dedicated connectivity across 16 U.S. markets, delivering up to 100Gbps between regional data centers, campuses, and edge locations and up to 400Gbps at key cloud data centers in those markets. This enables fast, secure movement of massive datasets for AI training, analytics, replication, and disaster recovery.
Recently upgraded markets include Northern Virginia; Atlanta; Chicago; Columbus; Dallas; Denver; Kansas City; Las Vegas; Los Angeles; Minneapolis; New York City; Phoenix; Portland; San Antonio; San Jose; and Seattle.
“AI is reshaping network design, pushing enterprises to move from experimentation to execution with architectures that reduce latency, cost variability, and operational complexity,” said Courtney Munroe, Vice President, Worldwide Telecommunications Research at IDC. “As workloads become more distributed and performance sensitive, organizations are rethinking how they connect edge sites, data centers, and multiple clouds, and Lumen’s network fabric shows how programmable networks can deliver more consistent data movement.”
The business impact is immediate and practical for industries scaling their AI ambitions:Financial Services: Keep risk, payments, and fraud workloads synchronized across multiple clouds with centralized policy control for lower latency and more predictable performance.
- Retail: Improve business agility by accelerating data movement across cloud and enterprise environments, so analytics keep pace with changing demand.
- Healthcare: Maintain data separation, support telehealth services, imaging and analytics, disaster recovery, and manage research workloads across institutions and resource centers.
- Manufacturing: Connect regional facilities and cloud environments to enable real-time analytics and predictive maintenance.
- Multi-Cloud Gateway (MCGW): Launched and available as of February 17, 2026, as a software-defined, self-service routing layer.
- Metro Network Expansion: Currently live across 16 major U.S. markets (including New York, Chicago, and Los Angeles), offering up to 400 Gbps at key cloud data centers.
- Internet On-Demand: Expanded in late 2025 to over 10 million new business locations, providing “cloud-like” connectivity scalability within minutes.
- Wavelength RapidRoutes: Available for deployment in just 20 business days, significantly faster than industry standard turn-up times.
- Microsoft: Chosen to expand Microsoft’s network capacity to support surging demand for Azure AI services. Microsoft utilizes Lumen’s Private Connectivity Fabric (PCF) for custom network architecture between data centers.
- Google Cloud: Partnered to modernize Network-as-a-Service (NaaS) offerings. This allows Lumen-managed SD-WAN and security services to be hosted directly in Google Cloud regions.
- Palantir Technologies: A multi-year alliance formed in October 2025 to combine Lumen’s connectivity fabric with Palantir’s Foundry and AI Platform (AIP), enabling enterprises to deploy AI faster in multi-cloud environments.
- Other Hyperscalers: Lumen has secured approximately $8.5 billion in private connectivity deals with companies including Amazon Web Services (AWS) and Meta to support their AI model training.
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On February 2nd, Lumen announced that it completed the sale of its Mass Markets fiber-to-the-home business in 11 states, including Quantum Fiber, to AT&T for $5.75 billion in cash. The sale includes substantially all of the related consumer fiber access network and customer relationships in those 11 states, which serve more than 1 million fiber customers and reaches more than 4 million enabled fiber locations. The completed transaction is another strategic milestone in Lumen’s transformation into the leading enterprise digital networking services company built for the multi-cloud, AI-driven economy rather than for consumer fiber access.
As part of the completed transaction, Lumen will retain assets that will continue to serve as the foundation of its enterprise transformation, including all national, regional, state, and metro level fiber backbone network infrastructure, central offices and associated real estate. In addition, Lumen is retaining and caring for its copper-based consumer services, which continue to provide a strong ongoing financial contribution to Lumen. The enterprise and wholesale fiber customers will remain with Lumen in all geographies.
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About Lumen Technologies:
Lumen is unleashing the world’s digital potential. We ignite business growth by connecting people, data, and applications – quickly, securely, and effortlessly. As the trusted network for AI, Lumen uses the scale of our network to help companies realize AI’s full potential. From metro connectivity to long-haul data transport to our edge cloud, security, managed service, and digital platform capabilities, we meet our customers’ needs today and as they build for tomorrow.
When networks shift from constraint to enabler, organizations can move faster, scale with confidence, and unlock greater innovation. To learn more about these products and availability timelines, visit Multi-Cloud Gateway and Connectivity Services.
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References:
https://assets.lumen.com/is/content/Lumen/lumen-multi-cloud-gateway-data-sheet
Lumen: “We’re Building the Backbone for the AI Economy” – NaaS platform to be available to more customers
Lumen deploys 400G on a routed optical network to meet AI & cloud bandwidth demands
Lumen and Ciena Transmit 1.2 Tbps Wavelength Service Across 3,050 Kilometers
Analysts weigh in: AT&T in talks to buy Lumen’s consumer fiber unit – Bloomberg
Lumen Technologies to connect Prometheus Hyperscale’s energy efficient AI data centers
Microsoft choses Lumen’s fiber based Private Connectivity Fabric℠ to expand Microsoft Cloud network capacity in the AI era
Lumen, Google and Microsoft create ExaSwitch™ – a new on-demand, optical networking ecosystem
ACSI report: AT&T, Lumen and Google Fiber top ranked in fiber network customer satisfaction
Taara Lightbridge Pro: an ultra reliable wireless optical communications system for 5G mobile backhaul
Google moonshot factory X graduate Taara [1.] is launching Lightbridge Pro, a wireless optical communications system designed to deliver 99.999% (“five nines”) carrier-grade uptime for 20 Gbps backhaul, addressing weather-related reliability issues in Free Space Optical Communication (FSOC).
Lightbridge Pro is designed for seamless integration into carrier-grade networks, including mobile backhaul and mission-critical infrastructure. By integrating intelligent optical switching directly into the hardware, it automatically reroutes traffic to fiber or RF backups during, for example, heavy fog or rain.
Note 1. Tara says that for the last eight years, they have been developing novel technology that uses beams of light to deliver high-speed, secure connectivity where fiber and wireless can’t – bringing abundant access to everyone, everywhere.
“As demand for data soars, existing connectivity solutions are reaching their limits. What if we could harness the power of light to deliver a better, faster, more efficient connection, without the need for cables?” Mahesh Krishnaswamy, Founder and CEO.
Key Features and Impact:
Carrier-Grade Reliability: Lightbridge Pro is purpose-built for high-availability requirements of 5G mobile backhaul,, and city-wide network providers.
Intelligent Switching: The system ensures seamless, near-instantaneous, switching between optical and backup connections (like RF) to maintain continuity.
Performance: It delivers up to 20 Gbps full-duplex capacity, bridging gaps where fiber installation is too costly or difficult.
Global Application: Already deployed in over 20 countries, the technology is used in dense urban, rural, and disaster recovery scenarios.
Operational Efficiency: The system includes comprehensive Fault, Configuration, Accounting, Performance, and Security (FCAPS) management, suitable for integration with existing Operations and Business Support Systems (OSS/BSS).
Deployment and Use Cases: Tara’s platform is aimed at large-scale network operators and mission-critical communications, particularly in dense urban environments or rough terrain where laying fiber is not economically viable.
Current Partners: Taara Lightbridge is already deployed in more than 20 countries, from dense urban cores to remote terrain to disaster recovery scenarios. Carriers already using Taara’s technology include Airtel, T-Mobile, SoftBank, Digicel, and Liquid Intelligent Technologies. T-Mobile previously deployed Taara units for high-capacity backhaul at Coachella and the Albuquerque Balloon Festival.
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Taara is showcasing these new solutions at Mobile World Congress (MWC) Barcelona 2026 where the start-up will also be announcing a new photonics-based wireless optical system designed for even greater density and scalability.
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Editor’s Analysis:
Taara’s Lightbridge Pro looks like a serious, carrier-minded evolution of free-space optics (FSO) for 5G backhaul, but its real value will hinge on how well the “five nines” claim holds up under diverse atmospheric and operational conditions in the field.
Risks and open questions:
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SLA realism: “Five nines” across mixed optical/RF paths is a strong claim; operators will want multi-year availability data by climate region, plus clear modeling of residual outage during extreme events where both optical and RF paths can degrade.
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Operational complexity: Even with integrated switching and FCAPS, adding a new transport technology introduces planning, monitoring, and skillset overhead versus staying on homogeneous fiber/microwave.
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Regulatory and spectrum: Where RF is the backup, spectrum licensing, interference management, and coordination with existing microwave/E‑band layers will affect total cost and deployment speed, and those aspects are not detailed in the product material.
Overall assessment:
For 5G mobile backhaul, Lightbridge Pro is best viewed as a targeted tool for high-value, hard-to-fiber routes, and for rapid-capacity or temporary deployments, rather than a universal replacement for fiber or microwave. If Taara’s integrated protection switching performs as advertised at scale, it meaningfully advances FSO from “interesting niche” to a credible part of a multi-layer transport strategy for carriers and city-scale operators.
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References:
https://www.taaraconnect.com/post/introducing-lightbridge-pro#
https://www.taaraconnect.com/product/lightbridge-pro
https://www.taaraconnect.com/about
Google X spin-out Taara and Digicomm International partner to offer high speed wireless communications
Dell’Oro: Mobile Core Networks +15% in 2025; Ookla: Global Reality Check on 5G SA and 5G Advanced in 2026
Palo Alto Networks and Google Cloud expand partnership with advanced AI infrastructure and cloud security
Google’s Project Suncatcher: a moonshot project to power ML/AI compute from space
Google Cloud announces TalayLink subsea cable and new connectivity hubs in Thailand and Australia
Dell’Oro: RAN Market Stabilized in 2025 with 1% CAG forecast over next 5 years; Opinion on AI RAN, 5G Advanced, 6G RAN/Core risks
A recently published report from Dell’Oro Group reveals that the Radio Access Network (RAN) market ended the year on a stable note, with stronger than typical 3Q to 4Q seasonality. Fourth-quarter results were consistent with the broader stabilization trend that shaped the RAN market throughout the year, resulting in stable revenue trends for the full year.
“Taking into consideration that the RAN market lost around a fifth of its value between 2022 and 2024, this improved stability in 2025 represents a welcome shift in market conditions,” said Stefan Pongratz, Vice President for RAN market research at the Dell’Oro Group. “Helping to explain the improved sentiment are the more favorable regional mix, easier comparisons, and the weaker USD. Even so, we have not made any material changes to the short-term outlook and still expect the market to be mostly flat in 2026,” continued Pongratz.
Additional highlights from the 4Q 2025 RAN report:
- Revenue rankings did not change in 2025. The top 5 RAN suppliers by worldwide revenue are Huawei, Ericsson, Nokia, ZTE, and Samsung.
- RAN vendor dynamics shifted in 2025—leading vendors strengthened their positions, while smaller suppliers adjusted their strategies. As a result, overall RAN market concentration increased during the year.
- Overall market concentration, as measured by the Herfindahl–Hirschman Index, reached a 10-year high in 2025.
- In 2025, Huawei and Nokia gained ground, Ericsson and Samsung were stable, and ZTE’s RAN revenue share fell.
- The fundamentals that shape the RAN market have not changed, and the long-term trajectory discussed in the most recent 5-year forecast still holds (1% CAGR, 2025-2030).
- The short-term outlook is mostly unchanged, with total RAN expected to remain stable in 2026.
RAN is not a growth market over time (0% CAGR 2020-2025 in nominal US $). However, it can go through periods of higher and lower capital intensity ratios as operators align investment needs with the availability of new spectrum/technologies and demand for capacity. The base case forecast is for stable RAN and capex trends, resulting in further improvements in capital intensity ratios before 6G investments commence towards the end of the forecast period. Worldwide RAN revenue is projected to grow at a 1% CAGR over the next five years, as rapidly declining LTE capex will offset continued 5G and initial 6G investments. RAN as a share of wireless capex is expected to average in the 20 to 25 percentage share range over the forecast period.
Dell’Oro Group’s RAN Quarterly Report offers a complete overview of the RAN industry, with tables covering manufacturers’ and market revenue for multiple RAN segments including 5G NR Sub-7 GHz, 5G NR mmWave, LTE, macro base stations and radios, small cells, Massive MIMO, Open RAN, and vRAN. The report also tracks the RAN market by region and includes a four-quarter outlook. To purchase this report, please contact us by email at [email protected].
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Editors Opinion:
This author believes that the only RAN growth driver over the next 5 years will be investments in 5G SA core networks, which finally is starting to be deployed more than 5G NSA networks as we noted in today’s companion IEEE Techblog post. Omdia forecasts that 5G SA core network software spending will grow at an 8.8% CAGR between 2025 and 2030, making it a primary driver of investment. Continued 5G investments by global telcos are largely being offset by sharply declining 4G-LTE investments, leading to a “stable” rather than a growing RAN market.
Neither AI RAN, 5G Advanced, or Open RAN will be significant RAN market growth drivers:
- 5G Advanced (5G-A): 5G Advanced is widely considered a key part of the roadmap toward 6G. While some operators are focusing on it, its initial impact on overall global RAN revenue is expected to be more incremental rather than a massive boom in the next 2-3 years. If 5G-Advanced is seen by operators as “incremental” and 6G is legally/technically bound to a 2030/2031 ITU-R standards and 3GPP spec finalization, there is very little “must-have” radio hardware for a network operator to buy before 2030 at the earliest.
- AI-RAN: While AI-RAN is viewed as a key tool for improving efficiency and reducing energy costs (operational expenditure), its immediate impact on capital investment (Capex) in RAN equipment is likely to be slower. However, some, like Samsung, argue that AI-RAN is already driving optimizations in 2026. AI-RAN is primarily an OpEx play. Network operators are buying software and specialized silicon to lower their energy bills and automate frequency management. While this is critical for their survival, it doesn’t create a new “coverage wave” of RAN spending. It’s simply a “treading water” investment.
- Open RAN: has not led to increased RAN sales or multi-vendor equipment in the same RAN. Rather, it is a procurement shift, not a market expander.
There may be pockets of RAN growth in 5G-Advanced for specific performance needs, 5G private networks, and AI-enabled efficiency tools. However, we believe that the global RAN market will continue to stagnate till 6G network are deployed in early 2031.
Stefan had forecast that “cumulative 6G RAN investments over the 2029-2034 period are projected to account for 55 to 60% of the total RAN capex over that time period.” However, 6G capex does not translate into 6G RAN revenue until 6G is actually deployed!
Any earlier 6G deployment will be BEFORE the 5G RAN (IMT 2030 RIT/SRITs) and IMT 2030 Frequency arrangements standards are approved by ITU-R in late 2030 or early 2031 as IMT 2030 recommendations. Note that 3GPP Release 21 marks the official start of its normative 6G work. While the specific milestones for Release 21 are to be decided by June 2026, it is widely expected to produce the first formal 6G RAN technical specifications by late 2028 or early 2029 and submit them to ITU-R WP 5D via ATIS. Therefore, any 6G RAN equipment shipped before the 2030 ITU seal of approval would be based on pre-standardized or early 3GPP specifications that may require later alignment and hardware/software updates.
–>No rational wireless network operator wants to deploy thousands of “6G-ready” sites in 2029 only to find that the ITU-R IMT 2030 RIT/SRITs and/or Frequency Arrangements finalized in late 2030 require a hardware filter change or a different sub-carrier spacing to meet global interference requirements.
Hopefully, 3GPP will have finalized its 6G core network specs during the same time period so that 6G RANs will be complemented with 6G core networks- unlike the initial 5G RAN rollouts which had 4G evolved packet cores (5G NSA).
Potential Repeat Problem of No 6G Core Network Standard:
It’s highly likely that 3GPP will once again (like with 5G) not submit their 6G core network specs to ITU-T which is responsible for non-radio aspects of wireless networks. That means that 3GPP effectively operates as a silo for the 6G Core Network (refusing ITU-T oversight),so there will likely be no unified global regulatory mandate for the “6G system” as a whole—only for the “radio” (ITU-R IMT 2030 recommendations). This might allow operators to delay 6G SA Core deployments indefinitely, which in turn kills the business case for buying new 5G-Advanced or AI-RAN hardware.
Google Gemini: If the 6G Core Network isn’t standardized in a way that allows operators to actually monetize these new radio architectures, it doesn’t matter if the RAN is “Open,” “AI-enabled,” or “Advanced.” It’s still just a cost center on a stagnant balance sheet. If the “brain” (6G Core) doesn’t support the “limbs” (6G RAN), the market may not buy the limbs and 6G RAN sales will disappoint, just as 5G RAN sales did. Many carriers are still struggling to recoup the billions spent on 5G deployment so are seriously concerned about the 6G ROI.
| Feature | 5G Challenge | 6G Challenge |
|---|---|---|
| Spectrum | Mid-band & mmWave (24-52 GHz) | Sub-THz & THz (>100 GHz) |
| Connectivity | Massive IoT (1M devices/km²) | Internet of Senses (10M devices/km²) |
| Architecture | Cloud-native | AI-native & “Cell-free” MIMO |
| Primary Goal | Enhanced Mobile Broadband | Convergence of Physical & Digital worlds |
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References:
https://www.linkedin.com/feed/update/urn:li:activity:7422420902362988544/
6G Capex Ramp to Start Around 2030, According to Dell’Oro Group
Dell’Oro: Mobile Core Networks +15% in 2025; Ookla: Global Reality Check on 5G SA and 5G Advanced in 2026
Dell’Oro: RAN market stable, Mobile Core Network market +14% Y/Y with 72 5G SA core networks deployed
Omdia on resurgence of Huawei: #1 RAN vendor in 3 out of 5 regions; RAN market has bottomed
Dell’Oro Group: RAN Market Grows Outside of China in 2Q 2025
Dell’Oro: AI RAN to account for 1/3 of RAN market by 2029; AI RAN Alliance membership increases but few telcos have joined
Omdia: Huawei increases global RAN market share due to China hegemony
Network equipment vendors increase R&D; shift focus as 0% RAN market growth forecast for next 5 years!
vRAN market disappoints – just like OpenRAN and mobile 5G
Dell’Oro: Mobile Core Networks +15% in 2025; Ookla: Global Reality Check on 5G SA and 5G Advanced in 2026
A recent Dell’Oro market research report estimates that 4G/5G Mobile Core Network (MCN) revenues rose 15% YoY in 2025, which was the fastest growth since 2014. For the first time, the 5G MCN market accounted for 50% share of the total MCN market.
Editor’s Note: The 4G and 5G Non Standalone (NSA) mobile core network market (Evolved Packet Core) is experiencing long-term decline as investments are finally shifting toward 5G standalone (SA) networks.
“In 2025, the MCN market recorded its highest year-over-year revenue growth rate since 2014,” stated Dave Bolan, Research Director at Dell’Oro Group. “This was driven by record-setting growth rates in all market segments: 4G MCN (highest since 2019), 5G MCN (highest since 2022), and Voice Core (highest since 2007). 4G MCN gains came from Caribbean and Latin America (CALA) and Europe, Middle East, Africa (EMEA) regions; 5G MCN from all regions; and Voice Core, primarily from Asia Pacific and EMEA regions.
“5G MCNs led the way in 2025 growth, as 5G Standalone (5G SA) networks reached an inflection point and moved towards mass market appeal, as more 5G SA networks expand in population coverage in urban, suburban, and rural areas. Voice Core was the next major contributor to growth in 2025, driven by planned 3G MCN shutdowns, which required upgrades from Circuit Switched Core to IMS Core, and IMS Core modernization to a cloud-native IMS Core for VoNR in 5G SA networks. Meanwhile, 4G MCNs expanded due to subscriber growth in Africa and South America,” added Bolan.
Additional highlights from the 4Q 2025 Mobile Core Network and Multi-Access Edge Computing Report include:
- The top four vendors (Huawei, Ericsson, Nokia, and ZTE) posted very strong growth rates in 2025. Collectively, they accounted for about the same amount of market share as in 2024.
- The Multi-access and Edge Computing (MEC) market segment (a subsegment of the 5G MCN market) attained the highest growth rate of any MCN segment in 2025, with the China region remaining the dominant region for MEC implementations.
- Standard-setting bodies, vendors, and Mobile Network Operators (MNOs) communities are collaborating to expand the ecosystem with new products, applications, and monetization features that are expected to deliver future benefits.
- Examples include RedCap radios, which reduce the cost of IoT devices for consumer wearables and industrial applications; network slicing for both mission-critical and on-demand applications; IMS data channels to increase monetization opportunities and enhance user experience; and Open APIs that enable developers to scale their applications across all MNOs, attracting the app development community.
- Agentic AI is expected to change data traffic patterns and alter the duration that subscribers remain connected to the network as agents operate on their behalf. This could represent a paradigm shift in the future, requiring increased MCN capacity, expanded vendor opportunities, and enhanced monetization for MNOs through pricing tiers.
The Dell’Oro Group Mobile Core Network & Multi-Access Edge Computing Quarterly Report offers complete, in-depth coverage of the market with tables covering manufacturers’ revenue, shipments, and average selling prices for Traditional Packet Core, Evolved Packet Core, 5G Packet Core, Policy, Subscriber Data Management, Signaling, Circuit Switched Core, and IMS Core by geographic regions. To purchase this report, please contact us at [email protected].
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Related: The second edition of Ookla and Omdia’s report on the global state of 5G Standalone core network confirms that the technology has moved beyond launch announcements into an execution-driven phase. By the close of 2025, the “coverage gap” between major economic blocs had narrowed, but a more consequential “capability gap” has emerged, reflecting divergent spectrum strategies, investment depth, and the extent to which operators have moved beyond baseline SA deployment toward end-to-end network optimization.
For government and regulatory bodies, 5G Standalone (SA) has evolved into a high-stakes strategic imperative. The intersection of national competitiveness, digital sovereignty, and AI readiness is fundamentally reshaping Capex priorities across Tier-1 markets.
- User Equipment (UE) Performance: Impact of 5G SA on battery life and the transition to Voice over New Radio (VoNR).
- Application-Layer QoE: Benchmarking latency and jitter for cloud-native and gaming infrastructure.
- Commercial Monetization: A review of the first commercial deployments of Network Slicing, Enterprise SLAs, and 5G-Advanced (Release 18) segmentation.
- Geopolitical Drivers: Assessing how sovereign AI strategies in the GCC and legislative shifts in Europe are dictating the global SA evolutionary path.
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5G Core network investment is accelerating as monetization transitions from concept to selective execution:
Omdia’s latest forecasts confirm the industry’s shift toward software-defined core capability as the primary driver of next-cycle investment. Global 5G SA core network software spending is projected to grow at an 8.8% CAGR between 2025 and 2030, with EMEA leading at 16.7%, significantly outpacing North America (5.5%) and Asia & Oceania (4.2%). This reflects EMEA’s later position in the deployment cycle, as the region is entering its period of peak 5G core adoption, while North America’s 5G core spending trajectory is expected to have peaked in 2025 following the commercial launches by AT&T and Verizon. By end of Q3 2025, 83 operators worldwide had deployed 5G core networks, with 5G core investment accounting for 63.6% of global core network function software spending.
5G Core Investment Accelerates Across Regions:
- 5G SA availability based on Speedtest® sample share reached 17.6% in Q4 2025, up modestly from 16.2% a year earlier, indicating that roughly one in six 5G Speedtests worldwide now occurs on a 5G standalone network. The headline global median SA download speed of 269.51 Mbps represents a 52% premium over non-standalone networks, though this figure masks significant regional variation driven by spectrum allocation depth, carrier aggregation maturity, and user-plane engineering.
- Asia leads in 5G availability: China continues to dominate with 80.9% 5G SA sample share and over 10 million 5G Advanced subscribers.
- Globally, 5G SA connections delivered a 52% download speed premium to 5G NSA (mostly an artifact of rich spectrum allocation and lower network load) and improved median multi-server latency by over 6% compared to NSA. However, this year’s report finds that a standalone core migration alone does not guarantee a better end-user experience. Quality of experience analysis reveals a nuanced picture: SA improves video and cloud infrastructure latency in Europe versus NSA, but underperforms NSA for gaming latency within the same region. North America records the lowest absolute SA cloud and gaming latency, consistent with dense hyperscaler adjacency and mature interconnect ecosystems.
- The Gulf Cooperation Council (GCC) was the global 5G SA performance leader, with the UAE setting the speed benchmark Led by e& and du’s aggressive 5G Advanced deployments, the delivered the world’s fastest 5G SA median download speeds in Q4 2025 at 1.13 Gbps, nearly five times that of Europe. The UAE alone reached a median of 1.24 Gbps on SA networks, a speed that would be considered exceptional even for full-fiber broadband in developed markets. The deployment of four-carrier aggregation and enhanced MIMO technology, coupled with the strategic allocation of premium mid-band spectrum to the SA network, demonstrates the performance ceiling that a fully realized 5G SA architecture can achieve.
- South Korea followed at 767 Mbps, driven by wide 3.5 GHz channel bandwidth, with the U.S. at 404 Mbps following the completion of nationwide SA deployments by all three Tier-1 operators. Europe, at 205 Mbps, trails all developed regions, though the region’s SA networks still deliver a 45% download speed premium over NSA, confirming the performance value of the SA transition where material spectrum depth is allocated.
Europe’s 5G SA sample share more than doubled from 1.1% to 2.8% between Q4 2024 and Q4 2025, driven by accelerated deployments in Austria (8.7%), Spain (8.3%), the United Kingdom (7.0%), and France (5.9%). These four markets now account for the vast majority of European SA connections. The United Kingdom and France registered the strongest year-on-year acceleration in Europe, each gaining 5.3 percentage points, reflecting the impact of investment-linked merger conditions and competition in the United Kingdom, as well as targeted R&D policy support in France.
Among European markets, France (41ms to cloud endpoints), Austria (48ms), and Finland (50ms) demonstrate what is achievable where backbone quality, peering density, and routing discipline are strong. These outcomes reflect an underappreciated end-to-end network stack optimization dividend, encompassing data-center proximity, fiber backhaul depth, and user-plane topology, rather than a pure “SA dividend” alone.
However, Europe still trails North America by 27% and emerging Asia by 30%. At the global level, the U.S. remains the largest accelerator in absolute terms over the last year, with SA sample share rising 8.2 percentage points to 31.6% year-on-year, driven by the sequential rollout of SA across all Tier-1 operators beyond T-Mobile. Firmware fragmentation, where handset OEMs gatekeep SA network access pending individual carrier certification, and tariff structures that fail to incentivize migration from NSA, remain the primary barriers to faster European adoption.
The report also presents early evidence that battery life is a tangible consumer benefit of 5G SA. In the UK, devices on EE’s 5G SA network recorded median discharge times approximately 22% longer than those on 5G NSA, with O2 showing an 11% advantage. These gains likely stem from features like SA’s unified control plane, which eliminates the dual-connectivity overhead of NSA configurations.
Consumer strategies now span speed tiers (primarily Europe), 5G network slicing (Singapore, France, and the U.S.), and 5G Advanced segmentation packages (China). Enterprise 5G network slicing presents the much larger long-term revenue opportunity, with T-Mobile’s SuperMobile representing the first nationwide commercial B2B slicing service in the U.S. Countries with coordinated regulatory frameworks, implementing clear coverage obligations, investment incentives, or infrastructure consolidation policies with deployment remedies, consistently outperform those with fragmented or reactive approaches, reinforcing the report’s finding that policy has emerged as a primary competitive differentiator in 5G SA outcomes globally.
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References:
MCN Market Roared Back in 2025 With 15 Percent Growth, According to Dell’Oro Group
https://www.ookla.com/articles/5g-sa-2026
Dell’Oro: RAN market stable, Mobile Core Network market +14% Y/Y with 72 5G SA core networks deployed
AT&T deploys nationwide 5G SA while Verizon lags and T-Mobile leads
Ericsson CEO’s strong statements on 5G SA, WRC 27, and AI in networks
Ookla: Uneven 5G deployment in Europe, 5G SA remains sluggish; Ofcom: 28% of UK connections on 5G with only 2% 5G SA
Ericsson reports ~flat 2Q-2025 results; sees potential for 5G SA and AI to drive growth
Téral Research: 5G SA core network deployments accelerate after a very slow start
Google Fiber and Nokia demo network slicing for home broadband in GFiber Labs
Analysts: Telco CAPEX crash looks to continue: mobile core network, RAN, and optical all expected to decline
Global 5G Market Snapshot; Dell’Oro and GSA Updates on 5G SA networks and devices
Dell’Oro: Mobile Core Network market has lowest growth rate since 4Q 2017
ITU-R M.[IMT-2030.EVAL] & ITU-R M.[IMT-2030.SUBMISSION] reports: Evaluation & Submission Guidelines for 6G RIT/SRITs (6G)
Backgrounder:
As stated for years in IEEE Techblog posts, ITU-R Working Party 5D (WP 5D) is responsible for all International Mobile Telecommunications (IMT) terrestrial radio interface technology (RIT/SRIT) reports and standards, e.g. 3G, 4G, 5G (IMT 2020) and 6G (IMT 2030).
5D has developed the minimum technical performance requirements and the evaluation criteria for IMT 2020 (5G) and will do so now for IMT 2030 (6G) along with other reports and standards described in this article
While any ITU member can propose IMT 2030 RIT/SRIT candidate standards, it is expected that they will principally come from 3GPP which contributes their specs to 5D via ATIS.
Standards for the non-radio aspects of 5G (e.g. core network, security, network slicing, etc) and 6G were supposed to be promulgated by ITU-T, but 3GPP (which develops those specifications) years ago decided NOT to liaise their specs with ITU-T.
–>Please see References at the bottom of this article for more information.
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ITU-R M.[IMT-2030.EVAL] – 6G RIT/SRIT Evaluation Criteria:
The 5D WG Technology aspects/SWG Evaluation is working on a report which will provide guidelines for the procedure, the methodology and the criteria (technical, spectrum and service) to be used in evaluating the candidate IMT-2030 radio interface technologies (RITs) or Set of RITs (SRITs) for a number of test environments. These test environments are chosen to closely simulate more stringent radio operating environments.
The evaluation procedure is designed in such a way that the overall performance of the candidate RITs/SRITs may be fairly and equally assessed on a technical basis. It ensures that the overall IMT-2030 objectives are met. This Report provides, for proponents, developers of candidate RITs/SRITs and independent evaluation groups, the common evaluation methodology and evaluation configurations to evaluate the candidate RITs/SRITs and system aspects impacting the radio performance.
–>This report is scheduled to be finalized at the WP 5D Meeting No. 52 (Geneva, 27 May-5 June 2026).
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ITU-R M.[IMT-2030.SUBMISSION] – 6G RIT/SRIT Submission Guidelines:
The draft new 5D Report ITU-R M.[IMT-2030.SUBMISSION], originating from the 5D July 2025 meeting, defines the submission guidelines, templates, and evaluation methodology for 6G Radio Interface Technologies (RITs/SRITs). The report focuses on enabling technology proposals for IMT-2030 which are to be submitted from February 2027 to February 2029 for 5D evaluation and approval.
- Submission & Evaluation Guidelines: The report serves as the official guide for submitting candidate Radio Interface Technologies (RITs) or Sets of Radio Interface Technologies (SRITs) for IMT-2030.
- Structure: It is modeled after earlier reports like M.2411 (for 5G), defining the evaluation criteria, procedures, and templates for 6G technologies.
- Technical Requirements: It outlines minimum performance requirements (MPRs) for 6G, including advanced capabilities like artificial intelligence, energy efficiency, and joint requirements.
- Timeline: The report is central to the 2027-2030 timeline, aiming for the first submissions at the 54th WP 5D meeting (Feb 2027) and final submission by early 2029.
- Context: It aligns with the ITU-R M.2160 framework (the “6G Vision”), which encompasses six usage scenarios: immersive communication, hyper-reliable low-latency communication, massive communication, ubiquitous connectivity, AI-integrated communication, and integrated sensing and communication.
WP 5D Workplan for IMT 2030 RIT/SRITs:
As previously noted, 5D will accept and evaluate IMT 2030 candidate RIT/SRIT submissions starting at 54th meeting of WP 5D, currently planned for February 2027. The final deadline for submissions is 12 calendar days prior to the start of the 59th meeting of WP 5D in February 2029. The evaluation of the proposed RITs/SRITs by the independent evaluation groups and the consensus-building process will be performed throughout this two year time period and thereafter. Subsequent calendar schedules will be decided according to the submissions of proposals to 5D.
WP 5D meetings in 2030 will focus on the final stages of evaluating, adopting, and approving 6G technology submissions, aiming for approval of the final IMT-2030 recommendation in late 2030. The 5D tentative meeting schedule for 2030:
- Meeting No. 62 (February 2030): 1 Finalize Addendum 6 to Circular Letter taking into account the draft new Report ITU-R M.[IMT-2030. OUTCOME]. 2 Review and update the work plan, if necessary.
- Meeting No. 63 (June 2030): 1 Develop and finalize Addendum 7 to Circular Letter taking into account completion of the draft new Recommendation ITU-R M.[IMT 2030.SPECS].
- Meeting No. 63 (October 2030): Finalize standards before potential approval by ITU-R SG 5 in November 2030 or early 2031.
References:
ITU-R WP 5D Meeting Reports (TIES access required)
https://www.itu.int/en/events/Pages/Calendar-Events.aspx?sector=ITU-R&group=R23-WP5D
https://www.itu.int/en/ITU-R/study-groups/rsg5/rwp5d/imt-2030/pages/default.aspx
https://www.itu.int/en/ITU-R/study-groups/rsg5/rwp5d/imt-2030/Pages/submission-eval.aspx
Roles of 3GPP and ITU-R WP 5D in the IMT 2030/6G standards process
ITU-R WP 5D Timeline for submission, evaluation process & consensus building for IMT-2030 (6G) RITs/SRITs
ITU-R WP5D IMT 2030 Submission & Evaluation Guidelines vs 6G specs in 3GPP Release 20 & 21
Highlights of 3GPP Stage 1 Workshop on IMT 2030 (6G) Use Cases
ITU-R WP 5D reports on: IMT-2030 (“6G”) Minimum Technology Performance Requirements; Evaluation Criteria & Methodology
ITU-R: IMT-2030 (6G) Backgrounder and Envisioned Capabilities
Verizon’s 6G Innovation Forum joins a crowded list of 6G efforts that may conflict with 3GPP and ITU-R IMT-2030 work
Ericsson and e& (UAE) sign MoU for 6G collaboration vs ITU-R IMT-2030 framework
ITU-R WP5D invites IMT-2030 RIT/SRIT contributions
NGMN issues ITU-R framework for IMT-2030 vs ITU-R WP5D Timeline for RIT/SRIT Standardization
IMT-2030 Technical Performance Requirements (TPR) from ITU-R WP5D
Should Peak Data Rates be specified for 5G (IMT 2020) and 6G (IMT 2030) networks?
China vs U.S.: Race to Generate Power for AI Data Centers as Electricity Demand Soars
The International Energy Agency (IEA) forecasts that in the next five years, the global demand for power (electricity) is set to grow roughly 50% faster than it did during the previous decade – and more than twice as fast as energy demand overall. That tremendous increase in demand is due to power hungry AI data centers. There’s also electric cars and buses, electric-powered industrial machines, and electric heating of homes.
Global AI growth will be contingent on generating more power for data centers:
- Global data center power demand is now expected to rise to a record 1,596 terawatt-hours by 2035 – +255% increase from 2025 levels.
- The U.S. is set to remain the leader in energy consumption with a +144% surge in demand over this period, to 430 terawatt-hours.
- China’s demand is projected to rise +255%, to 397 terawatt-hours.
- European demand is expected to surge +303%, to 274 terawatt-hours.
- New data centers coming online between now and 2030 will need more than 600 terawatt-hours of electricity. This is enough to power ~60 million homes.
Power for AI Data Centers: China vs U.S.:
China is currently ahead of the United States in generating and building out power infrastructure to support AI data centers, a phenomenon sometimes described by industry observers as an “electron gap.”
China’s rapid, centralized expansion of electricity generation—including both massive renewable projects and traditional, dispatchable power—has created a significant capacity advantage in the race to support AI workloads, which are increasingly limited by energy availability rather than just chip access.
Key factors in China’s power advantage for AI include:
Massive Generation Growth: Between 2010 and 2024, China’s power production increased by more than the rest of the world combined. In 2024 alone, China added 543 gigawatts of power capacity—more than the total capacity added by the U.S. in its entire history.
Significant Surplus Capacity: By 2030, China is projected to have roughly 400 gigawatts of spare power capacity, which is triple the expected power demand of the global data center fleet at that time.
“Eastern Data, Western Computing” Initiative: China is actively shifting energy-intensive data centers to its resource-rich western regions (like Inner Mongolia) while powering them with surplus renewable energy, such as wind and solar.
Lower Costs and Faster Buildouts: Data centers in China can pay less than half the rates for electricity that American data centers do. Furthermore, projects in China can move from planning to operation in months, compared to years in the U.S. due to faster permitting and fewer regulatory hurdles.
Conclusions:
While the U.S. currently leads in advanced AI chips and model development, it is facing a severe “energy bottleneck” for new data centers, with some requiring over a gigawatt of power. U.S. power demand has remained relatively flat for 20 years, resulting in a lag in building new capacity, whereas China has traditionally built power infrastructure in anticipation of high demand. Morgan Stanley has forecast that U.S. data centers could face a 44-gigawatt electricity shortfall in the next three years.
Despite China’s advantage in energy, U.S. export controls on high-end AI chips (such as Nvidia’s GPUs) have acted as a significant constraint on China’s actual AI compute power. This has led to a situation where the U.S. has the best “brains” (chips) but limited power to run them, while China has the “muscle” (energy) but limited access to top-tier AI brains.
However, the rapid improvements in Chinese AI models (such as DeepSeek), which are more energy-efficient and optimized for lower-tier hardware, may help mitigate this constraint.
References:
https://www.iea.org/reports/electricity-2026
https://x.com/KobeissiLetter/status/2023437717888250284
Big tech spending on AI data centers and infrastructure vs the fiber optic buildout during the dot-com boom (& bust)
Analysis: Ethernet gains on InfiniBand in data center connectivity market; White Box/ODM vendors top choice for AI hyperscalers
Fiber Optic Boost: Corning and Meta in multiyear $6 billion deal to accelerate U.S data center buildout
How will fiber and equipment vendors meet the increased demand for fiber optics in 2026 due to AI data center buildouts?
Analysis: Cisco, HPE/Juniper, and Nvidia network equipment for AI data centers
Networking chips and modules for AI data centers: Infiniband, Ultra Ethernet, Optical Connections
Nvidia CEO Huang: AI is the largest infrastructure buildout in human history; AI Data Center CAPEX will generate new revenue streams for operators
Analysis & Economic Implications of AI adoption in China
Executive Summary:
Visible signs of artificial intelligence adoption in China are everywhere. Consumers interact seamlessly with chatbots, livestream hosts promote algorithmically selected products, and recommendation engines exhibit an almost anticipatory understanding of user preferences. Yet, beyond these consumer-facing applications, a deeper and potentially more consequential transformation is unfolding. Across China’s retail and services sectors, AI is shifting from demand generation to cost optimization. Enterprises are deploying machine learning in logistics, inventory management, customer service, and fulfillment operations to reduce inefficiencies as revenue growth slows and pricing power tightens.
Highlights:
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Chinese companies are increasingly using AI to control operational costs and improve efficiency in a low-growth economic environment.
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AI is being deployed in logistics, inventory management, and customer service to reduce expenses rather than primarily drive demand.
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This shift towards AI for cost reduction is leading to steadier cash flow and improved operating margins for consumer companies.
China’s Consumer Sector: AI Powers Efficiency Over Growth:
As China’s economy adjusts to structural deceleration—marked by subdued household confidence, persistent real-estate overhang, and maturing market saturation—consumer companies face an unfamiliar imperative: prioritize resilience over expansion. With pricing power eroded and cost inflation persistent, traditional growth levers have lost potency. Leading platforms are responding by reorienting AI investments toward operational efficiency, transforming algorithms from engagement engines into margin-defense mechanisms. For investors, this evolution signals a new phase of earnings potential—one where incremental productivity gains could prove more durable than cyclical demand recovery.
“In a low-growth environment, incremental efficiency gains matter more than top-line expansion,” notes Zhao Ming, senior analyst for China internet companies at Hongyuan Capital. “AI has become a strategic lever for margin preservation.”
China’s consumer sector entered 2026 navigating familiar structural headwinds: cautious household sentiment, a fading property-wealth effect, and fierce price competition. Unlike in previous cycles, companies are finding it increasingly difficult to pass rising costs on to consumers. The result has been a strategic realignment. Where past growth phases emphasized volume and engagement, today’s market is rewarding operational discipline. That shift has sharpened the appeal of AI—not as a marketing showcase, but as a core instrument of productivity and cost control.
“In a slower-growth environment, leading Chinese consumer companies are using AI primarily to improve productivity and reduce operating costs rather than to drive incremental demand,” McKinsey said in a recent analysis of AI adoption across China’s retail and services sectors.
From Growth Catalyst to Cost Lever:
The center of gravity for AI investment has shifted from customer-facing innovation to operational optimization. E-commerce platforms and logistics operators have been among the earliest to integrate AI into mission-critical workflows. Demand-forecasting models are helping warehouses fine-tune inventory levels and reduce exposure to slow-moving goods. Routing algorithms are compressing last-mile delivery times and cutting fuel consumption. Automated customer-service systems are deflecting an ever-larger share of inquiries typically handled by human agents.
On their own, each of these applications may appear incremental. Taken together, they represent a meaningful improvement in margin resilience at a time when top-line expansion remains constrained. In an environment where minor percentage-point gains in efficiency can significantly affect earnings quality, AI is emerging as a quiet but potent differentiator.
Logistics as a Testbed for Scalable Efficiency:
The operational impact of AI is most visible in the logistics ecosystem, a sector that remains one of the largest cost centers in China’s consumer economy. Machine-learning systems are now proficient at forecasting order density by neighborhood and time of day, enabling fulfillment centers to position inventory closer to anticipated demand. In dense urban markets, adaptive algorithms continually adjust delivery routes in response to evolving conditions—from traffic and weather to cancellations and reorders—reducing both transit times and redundancy.
For investors, the value proposition is compelling: logistics efficiency scales. Once AI models are trained and stress-tested, they can be deployed across regions at low incremental cost, generating operating leverage even in periods of stagnant demand. Crucially, incumbents benefit from data scale. Years of transaction and delivery records translate into more accurate predictive models, reinforcing competitive moats and raising barriers to entry. This dynamic is reshaping industry structure even as consumer-facing platform features converge toward commoditization.
AI Extends Gains to Physical Retail:
Beyond e-commerce, brick-and-mortar retail—long considered a laggard in China’s digital transformation—is also seeing measurable efficiency dividends. Smart shelving, computer-vision inventory systems, and automated stock monitoring are cutting labor intensity while increasing inventory turnover. Grocery and convenience chains now rely on AI to optimize product assortments at the store level, calibrating selections to localized consumption patterns instead of applying national averages. The effect is twofold: reduced waste and fewer markdowns, both of which have historically weighed on profitability. The outcomes may not register as eye-catching innovation, but they align closely with investor priorities—stabler cash flows and predictable margins.
Labor Efficiency as a Strategic Imperative:
AI-enhanced customer service represents another underappreciated margin driver. Major consumer platforms report that routine customer interactions—order tracking, returns, product troubleshooting—are now predominantly handled through automated systems. This transition is particularly relevant in a labor market where wage growth continues to outpace consumption. Limiting headcount growth while maintaining response times and service quality has become a key operational goal.
“AI doesn’t replace customer service,” says Li Wenyuan, chief technology officer at retail software firm Qimeng Tech. “It filters it, so humans deal only with the expensive problems.” That filtering function is transforming customer operations from cost centers into scalable service platforms, balancing efficiency with user satisfaction.
Economic Implications:
For investors, the impact of China’s second-wave AI adoption will likely manifest less in headline growth metrics and more in incremental financial performance indicators. Key areas to watch include:
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Operating margin expansion driven by process automation
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Reduced fulfillment and logistics costs as a share of revenue
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Improved capital-expenditure efficiency through data-driven asset utilization
The first chapter of China’s AI consumer story was about differentiation—using algorithms to personalize experiences, boost engagement, and drive sales. The next chapter is about discipline. As growth normalizes, companies are deploying AI to do more with less: compress costs, stabilize earnings, and build leaner, more adaptive operating models. In a market where scale alone no longer guarantees profitability, AI has become not just a tool for innovation—but a mechanism for survival.
References:
https://www.barrons.com/articles/china-ai-boom-commerce-warehouses-b1ad55f1
China’s open source AI models to capture a larger share of 2026 global AI market
China’s telecom industry rapid growth in 2025 eludes Nokia and Ericsson as sales collapse
China ITU filing to put ~200K satellites in low earth orbit while FCC authorizes 7.5K additional Starlink LEO satellites
China gaining on U.S. in AI technology arms race- silicon, models and research
U.S. export controls on Nvidia H20 AI chips enables Huawei’s 910C GPU to be favored by AI tech giants in China
Bloomberg: China Lures Billionaires Into Race to Catch U.S. in AI
Analysis & Evaluation: HomeOfficeIQ™ within SmartHome™on the Calix Platform
Calix, Inc. today announced the launch of HomeOfficeIQ™, an advanced value-added service integrated within SmartHome™ on the Calix Platform. Designed to help broadband service providers strengthen subscriber retention and unlock new revenue opportunities, HomeOfficeIQ introduces intelligent cellular network failover functionality managed through CommandIQ®. This capability ensures uninterrupted connectivity for remote workers and households during network outages, extending resilience beyond the limits of the broadband infrastructure itself.
Through the CommandIQ app, subscribers can precisely manage device- or network-level prioritization to maintain business continuity, while ProtectIQ® continues to safeguard home networks against security threats and ExperienceIQ® enforces content and application controls for a consistent, secure online environment.
As hybrid work becomes a fixture of the connected home, resilient and secure broadband is now indispensable. According to Calix Market Insights, 37% of residential internet subscribers regularly use their home connections for work, and more than one in three who switched providers cited enhanced security as a primary driver. This shift highlights subscribers’ growing expectation for reliable connectivity that protects sensitive applications and workflows. For service providers, this translates into a clear opportunity to capture higher average revenue per user (ARPU)—with 35% of respondents reporting employer reimbursement for home internet service, underscoring its professional value.
Ben Foster, president and chief executive officer at Twin Valleyopens in a new tab, said: “Calix is giving us a powerful way to differentiate our residential experiences and create real value for our customers. Adding HomeOfficeIQ to our upcoming lifestyle-based offers builds on what SmartHome already delivers and reinforces why customers continue choosing Twin Valley. By keeping customers connected when it matters most, Calix is helping Twin Valley strengthen loyalty, support higher ARPU, and drive long-term, sustainable growth for our business.”
Shane Eleniak, chief product officer at Calix, said: “HomeOfficeIQ reflects our commitment to helping service providers deliver secure, connected experiences for their subscribers—even during unavoidable outages. Now, HomeOfficeIQ will offer our customers a simple, new way to strengthen their residential offerings. With this launch, Calix continues to extend SmartHome innovation on the Calix Platform, helping providers further differentiate from competitors, build the trust that drives retention and ARPU, and create long-term value for their businesses and communities.”
According to Calix, their HomeOffice IQ capabilities and enhancements for SmartHome enable service providers to deliver:
- Safe, secure connections during unavoidable network outages. HomeOfficeIQ quickly restores connectivity to critical and prioritized devices during outages, while keeping ProtectIQ active and applying the content controls of ExperienceIQ. Together, these ensure a safe, secure experience—helping safeguard video meetings, cloud-based applications, and other time-sensitive activities. HomeOfficeIQ is fully compatible with the award-winning Calix GigaSpire® portfolio.
- Personalized network controls over SSIDs or IoT devices for subscribers. When a cellular hotspot is activated leveraging HomeOfficeIQ, households can easily select and prioritize either multiple SSIDs or multiple devices. This helps ensure essential activities like work, school, or telehealth stay connected—giving households meaningful control over their network for the moments that matter most.
- Built-in CommandIQ promotions that boost engagement and drive adoption. Integrated directly into CommandIQ, promo and announcement tiles help providers promote new offers, share service updates, and educate users, increasing engagement and accelerating SmartHome adoption. CommandIQ recently earned the TMC 2025 Cybersecurity Excellence Award for advanced subscriber protection.
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About Calix:
Calix focuses on a broadband services, cloud software, access systems, and managed services for ISPs and Broadband Service Providers (BSPs) which offers broadband access and other bundled services. Here is how they describe themselves:
Calix, Inc. (NYSE: CALX)—Calix is an appliance-based platform, cloud and managed services company. Broadband experience providers leverage Calix’s broadband platform, cloud and managed services to simplify their operations, subscriber engagement and services; innovate for their consumer, business and municipal subscribers; and grow their value for members, investors and the communities they serve.
Our end-to-end platform and managed services democratize the use of data—enabling our customers of any size to operate efficiently, acquire subscribers and deliver exceptional experiences. Calix is dedicated to driving continuous improvement in partnership with our growing ecosystem to support the transformation of our customers and their communities.
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Author’s Assessment of Calix Deliverables:
- Broadband Platform and Cloud:
Calix Cloud delivers analytics, automation, and service intelligence to simplify operations, improve service agility, and drive revenue growth for service providers.
Engagement Cloud, Service Cloud, Operations Cloud, and related modules provide subscriber insights, marketing automation, and network/service visibility on a common platform.
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Access systems and premises gear
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Broadband access nodes and fiber-to-the-home (FTTH) optics support PON-based and fiber-based broadband architectures for residential and business services.
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GigaSpire-branded residential gateways and Wi‑Fi systems provide managed in‑home connectivity as CPE tightly integrated with the Calix platform and clouds.
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Managed services portfolio (SmartLife/experience services)
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SmartHome delivers managed residential Wi‑Fi, security (ProtectIQ), parental/content controls (ExperienceIQ), and new offers such as HomeOfficeIQ with cellular failover for work-from-home reliability.
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SmartBiz targets small business connectivity, offering managed Wi‑Fi and value‑added services tailored for business workflows and higher service tiers.
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SmartTown extends secure Wi‑Fi beyond the home into community and public spaces as a managed Wi‑Fi fabric for municipalities and regional BSPs.
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Core market segments:
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Regional and rural broadband service providers (BSPs/ISPs)
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Primary customers are Tier 2/3 and regional providers looking to differentiate on managed Wi‑Fi, subscriber experience, and ARPU growth rather than raw bandwidth alone.
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Residential broadband and smart home
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Focus on households that rely on broadband for hybrid work, streaming, gaming, and family connectivity, where secure, managed Wi‑Fi and application-aware services drive perceived value.
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Small business and community connectivity
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SmartBiz and SmartTown position Calix with providers serving SMBs, local enterprises, and municipalities that need managed wireless coverage and simple operations at scale.
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Growth aligned to government-funded fiber buildouts
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Calix highlights substantial revenue opportunity tied to U.S. BEAD and related broadband programs, leveraging its platform and systems as BSPs scale new FTTH networks and experience-based services. Their 10G PON solution is used by over 225 BSPs.
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References:
https://www.calix.com/press-release/2026/02/calix-launches-homeofficeiq.html
https://www.calix.com/blog/2026/01/latency-in-internet.html
Calix and Corning Weigh In: When Will Broadband Wireline Spending Increase?
Calix touts GigaSpire as smart home solution for ISPs
ZTE sees demand for fixed broadband and smart home solutions while 5G lags
MediaTek to expand chipset portfolio to include WiFi7, smart homes, STBs, telematics and IoT
Cisco’s Silicon One G300 as the dominant AI networking fabric, competing with Broadcom’s Tomahawk 6 series
On February 10, 2026, Cisco announced the Silicon One G300 102.4 Tbps Ethernet switch silicon, claiming it can power gigawatt-scale AI clusters for training, inference, and real-time agentic workloads, while maximizing GPU utilization with a 28% improvement in job completion time. The G300 was said to offer Intelligent Collective Networking, which combines an industry-leading fully shared packet buffer, path-based load balancing, and proactive network telemetry to offer better performance and profitability for large-scale data centers. It efficiently absorbs bursty AI traffic, responds faster to link failures, and prevents packet drops that can stall jobs, ensuring reliable data delivery even over long distances. With Intelligent Collective Networking, Cisco can deliver 33% increased network utilization, and a 28% reduction in job completion time versus simulated non-optimized path selection, making AI data centers more profitable with more tokens generated per GPU-hour. Also, the Cisco Silicon One G300 is highly programmable, enabling equipment to be upgraded for new network functionality even after it has been deployed. This enables Silicon One-based products to support emerging use cases and play multiple network roles, protecting long-term infrastructure investments. And with security fused into the hardware, customers can embrace holistic, at-speed security to keep clusters up and running.
The Cisco Silicon One G300 will power new Cisco N9000 and Cisco 8000 systems that push the frontier of AI networking in the data center. The systems feature innovative liquid cooling and support high-density optics to achieve new efficiency benchmarks and ensure customers get the most out of their GPU investments. In addition, the company enhanced Nexus One to make it easier for enterprises to operate their AI networks — on-premises or in the cloud — removing the complexity that can hold organizations back from scaling AI data centers.
“We are spearheading performance, manageability, and security in AI networking by innovating across the full stack – from silicon to systems and software,” said Jeetu Patel, President and Chief Product Officer, Cisco. “We’re building the foundation for the future of infrastructure, supporting every type of customer—from hyperscalers to enterprises—as they shift to AI-powered workloads.”
“As AI training and inference continues to scale, data movement is the key to efficient AI compute; the network becomes part of the compute itself. It’s not just about faster GPUs – the network must deliver scalable bandwidth and reliable, congestion-free data movement,” said Martin Lund, Executive Vice President of Cisco’s Common Hardware Group. “Cisco Silicon One G300, powering our new Cisco N9000 and Cisco 8000 systems, delivers high-performance, programmable, and deterministic networking – enabling every customer to fully utilize their compute and scale AI securely and reliably in production.”
The networking industry reaction to Cisco’s newest ASIC has been largely positive, with industry analysts and partners highlighting its role in reclaiming Cisco’s dominance in the AI infrastructure market. For example, Brendan Burke of Futurium thinks Cisco’s Silicon One G300 could be the backbone of Agentic AI Inference. His take: “Cisco’s latest announcements represent a calculated move to assert dominance in the AI networking fabric by attacking the specific bottlenecks of GPU cluster efficiency. As AI workloads shift toward agentic inference, where autonomous agents continuously interact across distributed environments, the network must handle unpredictable traffic patterns, unlike the structured flows of traditional training. Cisco is leveraging its vertical integration strategy to address the reliability and power constraints that plague these massive clusters. By emphasizing programmable silicon and rigorous optic qualification, Cisco aims to decouple network lifespan from rapid GPU innovation cycles, ensuring infrastructure can adapt to new traffic steering algorithms without hardware replacements. The G300 is a bid to make Ethernet the undisputed standard for AI back-end networks.”
- Industry-Leading Specs: Market analysts have noted that the G300’s 102.4 Tbps switching capacity sets a new benchmark for AI scale-out and scale-across networking.
- Efficiency Gains: Initial simulations showing a 28% reduction in job completion time (JCT) and a 33% increase in network utilization have been cited as major differentiators for large-scale AI clusters.
- Sustainability Focus: The shift toward liquid-cooled systems for the G300, which offers 70% greater energy efficiency per bit, is being viewed as a critical move for sustainable AI growth.
- Competitive Positioning: Experts from HyperFRAME Research suggest that the new silicon signals a “new confidence” from Cisco, positioning them as the “Apple of infrastructure” by tightly integrating hardware and software.
- AI Infrastructure Pivot: Financial analysts at Seeking Alpha have upgraded Cisco’s outlook, viewing the company no longer as just a legacy hardware firm but as a central player in the AI revolution.
- Partner Confidence: Major partners, such as Shanghai Lichan Technology, have expressed excitement about the Nexus 9100 Series powered by this silicon, specifically for its ability to simplify and scale AI deployments.
- Nvidia & Broadcom Competition: While the G300 is seen as a strong challenger to Nvidia’s Spectrum-X and Broadcom’s Tomahawk/Jericho lines, some observers note that Cisco still faces a steep climb to regain market share lost to these competitors in recent years.
- Complexity Concerns: Some industry veterans have pointed out that while the silicon is “hyperscale ready,” the success of these ASICs in the enterprise will depend on Cisco’s ability to maintain operational simplicity through tools like the Nexus Dashboard.
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Cisco Silicon One G300
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Broadcom Tomahawk 6 (BCM78910 Series)
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Bandwidth
102.4 Tbps  |
Bandwidth
102.4 Tbps  |
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Manufacturing Process
TSMC 3nm  |
Manufacturing Process
3nm technology |
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SerDes Lanes & Speed
512 lanes at 200 Gbps per link  |
SerDes Lanes & Speed
512 lanes at 200 Gbps per link, or 1024 lanes at 100G |
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Port Configuration
Up to 64 x 1.6TbE ports or 512 x 200GbE ports |
Port Configuration
Up to 64 x 1.6TbE ports or 512 x 200GbE ports |
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Target AI Cluster Size
Supports deployments of up to 128,000 GPUs |
Target AI Cluster Size
Supports over 100,000 XPUs (accelerators) Broadcom |
- Congestion Management: Cisco differentiates its G300 with an “Intelligent Collective Networking” approach featuring a fully shared packet buffer and a load-balancing agent that communicates across all G300s in the network to build a global map of congestion. Broadcom’s Tomahawk series also includes smart congestion control and global load balancing, though Cisco claims its implementation achieves higher network utilization (33% better).
- Programmability: Cisco emphasizes P4 programmability, allowing customers to update network functionality even after deployment.
- Ecosystem & Integration: Broadcom operates primarily in the merchant silicon market, with their chips used by various partners like HPE Juniper Networking. Cisco uses its own silicon to power its
Nexus 9000 and 8000 Series switches, tightly integrating hardware with software management platforms like Nexus One for a unified solution.
- Cooling Solutions: The Cisco G300 is designed to support high-density optics and is offered in new systems that include liquid-cooled options, providing 70% greater energy efficiency per bit compared to previous generations.
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References:
https://newsroom.cisco.com/c/r/newsroom/en/us/a/y2026/m02/cisco-announces-new-silicon-one-g300.html
https://blogs.cisco.com/sp/cisco-silicon-one-g300-the-next-wave-of-ai-innovation
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