AI RAN
AI infrastructure spending boom: a path towards AGI or speculative bubble?
by Rahul Sharma, Indxx with Alan J Weissberger, IEEE Techblog
Introduction:
The ongoing wave of artificial intelligence (AI) infrastructure investment by U.S. mega-cap tech firms marks one of the largest corporate spending cycles in history. Aggregate annual AI investments, mostly for cloud resident mega-data centers, are expected to exceed $400 billion in 2025, potentially surpassing $500 billion by 2026 — the scale of this buildout rivals that of past industrial revolutions — from railroads to the internet era.[1]
At its core, this spending surge represents a strategic arms race for computational dominance. Meta, Alphabet, Amazon and Microsoft are racing to secure leadership in artificial intelligence capabilities — a contest where access to data, energy, and compute capacity are the new determinants of market power.
AI Spending & Debt Financing:
Leading technology firms are racing to secure dominance in compute capacity — the new cornerstone of digital power:
- Meta plans to spend $72 billion on AI infrastructure in 2025.
- Alphabet (Google) has expanded its capex guidance to $91–93 billion.[3]
- Microsoft and Amazon are doubling data center capacity, while AWS will drive most of Amazon’s $125 billion 2026 investment.[4]
- Even Apple, typically conservative in R&D, has accelerated AI infrastructure spending.
Their capex is shown in the chart below:
Analysts estimate that AI could add up to 0.5% to U.S. GDP annually over the next several years. Reflecting this optimism, Morgan Stanley forecasts $2.9 trillion in AI-related investments between 2025 and 2028. The scale of commitment from Big Tech is reshaping expectations across financial markets, enterprise strategies, and public policy, marking one of the most intense capital spending cycles in corporate history.[2]
Meanwhile, OpenAI’s trillion-dollar partnerships with Nvidia, Oracle, and Broadcom have redefined the scale of ambition, turning compute infrastructure into a strategic asset comparable to energy independence or semiconductor sovereignty.[5]
Growth Engine or Speculative Bubble?
As Big Tech pours hundreds of billions of dollars into AI infrastructure, analysts and investors remain divided — some view it as a rational, long-term investment cycle, while others warn of a potential speculative bubble. Yet uncertainty remains — especially around Meta’s long-term monetization of AGI-related efforts.[8]
Some analysts view this huge AI spending as a necessary step towards achieving Artificial General Intelligence (AGI) – an unrealized type of AI that possesses human-level cognitive abilities, allowing it to understand, learn, and adapt to any intellectual task a human can. Unlike narrow AI, which is designed for specific functions like playing chess or image recognition, AGI could apply its knowledge to a wide range of different situations and problems without needing to be explicitly programmed for each one.
Other analysts believe this is a speculative bubble, fueled by debt that can never be repaid. Tech sector valuations have soared to dot-com era levels – and, based on price-to-sales ratios, are well beyond them. Some of AI’s biggest proponents acknowledge the fact that valuations are overinflated, including OpenAI chairman Bret Taylor: “AI will transform the economy… and create huge amounts of economic value in the future,” Taylor told The Verge. “I think we’re also in a bubble, and a lot of people will lose a lot of money,” he added.
Here are a few AI bubble points and charts:
- AI-related capex is projected to consume up to 94% of operating cash flows by 2026, according to Bank of America.[6]
- Over $75 billion in AI-linked corporate bonds have been issued in just two months — a signal of mounting leverage. Still, strong revenue growth from AI services (particularly cloud and enterprise AI) keeps optimism alive.[7]
- Meta, Google, Microsoft, Amazon and xAI (Elon Musk’s company) are all using off-balance-sheet debt vehicles, including special-purpose vehicles (SPVs) to fund part of their AI investments. A slowdown in AI demand could render the debt tied to these SPVs worthless, potentially triggering another financial crisis.
- Alphabet’s (Google’s parent company) CEO Sundar Pichai sees “elements of irrationality” in the current scale of AI investing which is much more than excessive investments during the dot-com/fiber optic built-out boom of the late 1990s. If the AI bubble bursts, Pichai said that no company will be immune, including Alphabet, despite its breakthrough technology, Gemini, fueling gains in the company’s stock price.
…………………………………………………………………………………………………………………..
From Infrastructure to Intelligence:
Executives justify the massive spend by citing acute compute shortages and exponential demand growth:
- Microsoft’s CFO Amy Hood admitted, “We’ve been short on capacity for many quarters” and confirmed that the company will increase its spending on GPUs and CPUs in 2026 to meet surging demand.
- Amazon’s Andy Jassy noted that “every new tranche of capacity is immediately monetized”, underscoring strong and sustained demand for AI and cloud services.
- Google reported billions in quarterly AI revenue, offering early evidence of commercial payoff.
Macro Ripple Effects – Industrializing Intelligence:
AI data centers have become the factories of the digital age, fueling demand for:
- Semiconductors, especially GPUs (Nvidia, AMD, Broadcom)
- Cloud and networking infrastructure (Oracle, Cisco)
- Energy and advanced cooling systems for AI data centers (Vertiv, Schneider Electric, Johnson Controls, and other specialists such as Liquid Stack and Green Revolution Cooling).
| Company Name | Core Expertise | Key Solutions for AI Data Centers |
|---|---|---|
| Vertiv | Critical infrastructure (power & cooling) | Offers full-stack solutions with air and liquid cooling, power distribution units (PDUs), and monitoring systems, including the AI-ready Vertiv 360AI portfolio. |
| Schneider Electric | Energy management & automation | Provides integrated power and thermal management via its EcoStruxure platform, specializing in modular and liquid cooling solutions for HPC and AI applications. |
| Johnson Controls | HVAC & building solutions | Offers integrated, energy-efficient solutions from design to maintenance, including Silent-Aire cooling and YORK chillers, with a focus on large-scale operations. |
| Eaton | Power management | Specializes in electrical distribution systems, uninterruptible power supplies (UPS), and switchgear, which are crucial for reliable energy delivery to high-density AI racks. |
- LiquidStack: A leader in two-phase and modular immersion cooling and direct-to-chip systems, trusted by large cloud and hardware providers.
- Green Revolution Cooling (GRC): Pioneers in single-phase immersion cooling solutions that help simplify thermal management and improve energy efficiency.
- Iceotope: Focuses on chassis-level precision liquid cooling, delivering dielectric fluid directly to components for maximum efficiency and reduced operational costs.
- Asetek: Specializes in direct-to-chip (D2C) liquid cooling solutions and rack-level Coolant Distribution Units (CDUs) for high-performance computing.
- CoolIT Systems: Known for its custom direct liquid cooling technologies, working closely with server OEMs (Original Equipment Manufacturers) to integrate cold plates and CDUs for AI and HPC workloads.
–>This new AI ecosystem is reshaping global supply chains — but also straining local energy and water resources. For example, Meta’s massive data center in Georgia has already triggered environmental concerns over energy and water usage.
Global Spending Outlook:
- According to UBS, global AI capex will reach $423 billion in 2025, $571 billion by 2026 and $1.3 trillion by 2030, growing at a 25% CAGR during the period 2025-2030.
Compute demand is outpacing expectations, with Google’s Gemini saw 130 times rise in AI token usage over the past 18 months, highlighting soaring compute and Meta’s infrastructure needs expanding sharply.[9]
Conclusions:
The AI infrastructure boom reflects a bold, forward-looking strategy by Big Tech, built on the belief that compute capacity will define the next decade’s leaders. If Artificial General Intelligence (AGI) or large-scale AI monetization unfolds as expected, today’s investments will be seen as visionary and transformative. Either way, the AI era is well underway — and the race for computational excellence is reshaping the future of global markets and innovation.
…………………………………………………………………………………………………………………………………………………………………………………………………………………………….
Footnotes:
[1] https://www.investing.com/news/stock-market-news/ai-capex-to-exceed-half-a-trillion-in-2026-ubs-4343520?utm_medium=feed&utm_source=yahoo&utm_campaign=yahoo-www
[2] https://www.venturepulsemag.com/2025/08/01/big-techs-400-billion-ai-bet-the-race-thats-reshaping-global-technology/#:~:text=Big%20Tech’s%20$400%20Billion%20AI%20Bet:%20The%20Race%20That’s%20Reshaping%20Global%20Technology,-3%20months%20ago&text=The%20world’s%20largest%20technology%20companies,enterprise%20strategy%2C%20and%20public%20policy.
[3] https://www.businessinsider.com/big-tech-capex-spending-ai-earnings-2025-10?
[4] https://www.investing.com/analysis/meta-plunged-12-amazon-jumped-11–same-ai-race-different-economics-200669410
[5] https://www.cnbc.com/2025/10/15/a-guide-to-1-trillion-worth-of-ai-deals-between-openai-nvidia.html
[6] https://finance.yahoo.com/news/bank-america-just-issued-stark-152422714.html
[7] https://news.futunn.com/en/post/64706046/from-cash-rich-to-collective-debt-how-does-wall-street?level=1&data_ticket=1763038546393561
[8] https://www.businessinsider.com/big-tech-capex-spending-ai-earnings-2025-10?
[9] https://finance.yahoo.com/news/ai-capex-exceed-half-trillion-093015889.html
……………………………………………………………………………………………………………………………………………………………………………………………………………………………
About the Author:
Rahul Sharma is President & Co-Chief Executive Officer at Indxx – a provider of end-to-end indexing services, data and technology products. He has been instrumental in leading the firm’s growth since 2011. Raul manages Indxx’s Sales, Client Engagement, Marketing and Branding teams while also helping to set the firm’s overall strategic objectives and vision.
Rahul holds a BS from Boston College and an MBA with Beta Gamma Sigma honors from Georgetown University’s McDonough School of Business.
……………………………………………………………………………………………………………………………………………………………………………………………………………………………
References:
Curmudgeon/Sperandeo: New AI Era Thinking and Circular Financing Deals
Expose: AI is more than a bubble; it’s a data center debt bomb
Can the debt fueling the new wave of AI infrastructure buildouts ever be repaid?
AI spending boom accelerates: Big tech to invest an aggregate of $400 billion in 2025; much more in 2026!
Big tech spending on AI data centers and infrastructure vs the fiber optic buildout during the dot-com boom (& bust)
FT: Scale of AI private company valuations dwarfs dot-com boom
Amazon’s Jeff Bezos at Italian Tech Week: “AI is a kind of industrial bubble”
AI Data Center Boom Carries Huge Default and Demand Risks
Will billions of dollars big tech is spending on Gen AI data centers produce a decent ROI?
Dell’Oro: Analysis of the Nokia-NVIDIA-partnership on AI RAN
RAN silicon rethink – from purpose built products & ASICs to general purpose processors or GPUs for vRAN & AI RAN
Nokia in major pivot from traditional telecom to AI, cloud infrastructure, data center networking and 6G
Reuters: US Department of Energy forms $1 billion AI supercomputer partnership with AMD
………………………………………………………………………………………………………………………………………………………………………….
Dell’Oro: Analysis of the Nokia-NVIDIA-partnership on AI RAN
According to Dell’Oro VP Stefan Pongratz, Nokia has outlined a clear plan to arrest its declining RAN revenue share (see chart below), with NVIDIA now a central pillar of that strategy. The partnership is designed to deliver AI RAN [1.] while meeting wireless network operators’ near-term constraints and concerns on performance, power, and TCO (Total Cost of Ownership). IEEE Techblog has noted in many past blog posts that telcos have huge doubts about AI RAN which implies they won’t buy into that new RAN architecture.
This is especially relevant considering the monumental failure of multi-vendor Open RAN which was promoted as a game changer, but has dismally failed to attain that vision.
Note 1. AI RAN is a mobile RAN architecture where AI and machine learning are embedded into the RAN software and underlying compute platform to optimize how the network is planned, configured, and operated. It is being pushed by NVIDIA to get its GPUs into 5G, 5G Advanced and 6G base stations and other wireless network equipment in the RAN.
……………………………………………………………………………………………………………………………………………………..
Nokia aims to use collaboration with NVIDIA (which invested $1B in the Finland based company) to stabilize its RAN market share in the near term and create a platform for long-term growth in AI-native 5G-Advanced and 6G networks. The timing—following a dense cadence of disclosures at NVIDIA’s GPU Technology Conference and Nokia’s Capital Markets Day—makes this an ideal time to reassess the scope of the joint announcements, the RAN implications, and Nokia’s broader competitive posture in an increasingly concentrated market.
Both companies share a belief that telecom networks will evolve from best-effort connectivity into a distributed compute fabric underpinning autonomous machines, self-driving vehicles, humanoids, and industrial digital twins. From that perspective, the RAN becomes an “AI grid” that executes and orchestrates AI workloads at the edge, enabling massive numbers of latency-sensitive, bandwidth-intensive AI use cases.
Unlike prior attempts to penetrate the RAN market with its GPUs, NVIDIA is now taking a more pragmatic approach, explicitly targeting parity with incumbent, purpose-built RAN equipment based on performance, power, and TCO rather than leading with speculative multi-tenant or new-revenue narratives. Nokia, acutely aware of wireless telco risk tolerance, is positioning the solution so that the ROI must be justifiable on a pure RAN basis, with additional AI and edge-compute upside treated as optional rather than foundational.
A quick recap of NVIDIA’s entry into RAN: Based on the announcement and subsequent discussions, our understanding is that NVIDIA will invest $1 B in Nokia and that NVIDIA-powered AI-RAN products will be incorporated into Nokia’s RAN portfolio starting in 2027 (with trials beginning in 2026). While RAN compute—which represents less than half of the $30B+ RAN market—is immaterial relative to NVIDIA’s $4+ T market cap, the potential upside becomes more meaningful when viewed in the context of NVIDIA’s broader telecom ambitions and its $165 B in trailing-twelve-month revenue.
With a deployed base of more than 1 million BTS, Nokia is prioritizing three migration vectors to GPU/AI-RAN, in order of expected impact:
-
Purpose-built D-RAN [2.], by inserting a new card into existing AirScale slots.
-
D-RAN vRAN [3.], using COTS servers at the cell site.
-
Cloud RAN [4.] or vRAN, using centralized COTS infrastructure.
This approach aligns with wireless network operators’ desire to sweat existing AirScale assets while minimizing operational disruption.
Note 2. Purpose-built D-RAN is a distributed RAN architecture where the baseband processing runs on dedicated, vendor-specific hardware at or very close to the cell site, rather than on generic COTS servers. It is “purpose-built” because the silicon, boards, and software stack are tightly integrated and optimized for RAN performance, power efficiency, and footprint, not general-purpose compute.
Note 3. vRAN or virtual RAN is a technology that virtualizes the functions of a cellular network’s radio access network, moving them from dedicated hardware to software running on general-purpose servers. This approach makes mobile networks more flexible, scalable, and cost-efficient by replacing proprietary hardware with software on common-off-the-shelf (COTS) hardware.
Note 4. Cloud RAN (C-RAN) is a centralized cellular network architecture that uses cloud computing to virtualize and process radio access network (RAN) functions. This architecture centralizes baseband units in a “BBU hotel,” allowing for more flexible and scalable network management, efficient resource allocation, and improved network performance. It allows operators to pool resources, adjust capacity based on demand, and support new services, which is a key enabler for 5G networks.
………………………………………………………………………………………………………………………………………………
In this model, the Distributed Unit, and often the higher-layer functions, are physically collocated with the radio unit at the site, making each site a largely self-contained RAN node. This contrasts with Cloud RAN or vRAN, where baseband functions are centralized or virtualized on shared cloud infrastructure, and with cloud/AI-RAN approaches that rely on GPUs or other general-purpose accelerators instead of custom RAN hardware.
The macro-RAN market (baseband plus radio) is roughly a 30 billion USD annual opportunity, with on the order of 1–2 million macro sites shipped per year. In that context, operators have limited appetite to pay more than 10,000 USD for a GPU per sector, even if software-led benefits accumulate over time, which is why NVIDIA is signaling GPU pricing in line with ARC-Compact but at roughly double the capacity and Nokia is targeting 48–50% gross margins in Mobile Infrastructure by 2028, slightly above the current run-rate.
If the TCO and performance-per-watt gap versus custom silicon continues to narrow, the partnership could materially influence AI-RAN and Cloud-RAN trajectories while also supporting Nokia’s margin expansion goals. AI-RAN was already expected to scale to roughly one-third of the RAN market by 2029; Nokia’s decision to lean harder into GPUs amplifies this structural shift without fundamentally changing the long-term 6G direction.
In the near term, GPU-enabled D-RAN using empty AirScale slots is expected to dominate deployments, reflecting operators’ preference for incremental, site-level upgrades. At the same time, the Nokia-NVIDIA partnership is not expected to meaningfully alter the overall Cloud RAN vs. D-RAN mix, Open RAN adoption (slow or non-existent) , or the trajectory of multi-tenant RAN, which remain more dependent on network operator architecture and commercial decisions than on a single vendor–silicon alignment.
Nokia plans to remain disciplined and focus on areas where it can differentiate and unlock value—particularly through software/faster innovation cycles via its recently announced partnership with NVIDIA. The company sees meaningful opportunities to capture incremental share in North America, Europe, India, and select APAC markets. And it is already off to a solid start— we estimate that Nokia’s 1Q25–3Q25 RAN revenue share outside North America improved slightly relative to 2024. Following this stabilization phase, Nokia is betting that its investments will pay off and that it will be well-positioned to lead with AI-native networks and 6G.
Nokia’s objective is clear: stabilize RAN in the short term, then grow by leading in AI-native networks and 6G over the longer horizon. Success now hinges on Nokia’s ability to operationalize the GPU-based RAN roadmap at scale and on NVIDIA’s ability to deliver carrier-grade economics and performance—turning the AI-RAN narrative into production-grade, repeatable deployments.
Nokia sees meaningful opportunities to capture incremental RAN market share in North America, Europe, India, and select APAC markets. And it is already off to a solid start— we estimate that Nokia’s 1Q25–3Q25 RAN revenue share outside North America improved slightly relative to 2024. Following this stabilization phase, Nokia is betting that its investments will pay off and that it will be well-positioned to lead with AI-native networks and 6G.
References:
Nokia in major pivot from traditional telecom to AI, cloud infrastructure, data center networking and 6G
Indosat Ooredoo Hutchison, Nokia and Nvidia AI-RAN research center in Indonesia amongst telco skepticism
Nvidia pays $1 billion for a stake in Nokia to collaborate on AI networking solutions
RAN silicon rethink – from purpose built products & ASICs to general purpose processors or GPUs for vRAN & AI RAN
Dell’Oro: AI RAN to account for 1/3 of RAN market by 2029; AI RAN Alliance membership increases but few telcos have joined
Dell’Oro: RAN revenue growth in 1Q2025; AI RAN is a conundrum
AI RAN Alliance selects Alex Choi as Chairman
Expose: AI is more than a bubble; it’s a data center debt bomb
Nokia and Rohde & Schwarz collaborate on AI-powered 6G receiver years before IMT 2030 RIT submissions to ITU-R WP5D
Nokia and the test and measurement firm Rohde & Schwarz have created and successfully tested a “6G” radio receiver that uses AI technologies to overcome one of the biggest anticipated challenges of 6G network rollouts, coverage limitations inherent in 6G’s higher-frequency spectrum.
–>This is truly astonishing as ITU-R WP5D doesn’t even plan to evaluate 6G RIT/SRITs till February 2027 when the first submissions are invited to be presented.
Nokia Bell Labs developed the receiver and validated it using 6G test equipment and methodologies from Rohde & Schwarz. The two companies will unveil a proof-of-concept receiver at the Brooklyn 6G Summit on November 6, 2025. Nokia says, “the machine learning capabilities in the receiver greatly boost uplink distance, enhancing coverage for future 6G networks. This will help operators roll out 6G over their existing 5G footprints, reducing deployment costs and accelerating time to market.”
Image Credit: Rohde & Schwarz
Nokia Bell Labs and Rohde & Schwarz have tested this new AI receiver under real world conditions, achieving uplink distance improvements over today’s receiver technologies ranging from 10% to 25%. The testbed comprises an R&S SMW200A vector signal generator, used for uplink signal generation and channel emulation. On the receive side, the newly launched FSWX signal and spectrum analyzer from Rohde & Schwarz is employed to perform the AI inference for Nokia’s AI receiver. In addition to enhancing coverage, the AI technology also demonstrates improved throughput and power efficiency, multiplying the benefits it will provide in the 6G era.
“One of the key issues facing future 6G deployments is the coverage limitations inherent in 6G’s higher-frequency spectrum. Typically, we would need to build denser networks with more cell sites to overcome this problem. By boosting the coverage of 6G receivers, however, AI technology will help us build 6G infrastructure over current 5G footprints,” said Peter Vetter, President, Core Research, Bell Labs, Nokia.
“Rohde & Schwarz is excited to collaborate with Nokia in pioneering AI-driven 6G receiver technology. Leveraging more than 90 years of experience in test and measurement, we’re uniquely positioned to support the development of next-generation wireless, allowing us to evaluate and refine AI algorithms at this crucial pre-standardization stage. This partnership builds on our long history of innovation and demonstrates our commitment to shaping the future of 6G,” said Michael Fischlein, VP, Spectrum & Network Analyzers, EMC and Antenna Test, Rohde & Schwarz.
…………………………………………………………………………………………………………………………………………………………………………………………
Last month, Nokia teamed up with rival kit vendor Ericsson to work on video coding standardization in preparation for 6G. The project, which also involved Berlin’s Fraunhofer Heinrich Hertz Institute (HHI), demonstrated a new video codec which they claim has higher compression efficiency than the current standards (H.264/AVC, H.265/HEVC, and H.266/VVC) without significantly increasing complexity, and its wider aim is to strengthen Europe’s role in next generation standardization, we were told at the time.
…………………………………………………………………………………………………………………………………………………………………………………………
About Nokia:
At Nokia, we create technology that helps the world act together.
As a B2B technology innovation leader, we are pioneering networks that sense, think and act by leveraging our work across mobile, fixed and cloud networks. In addition, we create value with intellectual property and long-term research, led by the award-winning Nokia Bell Labs, which is celebrating 100 years of innovation.
With truly open architectures that seamlessly integrate into any ecosystem, our high-performance networks create new opportunities for monetization and scale. Service providers, enterprises and partners worldwide trust Nokia to deliver secure, reliable and sustainable networks today – and work with us to create the digital services and applications of the future
About Rohde & Schwarz:
Rohde & Schwarz is striving for a safer and connected world with its Test & Measurement, Technology Systems and Networks & Cybersecurity Divisions. For over 90 years, the global technology group has pushed technical boundaries with developments in cutting-edge technologies. The company’s leading-edge products and solutions empower industrial, regulatory and government customers to attain technological and digital sovereignty. The privately owned, Munich-based company can act independently, long-term and sustainably. Rohde & Schwarz generated a net revenue of EUR 3.16 billion in the 2024/2025 fiscal year (July to June). On June 30, 2025, Rohde & Schwarz had more than 15,000 employees worldwide.
References:
ITU-R WP5D IMT 2030 Submission & Evaluation Guidelines vs 6G specs in 3GPP Release 20 & 21
ITU-R WP 5D reports on: IMT-2030 (“6G”) Minimum Technology Performance Requirements; Evaluation Criteria & Methodology
Market research firms Omdia and Dell’Oro: impact of 6G and AI investments on telcos
Nvidia pays $1 billion for a stake in Nokia to collaborate on AI networking solutions
Highlights of Nokia’s Smart Factory in Oulu, Finland for 5G and 6G innovation
Verizon’s 6G Innovation Forum joins a crowded list of 6G efforts that may conflict with 3GPP and ITU-R IMT-2030 work
Qualcomm CEO: expect “pre-commercial” 6G devices by 2028
NGMN: 6G Key Messages from a network operator point of view
Market research firms Omdia and Dell’Oro: impact of 6G and AI investments on telcos
Market research firm Omdia (owned by Informa) this week forecast that 6G and AI investments are set to drive industry growth in the global communications market. As a result, global communications providers’ revenue is expected to reach $5.6 trillion by 2030, growing at a 6.2% CAGR from 2025. Investment momentum is also expected to shift toward mobile networks from 2028 onward, as tier 1 markets prepare for 6G deployments. Telecoms capex is forecast to reach $395 billion by 2030, with a 3.6% CAGR, while technology capex will surge to $545 billion, reflecting a 9.3% CAGR.
Fixed telecom capex will gradually decline due to market saturation. Meanwhile, AI infrastructure, cloud services, and digital sovereignty policies are driving telecom operators to expand data centers and invest in specialized hardware.
Key market trends:
- CP capex per person will increase from $74 in 2024 to $116 in 2030, with CP capex reaching 2.5% of global GDP investment.
-
Capital intensity in telecom will decline until 2027, then rise due to mobile network upgrades.
-
Regional leaders in revenue and capex include North America, Oceania & Eastern Asia, and Western Europe, with Central & Southern Asia showing the highest growth potential.
Dario Talmesio, research director at Omdia said, “telecom operators are entering a new phase of strategic investment. With 6G on the horizon and AI infrastructure demands accelerating, the connectivity business is shifting from volume-based pricing to value-driven connectivity.”
Omdia’s forecast is based on a comprehensive model incorporating historical data from 67 countries, local market dynamics, regulatory trends, and technology migration patterns.
…………………………………………………………………………………………………………………………………………………
Separately, Dell’Oro Group sees 6G capex ramping around 2030, although it warns that the RAN market remains flat, “raising key questions for the industry’s future.” Cumulative 6G RAN investments over the 2029-2034 period are projected to account for 55% to 60% of the total RAN capex over the same forecast period.
“Our long-term position and characterization of this market have not changed,” said Stefan Pongratz, Vice President of RAN and Telecom Capex research at Dell’Oro Group. “The RAN network plays a pivotal role in the broader telecom market. There are opportunities to expand the RAN beyond the traditional MBB (mobile broadband) use cases. At the same time, there are serious near-term risks tilted to the downside, particularly when considering the slowdown in data traffic,” continued Pongratz.
Additional highlights from Dell’Oro’s October 2025 6G Advanced Research Report:
- The baseline scenario is for the broader RAN market to stay flat over the next 10 years. This is built on the assumption that the mobile network will run into utilization challenges by the end of the decade, spurring a 6G capex ramp dominated by Massive MIMO systems in the Sub-7GHz/cm Wave spectrum, utilizing the existing macro grid as much as possible.
- The report also outlines more optimistic and pessimistic growth scenarios, depending largely on the mobile data traffic growth trajectory and the impact beyond MBB, including private wireless and FWA (fixed wireless access).
- Cumulative 6G RAN investments over the 2029-2034 period are projected to account for 55 to 60 percent of the total RAN capex over the same forecast period.
Dell’Oro Group’s 6G Advanced Research Report offers an overview of the RAN market by technology, with tables covering manufacturers’ revenue for total RAN over the next 10 years. 6G RAN is analyzed by spectrum (Sub-7 GHz, cmWave, mmWave), by Massive MIMO, and by region (North America, Europe, Middle East and Africa, China, Asia Pacific Excl. China, and CALA). To purchase this report, please contact by email at [email protected].
References:
https://www.lightreading.com/6g/6g-momentum-is-building
6G Capex Ramp to Start Around 2030, According to Dell’Oro Group
https://www.lightreading.com/6g/6g-course-correction-vendors-hear-mno-pleas
https://www.lightreading.com/6g/what-at-t-really-wants-from-6g
Nvidia pays $1 billion for a stake in Nokia to collaborate on AI networking solutions
This is not only astonishing but unheard of: the world’s largest and most popular fabless semiconductor company –Nvidia– taking a $1 billion stake in a telco/reinvented data center connectivity company-Nokia.
Indeed, GPU king Nvidia will pay $1 billion for a stake of 2.9% in Nokia as part of a deal focused on AI and data centers, the Finnish telecom equipment maker said on Tuesday as its shares hit their highest level in nearly a decade on hope for AI to lift their business revenue and profits. The nonexclusive partnership and the investment will make Nvidia the second-largest shareholder in Nokia. Nokia said it will issue 166,389,351 new shares for Nvidia, which the U.S. company will subscribe to at $6.01 per share.
Nokia said the companies will collaborate on artificial intelligence networking solutions and explore opportunities to include its data center communications products in Nvidia’s future AI infrastructure plans. Nokia and its Swedish rival Ericsson both make networking equipment for connectivity inside (intra-) data centers and between (inter-) data centers and have been benefiting from increased AI use.
Summary:
- NVIDIA and Nokia to establish a strategic partnership to enable accelerated development and deployment of next generation AI native mobile networks and AI networking infrastructure.
- NVIDIA introduces NVIDIA Arc Aerial RAN Computer, a 6G-ready telecommunications computing platform.
- Nokia to expand its global access portfolio with new AI-RAN product based on NVIDIA platform.
- T-Mobile U.S. is working with Nokia and NVIDIA to integrate AI-RAN technologies into its 6G development process.
- Collaboration enables new AI services and improved consumer experiences to support explosive growth in mobile AI traffic.
- Dell Technologies provides PowerEdge servers to power new AI-RAN solution.
- Partnership marks turning point for the industry, paving the way to AI-native 6G by taking AI-RAN to innovation and commercialization at a global scale.
In some respects, this new partnership competes with Nvidia’s own data center connectivity solutions from its Mellanox Technologies division, which it acquired for $6.9 billion in 2019. Meanwhile, Nokia now claims to have worked on a redesign to ensure its RAN software is compatible with Nvidia’s compute unified device architecture (CUDA) platform, meaning it can run on Nvidia’s GPUs. Nvidia has also modified its hardware offer, creating capacity cards that will slot directly into Nokia’s existing AirScale baseband units at mobile sites.
Having dethroned Intel several years ago, Nvidia now has a near-monopoly in supplying GPU chips for data centers and has partnered with companies ranging from OpenAI to Microsoft. AMD is a distant second but is gaining ground in the data center GPU space as is ARM Ltd with its RISC CPU cores. Capital expenditure on data center infrastructure is expected to exceed $1.7 trillion by 2030, consulting firm McKinsey, largely because of the expansion of AI.
Nvidia CEO Jensen Huang said the deal would help make the U.S. the center of the next revolution in 6G. “Thank you for helping the United States bring telecommunication technology back to America,” Huang said in a speech in Washington, addressing Nokia CEO Justin Hotard (x-Intel). “The key thing here is it’s American technology delivering the base capability, which is the accelerated computing stack from Nvidia, now purpose-built for mobile,” Hotard told Reuters in an interview. “Jensen and I have been talking for a little bit and I love the pace at which Nvidia moves,” Hotard said. “It’s a pace that I aspire for us to move at Nokia.” He expects the new equipment to start contributing to revenue from 2027 as it goes into commercial deployment, first with 5G, followed by 6G after 2030.
Nvidia has been on a spending spree in recent weeks. The company in September pledged to invest $5 billion in beleaguered chip maker Intel. The investment pairs the world’s most valuable company, which has been a darling of the AI boom, with a chip maker that has almost completely fallen out of the AI conversation.
Later that month, Nvidia said it planned to invest up to $100 billion in OpenAI over an unspecified period that will likely span at least a few years. The partnership includes plans for an enormous data-center build-out and will allow OpenAI to build and deploy at least 10 gigawatts of Nvidia systems.
…………………………………………………………………………………………………………………………………………………………………………………………………………………………………
Tech Details:
Nokia uses Marvell Physical Layer (1) baseband chips for many of its products. Among other things, this ensured Nokia had a single software stack for all its virtual and purpose-built RAN products. Pallavi Mahajan, Nokia’s recently joined chief technology and AI officer recently told Light Reading that their software could easily adapt to run on Nvidia’s GPUs: “We built a hardware abstraction layer so that whether you are on Marvell, whether you are on any of the x86 servers or whether you are on GPUs, the abstraction takes away from that complexity, and the software is still the same.”
Fully independent software has been something of a Holy Grail for the entire industry. It would have ramifications for the whole market and its economics. Yet Nokia has conceivably been able to minimize the effort required to put its Layer 1 and specific higher-layer functions on a GPU. “There are going to be pieces of the software that are going to leverage on the accelerated compute,” said Mahajan. “That’s where we will bring in the CUDA integration pieces. But it’s not the entire software,” she added. The appeal of Nvidia as an alternative was largely to be found in “the programmability pieces that you don’t have on any other general merchant silicon,” said Mahajan. “There’s also this entire ecosystem, the CUDA ecosystem, that comes in.” One of Nvidia’s most eye-catching recent moves is the decision to “open source” Aerial, its own CUDA-based RAN software framework, so that other developers can tinker, she says. “What it now enables is the entire ecosystem to go out and contribute.”
…………………………………………………………………………………………………………………………………………………………………………………………………………………………………
Quotes:
“Telecommunications is a critical national infrastructure — the digital nervous system of our economy and security,” said Jensen Huang, founder and CEO of NVIDIA. “Built on NVIDIA CUDA and AI, AI-RAN will revolutionize telecommunications — a generational platform shift that empowers the United States to regain global leadership in this vital infrastructure technology. Together with Nokia and America’s telecom ecosystem, we’re igniting this revolution, equipping operators to build intelligent, adaptive networks that will define the next generation of global connectivity.”
“The next leap in telecom isn’t just from 5G to 6G — it’s a fundamental redesign of the network to deliver AI-powered connectivity, capable of processing intelligence from the data center all the way to the edge. Our partnership with NVIDIA, and their investment in Nokia, will accelerate AI-RAN innovation to put an AI data center into everyone’s pocket,” said Justin Hotard, President and CEO of Nokia. “We’re proud to drive this industry transformation with NVIDIA, Dell Technologies, and T-Mobile U.S., our first AI-RAN deployments in T-Mobile’s network will ensure America leads in the advanced connectivity that AI needs.”
……………………………………………………………………………………………………………………………………………………………………………………
Editor’s Notes:
1. In more advanced 5G networks, Physical Layer functions have demanded the support of custom silicon, or “accelerators.” A technique known as “lookaside,” favored by Ericsson and Samsung, uses an accelerator for only a single problematic Layer 1 task – forward error correction – and keeps everything else on the CPU. Nokia prefers the “inline” approach, which puts the whole of Layer 1 on the accelerator.
2. The huge AI-RAN push that Nvidia started with the formation of the AI-RAN Alliance in early 2024 has not met with an enthusiastic telco response so far. Results from Nokia as well as Ericsson show wireless network operators are spending less on 5G rollouts than they were in the early 2020s. Telco numbers indicate the appetite for smartphone and other mobile data services has not produced any sales growth. As companies prioritize efficiency above all else, baseband units that include Marvell and Nvidia cards may seem too expensive.
……………………………………………………………………………………………………………………………………………………………………………………….
Other Opinions and Quotes:
Nvidia chips are likely to be more expensive, said Mads Rosendal, analyst at Danske Bank Credit Research, but the proposed partnership would be mutually beneficial, given Nvidia’s large share in the U.S. data center market.
“This is a strong endorsement of Nokia’s capabilities,” said PP Foresight analyst Paolo Pescatore. “Next-generation networks, such as 6G, will play a significant role in enabling new AI-powered experiences,” he added.
Iain Morris, International Editor, Light Reading: “Layer 1 control software runs on ARM RISC CPU cores in both Marvell and Nvidia technologies. The bigger differences tend to be in the hardware acceleration “kernels,” or central components, which have some unique demands. Yet Nokia has been working to put as much as it possibly can into a bucket of common software. Regardless, if Nvidia is effectively paying for all this with its $1 billion investment, the risks for Nokia may be small………….Nokia’s customers will in future have an AI-RAN choice that limits or even shrinks the floorspace for Marvell. The development also points to more subtle changes in Nokia’s thinking. The message earlier this year was that Nokia did not require a GPU to implement AI for RAN, whereby machine-generated algorithms help to improve network performance and efficiency. Marvell had that covered because it had incorporated AI and machine-learning technologies into the baseband chips used by Nokia.”
“If you start doing inline, you typically get much more locked into the hardware,” said Per Narvinger, the president of Ericsson’s mobile networks business group, on a recent analyst call. During its own trials with Nvidia, Ericsson said it was effectively able to redeploy virtual RAN software written for Intel’s x86 CPUs on the Grace CPU with minimal changes, leaving the GPU only as a possible option for the FEC accelerator. Putting the entire Layer 1 on a GPU would mean “you probably also get more tightly into that specific implementation,” said Narvinger. “Where does it really benefit from having that kind of parallel compute system?”
………………………………………………………………………………………………………………………………………………….
Separately, Nokia and Nvidia will partner with T-Mobile U.S. to develop and test AI RAN technologies for developing 6G, Nokia said in its press release. Trials are expected to begin in 2026, focused on field validation of performance and efficiency gains for customers.
References:
https://nvidianews.nvidia.com/news/nvidia-nokia-ai-telecommunications
https://www.reuters.com/world/europe/nvidia-make-1-billion-investment-finlands-nokia-2025-10-28/
https://www.lightreading.com/5g/nvidia-takes-1b-stake-in-nokia-which-promises-5g-and-6g-overhaul
https://www.wsj.com/business/telecom/nvidia-takes-1-billion-stake-in-nokia-69f75bb6
Analysis: Cisco, HPE/Juniper, and Nvidia network equipment for AI data centers
Nvidia’s networking solutions give it an edge over competitive AI chip makers
Telecom sessions at Nvidia’s 2025 AI developers GTC: March 17–21 in San Jose, CA
Nvidia AI-RAN survey results; AI inferencing as a reinvention of edge computing?
FT: Nvidia invested $1bn in AI start-ups in 2024
The case for and against AI-RAN technology using Nvidia or AMD GPUs
Highlights of Nokia’s Smart Factory in Oulu, Finland for 5G and 6G innovation
Nokia & Deutsche Bahn deploy world’s first 1900 MHz 5G radio network meeting FRMCS requirements
Will the wave of AI generated user-to/from-network traffic increase spectacularly as Cisco and Nokia predict?
Indosat Ooredoo Hutchison and Nokia use AI to reduce energy demand and emissions
Verizon partners with Nokia to deploy large private 5G network in the UK
Omdia: How telcos will evolve in the AI era
Dario Talmesio, research director, service provider, strategy and regulation at market research firm Omdia (owned by Informa) sees positive signs for network operators.
“After many years of plumbing, now telecom operators are starting to see some of the benefits of their network and beyond network strategies. Furthermore, the investor community is now appreciating telecom investments, after many years of poor valuation, he said during his analyst keynote presentation at Network X, a conference organized by Light Reading and Informa in Paris, France last week.
“What has changed in the telecoms industry over the past few years is the fact that we are no longer in a market that is in contraction,” he said. Although telcos are generally not seeing double-digit percentage increases in revenue or profit, “it’s a reliable business … a business that is able to provide cash to investors.”
Omdia forecasts that global telecoms revenue will have a CAGR of 2.8% in the 2025-2030 timeframe. In addition, the industry has delivered two consecutive years of record free cash flow, above 17% of sales.
However, Omdia found that telcos have reduced capex, which is trending towards 15% of revenues. Opex fell by -0.2% in 2024 and is broadly flatlining. There was a 2.2% decline in global labor opex following the challenging trend in 2023, when labor opex increased by 4% despite notable layoffs.
“Overall, the positive momentum is continuing, but of course there is more work to be done on the efficiency side,” Talmesio said. He added that it is also still too early to say what impact AI investments will have over the longer term. “All the work that has been done so far is still largely preparatory, with visible results expected to materialize in the near(ish) future,” he added. His Network X keynote presentation addressed the following questions:
- How will telcos evolve their operating structures and shift their business focuses in the next 5 years?
- AI, cloud and more to supercharge efficiencies and operating models?
- How will big tech co-opetition evolve and impact traditional telcos?
Customer care was seen as the area first impacted by AI, building on existing GenAI implementations. In contrast, network operations are expected to ultimately see the most significant impact of agentic AI.
Talmesio said many of the building blocks are in place for telecoms services and future revenue generation, with several markets reaching 60% to 70% fiber coverage, and some even approaching 100%.
Network operators are now moving beyond monetizing pure data access and are able to charge more for different gigabit speeds, home gaming, more intelligent home routers and additional WiFi access points, smart home services such as energy, security and multi-room video, and more.
While noting that connectivity remains the most important revenue driver, when contributions from various telecoms-adjacent services are added up “it becomes a significant number,” Talmesio said.
Mobile networks are another important building block. While acknowledging that 5G has been something of a disappointment in the first five years of the deployment cycle, “this is really changing” as more operators deploy 5G standalone (5G SA core) networks, Omdia observed.
Talmesio said: “At the end of June, there were only 66 telecom operators launching or commercially using 5G SA. But those 66 operators are those operators that carry the majority of the world’s 5G subscribers. And with 5G SA, we have improved latency and more devices among other factors. Monetization is still in its infancy, perhaps, but then you can see some really positive progress in 5G Advanced, where as of June, we had 13 commercial networks available with some good monetization examples, including uplink.”
“Telecom is moving beyond telecoms,” with a number of new AI strategies in place. For example, telcos are increasingly providing AI infrastructure in their data centers, offering GPU as-a-service, AI-related colocation, AI-RAN and edge AI functionality.
Dario Talmesio, Omdia
……………………………………………………………………………………………………………………………………………………
AI is also being used for network management, with AI productivity tools and AI digital assistants, as well as AI software services including GenAI products and services for consumer, enterprises and vertical markets.
“There is an additional boost for telecom operators to move beyond connectivity, which is the sovereignty agenda,” Talmesio noted. While sovereignty in the past was largely applied to data residency, “in reality, there are more and more aspects of sovereignty that are in many ways facilitating telecom operators in retaining or entering business areas that probably ten years ago were unthinkable for them.” These include cloud and data center infrastructure, sovereign AI, cyberdefense and quantum safety, satellite communication, data protection and critical communications.
“The telecom business is definitely improving,” Talmesio concluded, noting that the market is now also being viewed more favorably by investors. “In many ways, the glass is maybe still half full, but there’s more water being poured into the telecom industry.”
References:
https://networkxevent.com/speakers/dario-talmesio/
https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/pushing-telcos-ai-envelope-on-capital-decisions
Omdia on resurgence of Huawei: #1 RAN vendor in 3 out of 5 regions; RAN market has bottomed
Omdia: Huawei increases global RAN market share due to China hegemony
Dell’Oro & Omdia: Global RAN market declined in 2023 and again in 2024
Omdia: Cable network operators deploy PONs
Qualcomm CEO: expect “pre-commercial” 6G devices by 2028
During his keynote speech at the 2025 Snapdragon Summit in Maui, Qualcomm CEO Cristiano Amon said:
“We have been very busy working on the next generation of connectivity…which is 6G. Designed to be the connection between the cloud and Edge devices, The difference between 5G and 6G, besides increasing the speeds, increasing broadband, increasing the amount of data, it’s also a network that has intelligence to have perception and sensor data. We’re going to have completely new use cases for this network of intelligence — connecting the edge and the cloud.”
“We have been working on this (6G) for a while, and it’s sooner than you think. We are ready to have pre-commercial devices with 6G as early as 2028. And when we get that, we’re going to have context aware intelligence at scale.”
…………………………………………………………………………………………………………………………………………………………………………………………..
Analysis: Let’s examine that statement, in light of the ITU-R IMT 2030 recommendations not scheduled to be completed until the end of 2030:
“pre-commercial devices” are not meant for general consumers while “as early as” leaves open the possibility that those 6G devices might not be available until after 2028.
…………………………………………………………………………………………………………………………………………………………………………………………..
Looking ahead at the future of devices, Amon noted that 6G would play a key role in the evolution of AI technology, with AI models becoming hybrid. This includes a combination of cloud and edge devices (like user interfaces, sensors, etc). According to Qualcomm, 6G will make this happen. Anon envisions a future where AI agents are a crucial part of our daily lives, upending the way we currently use our connected devices. He firmly believes that smartphones, laptops, cars, smart glasses, earbuds, and more will have a direct line of communication with these AI agents — facilitated by 6G connectivity.
Opinion: This sounds very much like the hype around 5G ushering a whole new set of ultra-low latency applications which never happened (because the 3GPP specs for URLLC were not completed in June 2020 when Release 16 was frozen). Also, very few mobile operators deployed 5G SA core, without which there are no 5G features, like network slicing and security.
Separately, Nokia Bell Labs has said that in the coming 6G era, “new man-machine interfaces” controlled by voice and gesture input will gradually replace more traditional inputs, like typing on touchscreens. That’s easy to read as conjecture, but we’ll have to see if that really happens when the first commercial 5G networks are deployed in late 2030- early 2031.
We’re sure to see faster network speeds with higher amounts of data with 6G with AI in more devices, but standardized 6G is still at least five years from being a commercial reality.
References:
https://www.androidauthority.com/qualcomm-6g-2028-3600781/
https://www.nokia.com/6g/6g-explained/
ITU-R WP5D IMT 2030 Submission & Evaluation Guidelines vs 6G specs in 3GPP Release 20 & 21
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
Ericsson and e& (UAE) sign MoU for 6G collaboration vs ITU-R IMT-2030 framework
Highlights of 3GPP Stage 1 Workshop on IMT 2030 (6G) Use Cases
6th Digital China Summit: China to expand its 5G network; 6G R&D via the IMT-2030 (6G) Promotion Group
MediaTek overtakes Qualcomm in 5G smartphone chip market
SoftBank’s Transformer AI model boosts 5G AI-RAN uplink throughput by 30%, compared to a baseline model without AI
Softbank has developed its own Transformer-based AI model that can be used for wireless signal processing. SoftBank used its Transformer model to improve uplink channel interpolation which is a signal processing technique where the network essentially makes an educated guess as to the characteristics and current state of a signal’s channel. Enabling this type of intelligence in a network contributes to faster, more stable communication, according to SoftBank. The Japanese wireless network operator successfully increased uplink throughput by approximately 20% compared to a conventional signal processing method (the baseline method). In the latest demonstration, the new Transformer-based architecture was run on GPUs and tested in a live Over-the-Air (OTA) wireless environment. In addition to confirming real-time operation, the results showed further throughput gains and achieved ultra-low latency.
Editor’s note: A Transformer model is a type of neural network architecture that emerged in 2017. It excels at interpreting streams of sequential data associated with large language models (LLMs). Transformer models have also achieved elite performance in other fields of artificial intelligence (AI), including computer vision, speech recognition and time series forecasting. Transformer models are lightweight, efficient, and versatile – capable of natural language processing (NLP), image recognition and wireless signal processing as per this Softbank demo.
Significant throughput improvement:
- Uplink channel interpolation using the new architecture improved uplink throughput by approximately 8% compared to the conventional CNN model. Compared to the baseline method without AI, this represents an approximately 30% increase in throughput, proving that the continuous evolution of AI models leads to enhanced communication quality in real-world environments.
Higher AI performance with ultra-low latency:
- While real-time 5G communication requires processing in under 1 millisecond, this demonstration with the Transformer achieved an average processing time of approximately 338 microseconds, an ultra-low latency that is about 26% faster than the convolution neural network (CNN) [1.] based approach. Generally, AI model processing speeds decrease as performance increases. This achievement overcomes the technically difficult challenge of simultaneously achieving higher AI performance and lower latency. Editor’s note: Perhaps this can overcome the performance limitations in ITU-R M.2150 for URRLC in the RAN, which is based on an uncompleted 3GPP Release 16 specification.
Note 1. CNN-based approaches to achieving low latency focus on optimizing model architecture, computation, and hardware to accelerate inference, especially in real-time applications. Rather than relying on a single technique, the best results are often achieved through a combination of methods.
Using the new architecture, SoftBank conducted a simulation of “Sounding Reference Signal (SRS) prediction,” a process required for base stations to assign optimal radio waves (beams) to terminals. Previous research using a simpler Multilayer Perceptron (MLP) AI model for SRS prediction confirmed a maximum downlink throughput improvement of about 13% for a terminal moving at 80 km/h.*2
In the new simulation with the Transformer-based architecture, the downlink throughput for a terminal moving at 80 km/h improved by up to approximately 29%, and by up to approximately 31% for a terminal moving at 40 km/h. This confirms that enhancing the AI model more than doubled the throughput improvement rate (see Figure 1). This is a crucial achievement that will lead to a dramatic improvement in communication speeds, directly impacting the user experience.
The most significant technical challenge for the practical application of “AI for RAN” is to further improve communication quality using high-performance AI models while operating under the real-time processing constraint of less than one millisecond. SoftBank addressed this by developing a lightweight and highly efficient Transformer-based architecture that focuses only on essential processes, achieving both low latency and maximum AI performance. The important features are:
(1) Grasps overall wireless signal correlations
By leveraging the “Self-Attention” mechanism, a key feature of Transformers, the architecture can grasp wide-ranging correlations in wireless signals across frequency and time (e.g., complex signal patterns caused by radio wave reflection and interference). This allows it to maintain high AI performance while remaining lightweight. Convolution focuses on a part of the input, while Self-Attention captures the relationships of the entire input (see Figure 2).
(2) Preserves physical information of wireless signals
While it is common to normalize input data to stabilize learning in AI models, the architecture features a proprietary design that uses the raw amplitude of wireless signals without normalization. This ensures that crucial physical information indicating communication quality is not lost, significantly improving the performance of tasks like channel estimation.
(3) Versatility for various tasks
The architecture has a versatile, unified design. By making only minor changes to its output layer, it can be adapted to handle a variety of different tasks, including channel interpolation/estimation, SRS prediction, and signal demodulation. This reduces the time and cost associated with developing separate AI models for each task.
The demonstration results show that high-performance AI models like Transformer and the GPUs that run them are indispensable for achieving the high communication performance required in the 5G-Advanced and 6G eras. Furthermore, an AI-RAN that controls the RAN on GPUs allows for continuous performance upgrades through software updates as more advanced AI models emerge, even after the hardware has been deployed. This will enable telecommunication carriers to improve the efficiency of their capital expenditures and maximize value.
Moving forward, SoftBank will accelerate the commercialization of the technologies validated in this demonstration. By further improving communication quality and advancing networks with AI-RAN, SoftBank will contribute to innovation in future communication infrastructure. The Japan based conglomerate strongly endorsed AI RAN at MWC 2025.
References:
https://www.softbank.jp/en/corp/news/press/sbkk/2025/20250821_02/
https://www.telecoms.com/5g-6g/softbank-claims-its-ai-ran-tech-boosts-throughput-by-30-
https://www.telecoms.com/ai/softbank-makes-mwc-25-all-about-ai-ran
https://www.ibm.com/think/topics/transformer-model
https://www.itu.int/rec/R-REC-M.2150/en
Softbank developing autonomous AI agents; an AI model that can predict and capture human cognition
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
Dell’Oro: RAN revenue growth in 1Q2025; AI RAN is a conundrum
Nvidia AI-RAN survey results; AI inferencing as a reinvention of edge computing?
OpenAI announces new open weight, open source GPT models which Orange will deploy
Deutsche Telekom and Google Cloud partner on “RAN Guardian” AI agent
Ericsson reports ~flat 2Q-2025 results; sees potential for 5G SA and AI to drive growth
Ericsson’s second-quarter results were not impressive, with YoY organic sales growth of +2% for the company and +3% for its network division (its largest). Its $14 billion AT&T OpenRAN deal, announced in December of 2023, helped lift Swedish vendor’s share of the global RAN market by +1.4 percentage points in 2024 to 25.7%, according to new research from analyst company Omdia (owned by Informa). As a result of its AT&T contract, the U.S. accounted for a stunning 44% of Ericsson’s second-quarter sales while the North American market resulted in a 10% YoY increase in organic revenues to SEK19.8bn ($2.05bn). Sales dropped in all other regions of the world! The charts below depict that very well:
Ericsson’s attention is now shifting to a few core markets that Ekholm has identified as strategic priorities, among them the U.S., India, Japan and the UK. All, unsurprisingly, already make up Ericsson’s top five countries by sales, although their contribution minus the US came to just 15% of turnover for the recent second quarter. “We are already very strong in North America, but we can do more in India and Japan,” said Ekholm. “We see those as critically important for the long-term success.”
Opportunities: As telco investment in RAN equipment has declined by 12.5% (or $5 billion) last year, the Swedish equipment vendor has had few other obvious growth opportunities. Ericsson’s Enterprise division, which is supposed to be the long-term provider of sales growth for Ericsson, is still very small – its second-quarter revenues stood at just SEK5.5bn ($570m) and even once currency exchange changes are taken into account, its sales shrank by 6% YoY.
On Tuesday’s earnings call, Ericsson CEO Börje Ekholm said that the RAN equipment sector, while stable currently, isn’t offering any prospects of exciting near-term growth. For longer-term growth the industry needs “new monetization opportunities” and those could come from the ongoing modest growth in 5G-enabled fixed wireless access (FWA) deployments, from 5G standalone (SA) deployments that enable mobile network operators to offer “differentiated solutions” and from network APIs (that ultra hyped market is not generating meaningful revenues for anyone yet).
Cost Cutting Continues: Ericsson also has continued to be aggressive about cost reduction, eliminating thousands of jobs since it completed its Vonage takeover. “Over the last year, we have reduced our total number of employees by about 6% or 6,000,” said Ekholm on his routine call with analysts about financial results. “We also see and expect big benefits from the use of AI and that is one reason why we expect restructuring costs to remain elevated during the year.”
Use of AI: Ericsson sees AI as an opportunity to enable network automation and new industry revenue opportunities. The company is now using AI as an aid in network design – a move that could have negative ramifications for staff involved in research and development. Ericsson is already using AI for coding and “other parts of internal operations to drive efficiency… We see some benefits now. And it’s going to impact how the network is operated – think of fully autonomous, intent-based networks that will require AI as a fundamental component. That’s one of the reasons why we invested in an AI factory,” noted the CEO, referencing the consortium-based investment in a Swedish AI Factory that was announced in late May. At the time, Ericsson noted that it planned to “leverage its data science expertise to develop and deploy state-of-the-art AI models – improving performance and efficiency and enhancing customer experience.
Ericsson is also building AI capability into the products sold to customers. “I usually use the example of link adaptation,” said Per Narvinger, the head of Ericsson’s mobile networks business group, on a call with Light Reading, referring to what he says is probably one of the most optimized algorithms in telecom. “That’s how much you get out of the spectrum, and when we have rewritten link adaptation, and used AI functionality on an AI model, we see we can get a gain of 10%.”
Ericsson hopes that AI will boost consumer and business demand for 5G connectivity. New form factors such as smart glasses and AR headsets will need lower-latency connections with improved support for the uplink, it has repeatedly argued. But analysts are skeptical, while Ericsson thinks Europe is ill equipped for more advanced 5G services.
“We’re still very early in AI, in [understanding] how applications are going to start running, but I think it’s going to be a key driver of our business going forward, both on traffic, on the way we operate networks, and the way we run Ericsson,” Ekholm said.
Europe Disappoints: In much of Europe, Ericsson and Nokia have been frustrated by some government and telco unwillingness to adopt the European Union’s “5G toolbox” recommendations and evict Chinese vendors. “I think what we have seen in terms of implementation is quite varied, to be honest,” said Narvinger. Rather than banning Huawei outright, Germany’s government has introduced legislation that allows operators to use most of its RAN products if they find a substitute for part of Huawei’s management system by 2029. Opponents have criticized that move, arguing it does not address the security threat posed by Huawei’s RAN software. Nevertheless, Ericsson clearly eyes an opportunity to serve European demand for military communications, an area where the use of Chinese vendors would be unthinkable.
“It is realistic to say that a large part of the increased defense spending in Europe will most likely be allocated to connectivity because that is a critical part of a modern defense force,” said Ekholm. “I think this is a very good opportunity for western vendors because it would be far-fetched to think they will go with high-risk vendors.” Ericsson is also targeting related demand for mission-critical services needed by first responders.
5G SA and Mobile Core Networks: Ekholm noted that 5G SA deployments are still few and far between – only a quarter of mobile operators have any kind of 5G SA deployment in place right now, with the most notable being in the US, India and China. “Two things need to happen,” for greater 5G SA uptake, stated the CEO.
- “One is mid-band [spectrum] coverage… there’s still very low build out coverage in, for example, Europe, where it’s probably less than half the population covered… Europe is clearly behind on that“ compared with the U.S., China and India.
- “The second is that [network operators] need to upgrade their mobile core [platforms]... Those two things will have to happen to take full advantage of the capabilities of the [5G] network,” noted Ekholm, who said the arrival of new devices, such as AI glasses, that require ultra low latency connections and “very high uplink performance” is starting to drive interest. “We’re also seeing a lot of network slicing opportunities,” he added, to deliver dedicated network resources to, for example, police forces, sports and entertainment stadiums “to guarantee uplink streams… consumers are willing to pay for these things. So I’m rather encouraged by the service innovation that’s starting to happen on 5G SA and… that’s going to drive the need for more radio coverage [for] mid-band and for core [systems].”
Ericsson’s Summary -Looking Ahead:
- Continue to strengthen competitive position
- Strong customer engagement for differentiated connectivity
- New use cases to monetize network investments taking shape
- Expect RAN market to remain broadly stable
- Structurally improving the business through rigorous cost management
- Continue to invest in technology leadership
………………………………………………………………………………………………………………………………………………………………………………………………
References:
https://www.telecomtv.com/content/5g/ericsson-ceo-waxes-lyrical-on-potential-of-5g-sa-ai-53441/
https://www.lightreading.com/5g/ericsson-targets-big-huawei-free-places-ai-and-nato-as-profits-soar
Ericsson revamps its OSS/BSS with AI using Amazon Bedrock as a foundation
Dell’Oro: AI RAN to account for 1/3 of RAN market by 2029; AI RAN Alliance membership increases but few telcos have joined
AI RAN [1.] is projected to account for approximately a third of the RAN market by 2029, according to a recent AI RAN Advanced Research Report published by the Dell’Oro Group. In the near term, the focus within the AI RAN segment will center on Distributed-RAN (D-RAN), single-purpose deployments, and 5G.
“Near-term priorities are more about efficiency gains than new revenue streams,” said Stefan Pongratz, Vice President at Dell’Oro Group. “There is strong consensus that AI RAN can improve the user experience, enhance performance, reduce power consumption, and play a critical role in the broader automation journey. Unsurprisingly, however, there is greater skepticism about AI’s ability to reverse the flat revenue trajectory that has defined operators throughout the 4G and 5G cycles,” continued Pongratz.
Note 1. AI RAN integrates AI and machine learning (ML) across various aspects of the RAN domain. The AI RAN scope in this report is aligned with the greater industry vision. While the broader AI RAN vision includes services and infrastructure, the projections in this report focus on the RAN equipment market.
Additional highlights from the July 2025 AI RAN Advanced Research Report:
- The base case is built on the assumption that AI RAN is not a growth vehicle. But it is a crucial technology/tool for operators to adopt. Over time, operators will incorporate more virtualization, intelligence, automation, and O-RAN into their RAN roadmaps.
- This initial AI RAN report forecasts the AI RAN market based on location, tenancy, technology, and region.
- The existing RAN radio and baseband suppliers are well-positioned in the initial AI-RAN phase, driven primarily by AI-for-RAN upgrades leveraging the existing hardware. Per Dell’Oro Group’s regular RAN coverage, the top 5 RAN suppliers contributed around 95 percent of the 2024 RAN revenue.
- AI RAN is projected to account for around a third of total RAN revenue by 2029.
In the first quarter of 2025, Dell’Oro said the top five RAN suppliers based on revenues outside of China are Ericsson, Nokia, Huawei, Samsung and ZTE. In terms of worldwide revenue, the ranking changes to Huawei, Ericsson, Nokia, ZTE and Samsung.
About the Report: Dell’Oro Group’s AI RAN Advanced Research Report includes a 5-year forecast for AI RAN by location, tenancy, technology, and region. Contact: [email protected]
………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………
Author’s Note: Nvidia’s Aerial Research portfolio already contains a host of AI-powered tools designed to augment wireless network simulations. It is also collaborating with T-Mobile and Cisco to develop AI RAN solutions to support future 6G applications. The GPU king is also working with some of those top five RAN suppliers, Nokia and Ericsson, on an AI-RAN Innovation Center. Unveiled last October, the project aims to bring together cloud-based RAN and AI development and push beyond applications that focus solely on improving efficiencies.
……………………………………………………………………………………………………………………………………………………………………………………………………………………………………………….
The one year old AI RAN Alliance has now increased its membership to over 100, up from around 84 in May. However, there are not many telco members with only Vodafone joining since May. The other telco members are: Turkcell ,Boost Mobile, Globe, Indosat Ooredoo Hutchison (Indonesia), Korea Telecom, LG UPlus, SK Telecom, T-Mobile US and Softbank. This limited telco presence could reflect the ongoing skepticism about the goals of AI-RAN, including hopes for new revenue opportunities through network slicing, as well as hosting and monetizing enterprise AI workloads at the edge.
Francisco Martín Pignatelli, head of open RAN at Vodafone, hardly sounded enthusiastic in his statement in the AI-RAN Alliance press release. “Vodafone is committed to using AI to optimize and enhance the performance of our radio access networks. Running AI and RAN workloads on shared infrastructure boosts efficiency, while integrating AI and generative applications over RAN enables new real-time capabilities at the network edge,” he added.
Perhaps, the most popular AI RAN scenario is “AI on RAN,” which enables AI services on the RAN at the network edge in a bid to support and benefit from new services, such as AI inferencing.
“We are thrilled by the extraordinary growth of the AI-RAN Alliance,” said Alex Jinsung Choi, Chair of the AI-RAN Alliance and Principal Fellow at SoftBank Corp.’s Research Institute of Advanced Technology. “This milestone underscores the global momentum behind advancing AI for RAN, AI and RAN, and AI on RAN. Our members are pioneering how artificial intelligence can be deeply embedded into radio access networks — from foundational research to real-world deployment — to create intelligent, adaptive, and efficient wireless systems.”
Choi recently suggested that now is the time to “revisit all our value propositions and then think about what should be changed or what should be built” to be able to address issues including market saturation and the “decoupling” between revenue growth and rising TCO. He also cited self-driving vehicles and mobile robots, where low latency is critical, as specific use cases where AI-RAN will be useful for running enterprise workloads.
About the AI-RAN Alliance:
The AI-RAN Alliance is a global consortium accelerating the integration of artificial intelligence into Radio Access Networks. Established in 2024, the Alliance unites leading companies, researchers, and technologists to advance open, practical approaches for building AI-native wireless networks. The Alliance focuses on enabling experimentation, sharing knowledge, and real-world performance to support the next generation of mobile infrastructure. For more information, visit: https://ai-ran.org
References:
https://www.delloro.com/advanced-research-report/ai-ran/
https://www.delloro.com/news/ai-ran-to-top-10-billion-by-2029/
Dell’Oro: RAN revenue growth in 1Q2025; AI RAN is a conundrum
AI RAN Alliance selects Alex Choi as Chairman
Nvidia AI-RAN survey results; AI inferencing as a reinvention of edge computing?
Deutsche Telekom and Google Cloud partner on “RAN Guardian” AI agent
The case for and against AI-RAN technology using Nvidia or AMD GPUs
