Author: Alan Weissberger
Analysis: OpenAI and Deutsche Telekom launch multi-year AI collaboration
Deutsche Telekom (DT) has formalized a strategic, multi-year collaboration with OpenAI to integrate advanced artificial intelligence (AI) solutions across its internal operations and customer engagement platforms. The partnership aims to co-develop “simple, personal, and multi-lingual AI experiences” focused on enhancing communication and productivity. Initial pilot programs are slated for deployment in Q1 2026. AI will also play a larger role in customer care, internal copilots, and network operations as the Group advances toward more autonomous, self-healing networks.DT plans a company-wide rollout of ChatGPT Enterprise, leveraging AI to streamline core functions including:
- Customer Care: Deploying sophisticated virtual assistants to manage billing inquiries, service outages, plan modifications, roaming support, and device troubleshooting [1].
- Internal Operations: Utilizing AI copilots to increase internal efficiency.
- Network Management: Optimizing core network provisioning and operations.
- Sovereign Cloud (2021): DT’s T-Systems division partnered with Google Cloud to offer sovereign cloud services.
- T Cloud Suite (Early 2025): The launch of a comprehensive suite providing sovereign public, private, and AI cloud options leveraging hybrid infrastructure.
- Industrial AI Cloud (Early 2025): A collaboration with Nvidia to build a dedicated industrial AI data center in Munich, scheduled for Q1 2026 operations.
- Edge AI compute services for enterprises.
- Vertical AI solutions tailored for healthcare, retail, and manufacturing sectors.
- Integrated private 5G and AI bundles for industrial logistical hubs.
“Telcos – if they execute – will have a big play in the edge inferencing space as well as providing hosting and colo services that can host domain specific SLMs that need to be run closer to the user data,” he said. “Furthermore, telcos will play a role in connectivity services across Neocloud providers such as CoreWeave, Lambda Labs, Digital Ocean, Vast.AI etc. OpenAI does not want to lose the opportunity to partner with telcos so they are striking early,” Nag added.
Other Voices:
- Roger Entner notes the model is highly applicable to European incumbents (e.g., Orange, Telefonica) due to the relative scarcity of existing AI data centers in the region, allowing operators to fill a critical infrastructure gap. Conversely, the model is less viable for U.S. operators, where hyperscalers already dominate the extensive data center market.
- AvidThink Founder and colleague Roy Chua cautions that while DT presents a robust “reference blueprint,” replicating this strategy requires significant scale, substantial financial investment, and regulatory alignment—factors not easily accessible to all network operators.
- Futurum Group VP and Practice Lead Nick Patience told Fierce Network, “This deal elevates DT from being a user of AI to being a co-developer, which is pretty significant. DT is one of the few operators building a full-stack AI story. This is an example of OpenAI treating telcos as high-scale distribution and data channels – customer care, billing, network telemetry, national reach and government relationships. This suggests OpenAI is deliberately building an operator channel in key regions (U.S., Korea, EU) but still in partnership with existing cloud and infra providers rather than displacing them.”
OpenAI has established significant partnerships with several telecom network providers and related technology companies to integrate AI into network operations, enhance customer experience, and develop new AI-native platforms. Those deals and collaborations include:
- T-Mobile: T-Mobile has a multi-year agreement with OpenAI and is actively testing the integration of AI (specifically IntentCX) into its business operations for customer service improvements. T-Mobile is also collaborating with Nokia and Nvidia on AI-RAN (Radio Access Network) technologies for 6G innovation.
- SK Telecom (SKT): SK Telecom has an in-house AI company and collaborates with OpenAI and other AI leaders like Anthropic to enhance its AI capabilities, build sovereign AI infrastructure, and explore new services for its customers in South Korea and globally. They are also reportedly integrating Perplexity into their offerings.
- Deutsche Telekom (DT): DT is partnering with OpenAI to offer ChatGPT Enterprise across its business to help teams work more effectively, improve customer service, and automate network operations.
- Circles: This global telco technology company and OpenAI announced a strategic global collaboration to build a fully AI-native telco SaaS platform, which will first launch in Singapore. The platform aims to revolutionize the consumer experience and drive operational efficiencies for telcos worldwide.
- Rakuten: Rakuten and OpenAI launched a strategic partnership to develop AI tools and a platform aimed at leveraging Rakuten’s Open RAN expertise to revolutionize the use of AI in telecommunications.
- Orange: Orange is working with OpenAI to drive new use cases for enterprise needs, manage networks, and enable innovative customer care solutions, including those that support African regional languages.
- Indian Telecoms (Reliance Jio, Airtel): Telecom providers in India are integrating AI tools from companies like Google and Perplexity into their mobile subscriptions, providing millions of users access to advanced intelligence resources.
- Nokia & Nvidia: In a broader industry collaboration, Nvidia invested $1 billion in Nokia to add Nvidia-powered AI-RAN products to Nokia’s portfolio, enabling telecom service providers to launch AI-native 5G-Advanced and 6G networks. This partnership also includes T-Mobile US for testing.
Conclusions:
With more than 261 million mobile customers globally, Deutsche Telekom provides a strong foundation to bring AI into everyday use at scale. The new collaboration marks the next step in Deutsche Telekom’s AI journey – moving from early pilots to large-scale products that make AI useful for everyone
References:
https://www.telekom.com/en/media/media-information/archive/openai-and-telekom-collaborate-1100164
https://www.telekom.com/en/company/companyprofile/company-profile-625808
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OpenAI and Broadcom in $10B deal to make custom AI chips
Custom AI Chips: Powering the next wave of Intelligent Computing
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Telecom network outages: causes, effects, and remedies for telecom providers & IT enterprise
Network outages, historically caused by misconfigurations, software defects, or hardware failures, are increasingly disruptive for several reasons, such as hyper-connectivity, single points of failure and over-reliance on concentrated hyperscaler cloud infrastructures. This leads to an expanded “blast radius” from single points of failure. The latest Cloudflare outage reveals that enterprises heavily reliant on a dangerously few major IT providers face critical single points of failure, leading to authentication issues, lost revenue, and broken customer experiences.
Cloudflare is a global cloud services and cybersecurity firm. It provides data centers, website and email security, protection from data loss and defences against cyber threats, among other things. It describes itself as providing an “immune system for the internet”, with technology that sits between its clients and the wider world that blocks billions of cyber threats daily. It also uses its global infrastructure to speed up internet traffic. It makes more than $500m – a quarter from nearly 300,000 customers operating in 125 countries, including China. Users of several heavy-traffic websites reported that they went offline at the same time as the Cloudflare outage.
Akamai’s Reuben Koh advocates for a distributed compute and edge architecture, which acts as autonomous cells to mitigate systemic risk and improve resilience via graceful degradation. He also suggests adopting strategies like graceful degradation and diversifying cloud providers which help telecom operators and other organizations limit the spread of outage disruption.
Computer outage, error or failure causing by software update mistake, operating system crash or cyber attack, server down or technical issue concept, people victims looking at computer laptop outage.
- Systemic Risk Assessment: Regulations, such as the EU’s Digital Operational Resilience Act (DORA) which is effective from January 17, 2025, are moving from assessing a single firm’s risk to evaluating the broader market impact of a critical third-party provider failure. DORA specifically designates critical ICT third-party providers subject to direct oversight.
- Operational Resilience Mandates: Jurisdictions are pushing firms to demonstrate the ability to maintain operations or safely exit a non-performing CSP relationship. This includes requirements for robust contingency and exit plans.
- Geographic Examples:
–Singapore is framing cloud infrastructure as essential national computing, issuing specific resilience guidelines.–Australia has issued warnings to financial institutions regarding over-dependence on a narrow set of US-based hyperscalers.–Japan is tightening scrutiny and expectations around managing third-party cloud risks.
- Continuous Discovery & Inventory: Telecom operators must maintain an up-to-date, comprehensive inventory of all APIs (managed, unmanaged, “shadow,” and “zombie”) across the enterprise.
- Shift-Left Security: Integrate security testing and design principles early into the software development lifecycle to identify and remediate vulnerabilities before APIs reach production environments.
- Implement Zero Trust Architecture (ZTA): Adopt a “never trust, always verify” approach, assuming an attacker may already be internal. This means applying strict authentication and authorization controls at the API level, not just the network perimeter.
- Strong Authentication and Authorization: Use robust mechanisms like OAuth 2.0 and OpenID. Connect, employing the principle of least privilege to ensure entities only have the minimum necessary access.
- Runtime Protection and Monitoring: Implement API gateways for centralized traffic management, rate limiting to prevent Denial-of-Service (DoS) attacks, and use behavioral analytics to detect anomalous activity indicative of abuse.
- Input Validation and Data Handling: Strictly validate and sanitize all data inputs to prevent injection attacks, and ensure APIs only expose necessary information to minimize data leakage.
- Human Oversight in AI: As AI and automation increase, maintain robust human oversight in change management and incident response, as AI systems can behave unpredictably. Telecom staff should be closely involved in change management and incident response, even as network automation increases.
Note 1. The UK’s Telecommunications Security Act – 2021 is a landmark law establishing mandatory, tough security standards for public telecom networks, making cybersecurity a legal duty for providers to protect critical infrastructure. It empowers regulator Ofcom, introduces penalties for non-compliance (up to 10% of turnover), and mandates adherence to specific security measures in the Code of Practice (CoP) through phased deadlines, requiring strong governance, supply chain security, and proactive threat management.
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Conclusions:
Koh advocates for the implementation of resilient network architectures and improved operational maturity to enhance system fault tolerance. Key steps include distributed design, optimized operational protocols, comprehensive network visibility, and pragmatic capacity planning. These measures are becoming increasingly important as telecommunications infrastructure underpins essential societal functions.
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References:
What telecom operators can learn from recent network outages
Cloudflare outage highlights enterprise infrastructure dependence
https://www.techtarget.com/whatis/feature/8-largest-IT-outages-in-history
España hit with major telecom blackout after power outage April 28th
Comcast frequent, intermittent internet outages + long outage in Santa Clara, CA with no auto-recovery!
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Rogers Telecommunications restores service after 19 hour outage disrupting life in Canada
GSMA, ETSI, IEEE, ITU & TM Forum: AI Telco Troubleshooting Challenge + TelecomGPT: a dedicated LLM for telecom applications
Rogers Telecommunications restores service after 19 hour outage disrupting life in Canada
Custom AI Chips: Powering the next wave of Intelligent Computing
by the Indxx team of market researchers with Alan J Weissberger
The Market for AI Related Semiconductors:
Several market research firms and banks forecast that revenue from AI-related semiconductors will grow at about 18% annually over the next few years—five times faster than non-AI semiconductor market segments.
- IDC forecasts that global AI hardware spending, including chip demand, will grow at an annual rate of 18%.
- Morgan Stanley analysts predict that AI-related semiconductors will grow at an 18% annual rate for a specific company, Taiwan Semiconductor (TSMC).
- Infosys notes that data center semiconductor sales are projected to grow at an 18% CAGR.
- MarketResearch.biz and the IEEE IRDS predict an 18% annual growth rate for AI accelerator chips.
- Citi also forecasts aggregate chip sales for potential AI workloads to grow at a CAGR of 18% through 2030.
AI-focused chips are expected to represent nearly 20% of global semiconductor demand in 2025, contributing approximately $67 billion in revenue [1]. The global AI chip market is projected to reach $40.79 billion in 2025 [2.] and continue expanding rapidly toward $165 billion by 2030.
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Types of AI Custom Chips:
Artificial intelligence is advancing at a speed that traditional computing hardware can no longer keep pace with. To meet the demands of massive AI models, lower latency, and higher computing efficiency, companies are increasingly turning to custom AI chips which are purpose-built processors optimized for neural networks, training, and inference workloads.
Those AI chips include Application Specific Integrated Circuits (ASICs) and Field- Programmable Gate Arrays (FPGAs) to Neural Processing Units (NPUs) and Google’s Tensor Processing Units (TPUs). They are optimized for core AI tasks like matrix multiplications and convolutions, delivering far higher performance-per-watt than CPUs or GPUs. This efficiency is key as AI workloads grow exponentially with the rise of Large Language Models (LLMs) and generative AI.
OpenAI – Broadcom Deal:
Perhaps the biggest custom AI chip design is being done by an OpenAI partnership with Broadcom in a multi-year, multi-billion dollar deal announced in October 2025. In this arrangement, OpenAI will design the hardware and Broadcom will develop custom chips to integrate AI model knowledge directly into the silicon for efficiency.
Here’s a summary of the partnership:
- OpenAI designs its own AI processors (GPUs) and systems, embedding its AI insights directly into the hardware. Broadcom develops and deploys these custom chips and the surrounding infrastructure, using its Ethernet networking solutions to scale the systems.
- Massive Scale: The agreement covers 10 gigawatts (GW) of AI compute, with deployments expected over four years, potentially extending to 2029.
- Cost Savings: This custom silicon strategy aims to significantly reduce costs compared to off-the-shelf Nvidia or AMD chips, potentially saving 30-40% on large-scale deployments.
- Strategic Goal: The collaboration allows OpenAI to build tailored hardware to meet the intense demands of developing frontier AI models and products, reducing reliance on other chip vendors.
AI Silicon Market Share of Key Players:
- Nvidia, with its extremely popular AI GPUs and CUDA software ecosystem., is expected to maintain its market leadership. It currently holds an estimated 86% share of the AI GPU market segment according to one source [2.]. Others put NVIDIA’s market AI chip market share between 80% and 92%.
- AMD holds a smaller, but growing, AI chip market share, with estimates placing its discrete GPU market share around 4% to 7% in early to mid-2025. AMD is projected to grow its AI chip division significantly, aiming for a double-digit share with products like the MI300X. In response to the extraordinary demand for advanced AI processors, AMD’s Chief Executive Officer, Dr. Lisa Su, presented a strategic initiative to the Board of Directors: to pivot the company’s core operational focus towards artificial intelligence. Ms. Su articulated the view that the “insatiable demand for compute” represented a sustained market trend. AMD’s strategic reorientation has yielded significant financial returns; AMD’s market capitalization has nearly quadrupled, surpassing $350 billion [1]. Furthermore, the company has successfully executed high-profile agreements, securing major contracts to provide cutting-edge silicon solutions to key industry players, including OpenAI and Oracle.
- Intel accounts for approximately 1% of the discrete GPU market share, but is focused on expanding its presence in the AI training accelerator market with its Gaudi 3 platform, where it aims for an 8.7% share by the end of 2025. The former microprocessor king has recently invested heavily in both its design and manufacturing businesses and is courting customers for its advanced data-center processors.
- Qualcomm, which is best known for designing chips for mobile devices and cars, announced in October that it would launch two new AI accelerator chips. The company said the new AI200 and AI250 are distinguished by their very high memory capabilities and energy efficiency.
Big Tech Custom AI chips vs Nvidia AI GPUs:
Big tech companies, including Google, Meta, Amazon, and Apple—are designing their own custom AI silicon to reduce costs, accelerate performance, and scale AI across industries. Yet nearly all rely on TSMC for manufacturing, thanks to its leadership in advanced chip fabrication technology [3.]
- Google recently announced Ironwood, its 7th-generation Tensor Processing Unit (TPU), a major AI chip for LLM training and inference, offering 4x the performance of its predecessor (Trillium) and massive scalability for demanding AI workloads like Gemini, challenging Nvidia’s dominance by efficiently powering complex AI at scale for Google Cloud and major partners like Meta. Ironwood is significantly faster, with claims of over 4x improvement in training and inference compared to the previous Trillium (6th gen) TPU. It allows for super-pods of up to 9,216 interconnected chips, enabling huge computational power for cutting-edge models. It’s optimized for high-volume, low-latency AI inference, handling complex thinking models and real-time chatbots efficiently.
- Meta is in advanced talks to purchase and rent large quantities of Google’s custom AI chips (TPUs), starting with cloud rentals in 2026 and moving to direct purchases for data centers in 2027, a significant move to diversify beyond Nvidia and challenge the AI hardware market. This multi-billion dollar deal could reshape AI infrastructure by giving Meta access to Google’s specialized silicon for workloads like AI model inference, signaling a major shift in big tech’s chip strategy, notes this TechRadar article.
- According to a Wall Street Journal report published on December 2, 2025, Amazon’s new Trainium3 custom AI chip presents a challenge to Nvidia’s market position by providing a more affordable option for AI development. Four times as fast as its previous generation of AI chips, Amazon said Trainium3 (produced by AWS’s Annapurna Labs custom-chip design business) can reduce the cost of training and operating AI models by up to 50% compared with systems that use equivalent graphics processing units, or GPUs. AWS acquired Israeli startup Annapurna Labs in 2015 and began designing chips to power AWS’s data-center servers, including network security chips, central processing units, and later its AI processor series, known as Inferentia and Trainium. “The main advantage at the end of the day is price performance,” said Ron Diamant, an AWS vice president and the chief architect of the Trainium chips. He added that his main goal is giving customers more options for different computing workloads. “I don’t see us trying to replace Nvidia,” Diamant said.
- Interestingly, many of the biggest buyers of Amazon’s chips are also Nvidia customers. Chief among them is Anthropic, which AWS said in late October is using more than one million Trainium2 chips to build and deploy its Claude AI model. Nvidia announced a month later that it was investing $10 billion in Anthropic as part of a massive deal to sell the AI firm computing power generated by its chips.
Image Credit: Emil Lendof/WSJ, iStock
Other AI Silicon Facts and Figures:
- Edge AI chips are forecast to reach $13.5 billion in 2025, driven by IoT and smartphone integration.
- AI accelerators based on ASIC designs are expected to grow by 34% year-over-year in 2025.
- Automotive AI chips are set to surpass $6.3 billion in 2025, thanks to advancements in autonomous driving.
- Google’s TPU v5p reached 30% faster matrix math throughput in benchmark tests.
- U.S.-based AI chip startups raised over $5.1 billion in venture capital in the first half of 2025 alone.
Conclusions:
Custom silicon is now essential for deploying AI in real-world applications such as automation, robotics, healthcare, finance, and mobility. As AI expands across every sector, these purpose-built chips are becoming the true backbone of modern computing—driving a hardware race that is just as important as advances in software. More and more AI firms are seeking to diversify their suppliers by buying chips and other hardware from companies other than Nvidia. Advantages like cost-effectiveness, specialization, lower power consumption and strategic independence that cloud providers gain from developing their own in-house AI silicon. By developing their own chips, hyperscalers can create a vertically integrated AI stack (hardware, software, and cloud services) optimized for their specific internal workloads and cloud platforms. This allows them to tailor performance precisely to their needs, potentially achieving better total cost of ownership (TCO) than general-purpose Nvidia GPUs
However, Nvidia is convinced it will retain a huge lead in selling AI silicon. In a post on X, Nvida wrote that it was “delighted by Google’s success with its TPUs,” before adding that Nvidia “is a generation ahead of the industry—it’s the only platform that runs every AI model and does it everywhere computing is done.” The company said its chips offer “greater performance, versatility, and fungibility” than more narrowly tailored custom chips made by Google and AWS.
The race is far from over, but we can expect to surely see more competition in the AI silicon arena.
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Links for Notes:
2. https://sqmagazine.co.uk/ai-chip-statistics/
3. https://www.ibm.com/think/news/custom-chips-ai-future
References:
https://www.wsj.com/tech/ai/amazons-custom-chips-pose-another-threat-to-nvidia-8aa19f5b
https://www.wsj.com/tech/ai/nvidia-ai-chips-competitors-amd-broadcom-google-amazon-6729c65a
AI infrastructure spending boom: a path towards AGI or speculative bubble?
OpenAI and Broadcom in $10B deal to make custom AI chips
Reuters & Bloomberg: OpenAI to design “inference AI” chip with Broadcom and TSMC
RAN silicon rethink – from purpose built products & ASICs to general purpose processors or GPUs for vRAN & AI RAN
Dell’Oro: Analysis of the Nokia-NVIDIA-partnership on AI RAN
Cisco CEO sees great potential in AI data center connectivity, silicon, optics, and optical systems
Expose: AI is more than a bubble; it’s a data center debt bomb
China gaining on U.S. in AI technology arms race- silicon, models and research
Dell’Oro: Optical Transport Systems market +15% year-over-year in 3Q2025 driven by Cloud Service Providers
Dell’Oro Group recently published its 3Q25 Optical Transport report, highlighting continued strength in the market as demand accelerates across customer segments and technology areas. Below is a summary of the key findings from this latest research.
The Optical Transport Systems market increased by 15% year-over-year (Y/Y) in 3Q2025, driven by robust demand across all major customer groups and technology segments. The most significant growth was seen in Cloud Service Providers (CSPs) which grew +58% Y/Y and the DWDM Long Haul segment which grew +24% Y/Y. Direct sales for data center interconnect (DCI) continued to be the driving application for optical transport equipment sales, growing 34% Y/Y. Non-DCI also performed well, rising 7% Y/Y, driven by increased spending by communication service providers (CSPs).
In the first nine months of 2025, two vendors—Ciena and Nokia—gained more than one percentage point of market share. Other vendors that gained some market share included 1Finity, Adtran, Cisco, and Smartoptics. Note that Nokia acquired Infinera -a fiber optic equipment company on February 28, 2025.
Image Source: Jimmy Yu, Dell’Oro Group
The Dell’Oro Group Optical Transport Quarterly Report offers complete, in-depth coverage of the market with tables covering manufacturers’ revenue, average selling prices, and unit shipments (by speed up to 1.6 Tbps). The report tracks DWDM long haul, WDM metro, multiservice multiplexers (SONET/SDH), data center interconnect (metro and long haul), disaggregated WDM systems, and IPoDWDM ZR/ZR+ Optics. To purchase this report, please contact us at [email protected].
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Backgrounder:
- Optical Transceivers: Convert electrical signals into optical signals for transmission over fibers, and vice versa, at the endpoints of a link.
- Wavelength Division Multiplexers (WDM/DWDM): Devices that combine multiple optical signals (each on a different wavelength) into a single fiber for transmission, and separate them at the receiving end, maximizing fiber capacity.
- Optical Add/Drop Multiplexers (OADMs): Allow specific wavelengths (channels) to be added or removed from a fiber link at intermediate points in the network without interrupting the other channels.
- Optical Cross-Connects (OXCs) / Optical Switches: Used to route optical signals from one incoming fiber to a different outgoing fiber in the optical domain, often used in core networks.
- Regenerators / Optical Amplifiers (EDFAs): Used to amplify or regenerate optical signals over long distances to maintain signal strength and quality.
- OTN Terminal Equipment / Muxponders & Transponders: These devices package client signals (like Ethernet, Fibre Channel, or even SONET/SDH signals) into the standard OTN frame format (ITU G.709) for efficient transport.
- SONET/SDH: These are legacy, connection-oriented, circuit-switched technologies originally designed for carrying voice traffic in North America (SONET) and globally (SDH). They operate at the physical layer (Layer 1) and use Time Division Multiplexing (TDM).
- Usage: They are still widely deployed in existing network infrastructure, especially where high reliability and stringent latency requirements for legacy TDM services are necessary.
- OTN: OTN (ITU-T G.709 standard) is the modern successor, designed to combine the management and protection capabilities of SONET/SDH with the bandwidth efficiency of WDM.
- Usage: OTN has largely replaced SONET/SDH in new core and metro networks due to its ability to transparently carry multiple types of traffic (Ethernet, IP, Fibre Channel, and SONET/SDH frames) over a single, high-capacity infrastructure. It offers enhanced performance monitoring, Forward Error Correction (FEC) for longer reach, and greater scalability.
- Huawei has consistently maintained a leading position in the global optical networking market.
- Ciena is a major leader, particularly in North America (holding nearly 50% share in the U.S. market) and among cloud providers, benefiting from strong demand for its WaveLogic 6e and 400ZR/ZR+ solutions.
- Nokia has significantly strengthened its position, becoming the second-largest optical networking vendor globally (with approximately 20% market share) following its acquisition of Infinera in February 2025. The combined company saw substantial growth in revenue from cloud customers.
- Cisco saw a 31% increase in revenue from cloud operators in Q2 2025, a key driver of market growth.
- ZTE and FiberHome are also among the top six, often noted for their competitive solutions in global and emerging markets.
- Excluding sales into China, the leading vendors are Ciena, Huawei, Nokia, Infinera (now part of Nokia), and Fujitsu, accounting for around 80% of that specific market segment.
References:
Optical Transport Market Surges 15% in 3Q25, According to Dell’Oro Group
Dell’Oro: Optical Transport market to hit $17B by 2027; Lumen Technologies 400G wavelength market
LightCounting: Q1 2024 Optical Network Equipment market split between telecoms (-) and hyperscalers (+)
Highlights of LightCounting’s December 2023 Quarterly Market Update on Optical Networking
Dell’Oro: Optical Transport Market Down 2% in 1st 9 Months of 2021
Dell’Oro: Optical Transport Equipment Market Stagnant in 1Q 2021; Jimmy Yu’s Take
Dell’ Oro: Huawei still top telecom equipment supplier; optical transport market +1% in 2020
New Street Research study: Cable broadband will continue its decline, but total broadband access subscribers will increase
A recent New Street Research broadband trends study suggests that U.S. cablecos (previously called MSOs) aren’t likely to increase the net number of broadband internet subscribers during this decade, but their broadband losses are expected to decrease. The financial market research firm doesn’t anticipate cable broadband subscriber growth to be positive for at least another four to five years. Under New Street’s “base case,” cable broadband net adds will remain negative each year until 2030. Cable broadband is facing fierce competition on the high end from fiber to the premises (e.g. AT&T, Frontier/Verizon) and on the lower end from 5G FWA (e.g. T-MobileUS, Verizon).
Cable “is the new copper,” New Street Research analysts David Barden and Vikash Harlalka wrote, implying declining subscribers for xDSL based broadband will also happen to cablecos. Obviously, cablecos won’t like that characterization given that their hybrid fiber/coax (HFC) networks are mostly comprised of fiber. However, declining subscriber trends is not a commentary about the cable industry’s underlying broadband access network technology.
“With industry growth remaining below pre-pandemic levels and FWA adds remaining strong, we don’t expect Cable to grow subscribers this decade. Cable needs industry growth to improve and FWA adds to slow down to return to growth,” New Street’s analysts write in their 140-page report (subscribers only).
New Street outlines potential scenarios for how cable’s share of the broadband market will look by 2030:
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Best case scenario – cable has 42% of the market as 84% of the market is divvied up between cable and fiber, while FWA gets 16%.
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Plausible scenario – cable retains 32% share of the broadband market, with 80% of it being shared with fiber, and FWA capturing 20%.
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Optimistic scenario – cable captures 50% of the broadband market, fueled by “superior marketing and cheaper mobile bundles,” compared to fiber (41%) and FWA (10%).
New Street expects cable’s “steady state terminal market share” to be just a bit higher than 40% across its footprint, down from 62% today.
The report also takes a look at how cable will fare in markets that overlap with fiber. New Street estimates that 75% of cable markets will have a fiber competitor in the years to come. When combining non-fiber and fiber markets, cable is expected to capture about 41% of the share in their footprints. That compares to fiber (34%), FWA (20%), DSL (2%) and satellite broadband (3%).
It only gets worse for cablecos, as their customer net promoter scores (NPS) [1.] are lower than their competitors (mostly telcos). Using data from Recon Analytics’ weekly survey of about 10,000 respondents, New Street’s study notes there’s a pronounced customer NPS gap for cable against its primary broadband rivals. Customer NPS scores from Comcast (2) and Charter (1) are just above water compared to Cox Communications (-1) and Optimum Communications (-8). Fiber providers are doing much better: AT&T Fiber (25), Verizon Fios (21), Frontier (17) and Lumen Fiber (1). FWA also holds a sizable customer NPS advantage: T-Mobile (31) and Verizon FWA (29).
Note 1. NPS is a customer loyalty metric that measures the likelihood of customers recommending a company to a friend or colleague, using a scale of \(0\)-\(10\). The score is calculated by subtracting the percentage of “detractors” (those who score \(0\)-\(6\)) from the percentage of “promoters” (those who score \(9\)-\(10\)), with “passives” (those who score \(7\)-\(8\)) not being factored into the final score. NPS is a single, easy-to-understand number that ranges from \(-100\) to \(+100\) and is used to gauge customer satisfaction and predict business growth. Customers are asked, “On a scale of \(0\)-\(10\), how likely are you to recommend [company] to a friend or colleague?”
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Considering all types of broadband access, New Street expects total net U.S. broadband net adds of 1.6 million, up from the 1.2 million from an earlier estimate. Fueled by fiber and FWA, net broadband subscriber adds are expected to continue above that level through 2030.
That growth will continue even as the market becomes increasingly saturated. New Street forecasts 139 million Internet households in 2030, up from 133 million at the end of 2025. Broadband penetration is expected to reach 93% by 2030, up from 87.7% at the end of 2025.
New Street expects U.S. network service providers to have 32 million to 36 million FWA subscribers in the coming years. However, the forecast expects a slight slowdown in FWA sub adds in 2026, coming in just below the range of 3.7 million to 3.8 million seen over the past three years. Next year, New Street expects FWA subscriber adds of 3.6 million (1.7 million for T-Mobile, 1 million for Verizon and 900,000 for AT&T). The analysts estimate that the carriers currently have enough capacity to support about 32 million FWA subs, estimating that carriers have already consumed about 55% of total capacity with new subs. That estimate does not include potential capacity coming from the upcoming auction of upper C-Band spectrum. That auction could provide capacity for another 4 million or so additional FWA subs, New Street said.
- Intense Competition: Cable operators are losing subscribers to FTTH, which offers faster speeds and higher reliability, and FWA services, which often appeal to customers seeking lower-priced or easily installed options.
- Market Saturation and Demographics: The broadband market is becoming increasingly saturated, and a slowdown in new household formation and people moving is curbing a key driver of new broadband connections.
- End of Government Subsidies: The expiration of government programs like the Affordable Connectivity Program (ACP) is impacting subscriber numbers, with major cable operators losing customers who relied on the subsidy.
- Network Upgrades: Cable companies are investing in network upgrades, such as DOCSIS 4.0, to improve speeds and performance, but it is not yet clear if these upgrades will significantly boost subscriber numbers.
Other Analyst Opinions:
- MoffettNathanson sees flattish cable broadband subscriber growth for the next couple of years, with a small gain in 2028. The firm projects subscriber losses in legacy markets will be eventually offset by gains from rural expansions and edge-out builds. “The conclusion for the two [Comcast and Charter] is about the same: even a near worst-case scenario yields roughly flat subscribership over the next five years or so,” Moffett wrote. “That’s a far cry from the doomsday scenarios we typically hear for the bear case.”
- In February 2025, Wolfe Research estimated that total industry net broadband additions for 2025 would be under 2 million, with cable providers bearing much of the slowdown.
- Grand View Research forecasts the global broadband services market (all connection types) to reach ~ US$ 875 billion by 2030, growing ~ 9.8% per year from 2025. In North America, broadband services revenue is expected to grow at ~ 8.3% CAGR from 2025 to 2030.
- Mordor Intelligence forecasts that the global market for hybrid-fiber coaxial (HFC — the backbone for many cable networks) will grow a 7.6% CAGR from $14.96 billion in 2025 to ~ $21.58 billion in 2030.
- An Ericsson analysis noted a projected decline of around 150 million DSL and cable connections globally between 2024 and 2030, with most growth coming from fiber, FWA, and satellite.
References:
https://www.lightreading.com/cable-technology/ouch-broadband-study-casts-cable-as-the-new-copper-
https://www.lightreading.com/cable-technology/cable-broadband-faces-a-flat-future-not-doomsday
https://telcomagazine.com/top10/top-10-global-fxxt-companies-in-telecoms
Tampnet to expand 5G offshore connectivity in the Gulf of Mexico using Nokia AirScale 5G radios
Tampnet, a global leader in offshore communications, is expanding its operations in the Gulf of Mexico and is now using Nokia AirScale 5G radios across its entire on-sea network of 120 active base stations, as well as extending coverage to 350-400 platforms, rigs, floating production storage and offloading (FPSO) units, wind farms and vessels. While Telenor Maritime operates a 4G/5G-ready offshore mobile service for the oil and gas industry in the Norwegian section of the North Sea, Tampnet has spread its operations across several parts of the world, including off the coast of the U.S.
Building on the 2025 deployment of the world’s first fully autonomous private 5G edge network on an offshore production platform on the Norwegian continental shelf (NCS), this partnership extends that innovation to U.S. offshore, setting new benchmarks for connectivity, safety and digital transformation across the global offshore energy sector.
Art by midJourney for Fierce Network
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Arnt Erling Skavdal, CTO of Mobile Technology, Tampnet: “With Nokia’s 5G technology, we are taking a significant step towards modernizing our offshore networks in the Gulf. This investment will enable us to meet the evolving connectivity and automation needs of offshore industries, enhance worker safety and unlock new digital applications that were not possible before.”
The Gulf of Mexico is a strategic region for Tampnet, where the company operates both private and public networks and manages critical subsea fiber that connects offshore assets to the mainland. Tampnet’s infrastructure forms the digital backbone of the region’s offshore activity, delivering reliable ultra-low latency, high-availability connectivity that supports safer, smarter and more sustainable operations from site to shore.
Nokia’s 5G AirScale Radio Access Network (RAN) equipment will enable offshore industries to implement advanced capabilities including real-time telemetry and monitoring, AI-driven predictive maintenance, and scalable industrial automation. Personnel in the Gulf region will benefit from high-performance private wireless connectivity, which will enhance operational safety and drive significant efficiency gains.
Jeff Pittman, Head of North America Enterprise, Mobile Networks, Nokia: “Our collaboration with Tampnet demonstrates how Nokia’s private wireless solutions are enabling digital transformation in some of the world’s most challenging environments. Together, we are setting new standards for offshore connectivity that will deliver long-term value to energy producers and their workforce.”
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- Real-time remote monitoring: Onshore control centers can monitor offshore equipment and facilities in real time using vast networks of IoT sensors and high-definition video surveillance, reducing the need for physical site visits.
- AI-driven predictive maintenance: IoT sensors on critical infrastructure like pipelines, pumps, and wind turbines continuously stream performance and environmental data (e.g., vibration, temperature, pressure) over private 5G networks. AI analytics use this data to predict potential failures before they occur, minimizing costly downtime and extending asset lifespan.
- Scalable industrial automation: 5G provides the reliable, low-latency connectivity necessary for automated systems, including autonomous guided vehicles (AGVs) in ports and robotic arms on platforms. This allows for complex, coordinated operations with minimal human intervention.
- Autonomous inspection with drones and robots: Drones and unmanned ground vehicles (UGVs) equipped with high-resolution cameras and sensors perform inspections of hazardous or hard-to-reach areas, such as flare stacks or wind turbine blades. 5G enables the real-time data transmission and remote control required for these operations, keeping personnel out of harm’s way.
- Augmented reality (AR) and virtual reality (VR) support: Field workers can use AR devices for guided maintenance and troubleshooting, receiving real-time instructions and collaboration from experts onshore. VR is also used for training and detailed visualization of digital twins.
- Enhanced safety and crew communication: 5G-enabled safety systems, such as connected worker wearables (e.g., smart helmets, gas detectors), track personnel and environmental conditions in real time, providing instant alerts in case of incidents or hazards. This also facilitates reliable crew communication across vast operational zones.
- Remote operation of equipment: With 5G’s ultra-low latency, operators can precisely control heavy machinery and underwater robots from remote locations, improving efficiency and safety.
- Digital twins: The massive amounts of data collected via 5G networks feed into digital twin models of offshore assets (e.g., entire wind farms or rigs), allowing operators to simulate scenarios, optimize performance, and manage assets with unprecedented accuracy.
About Nokia: Nokia is a global leader in connectivity for the AI era. With expertise across fixed, mobile, and transport networks, powered by the innovation of Nokia Bell Labs, we’re advancing connectivity to secure a brighter world.
About Tampnet: Tampnet provides first-class, high-capacity connectivity to the global energy sector, enabling digitalization, efficiency, and sustainability. By operating the world’s largest offshore network, Tampnet delivers reliable and scalable high-capacity, low-latency connectivity solutions that support safer, smarter and more sustainable operations from site to shore. Through continuous innovation and focus on reduction of carbon footprint, Tampnet revolutionises offshore operations, contributing to a more sustainable energy production landscape. The company operates offshore telecom infrastructure in the North Sea and the Gulf of Mexico (Gulf of America). More than offshore energy installations, as well as a large number of mobile rigs and vessels, receive high-speed data communication by Tampnet.
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References:
https://www.nokia.com/industries/oil-and-gas/
https://www.fierce-network.com/wireless/nokia-confirms-tampnet-5g-radio-deal
Nokia and Eolo deploy 5G SA mmWave “Cloud RAN” network
Nokia wins multi-billion dollar contract from Bharti Airtel for 5G equipment
Charter Communications selects Nokia AirScale to support 5G connectivity for Spectrum Mobile™ customers
Nokia in multi-year deal with Zain to provide 5G RAN equipment throughout Jordan
Telia’s mobile network with CBTC technology deployed in Oslo metro line
Telia is claiming a European first with the deployment of a digital signaling system on the Oslo metro that operates over the Nordic telecom operator’s commercial 4G/5G mobile network. Sporveien is the Oslo subway transport operator.
Developed by Siemens Mobility, the system uses communications-based train control (CBTC) technology to link trains, trackside equipment and central control systems. According to Telia, CBTC enables far more precise train-position tracking than legacy signaling platforms, allowing operators to safely reduce headways and run trains more closely together.
Morten Karlsen Sørby, acting Head of Telia Norway: “As far as we know, only the New York City Subway uses a mobile network as part of a signaling system. It places high demands on availability and service quality, and Telia is ready to deliver. We congratulate Sporveien on this new system, and we’re very proud of our innovative collaboration with both Sporveien and Siemens Mobility.”
Today’s launch is on the Oslo Metro’s line 4 between Brattlikollen and Bergkrystallen, with implementation across the entire subway scheduled for 2030. The current signaling system has been in place since the Metro opened in 1966.
Birte Sjule, CEO of Sporveien: “The subway can only operate with a well-functioning signaling system, so this project is extremely important for Oslo’s residents. By replacing technology that has passed its useful life, we’ll reap additional benefits such as more frequent departures and increased capacity in the years to come.”
The solution delivered to Sporveien is part of Telia’s Enterprise Mobile Network (EMN) portfolio, which offers advanced and customized connectivity services to support industrial digitalization. EMN can use either 4G or 5G technology, or a combination, depending on the specific needs of the business.
Private 5G is now being integrated into CBTC systems to provide higher capacity, lower latency, and improved performance, especially in urban and high-demand environments. Companies are actively rolling out and testing CBTC with 5G, making it a next-generation standard for some new and retrofitted systems.
References;
Ericsson and Telia said to provide lower 5G latency & power dissipation/longer battery life
Non-coherent Massive MIMO for High-Mobility Communications
Selected Applications/Use Cases by Industry for ITU-R International Mobile Telecommunications (IMT) – 3G, 4G & 5G
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.
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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.
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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
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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.
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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
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Highlights of ITU Global Connectivity Report 2025 and the Baku Action Plan
The ITU Global Connectivity Report 2025, released at the conclusion of the World Telecommunication Development Conference (WTDC-25) in Baku, Azerbaijan, delivers a comprehensive assessment of how global connectivity has evolved from a scarce asset in 1994 into a foundational layer of the digital economy and everyday life, with close to 6 billion users projected to be online by 2025. Its analytical framework is anchored in the policy objective of achieving universal and meaningful connectivity (UMC), structured across six interdependent dimensions: Quality, Availability, Affordability, Devices, Skills, and Security.
The report underscores the socio‑economic gains associated with large‑scale digital transformation, including enhanced productivity, innovation, and service delivery across sectors. At the same time, it emphasizes that progress is constrained by persistent digital divides along income, gender, age, and geographic lines, as well as by escalating exposure to online harms, misinformation, and non‑trivial environmental externalities from ICT infrastructure and usage.
It suggests the era of easy, organic network expansion is over. While 74% of the world is now online, the curve is flattening, and the remaining deficits are structural rather than merely about access.
With an estimated 2.2 billion people still offline, ITU Member States (194) agreed this week on the Baku Action Plan—a four-year roadmap to 2029 designed to close these persistent divides.
The report provides detailed analysis of structural barriers to universal and meaningful connectivity (UMC), notably high connectivity and device costs, gaps in digital skills, and constrained access to appropriate end‑user devices. It translates this analysis into evidence‑based policy guidance focused on regulatory coherence, targeted affordability interventions, and demand‑side enablers to ensure that connectivity translates into effective and inclusive digital usage.
From a network engineering and infrastructure perspective, the report highlights the critical role of resilient, high‑capacity backbones, including submarine cable systems and satellite constellations, as strategic layers of the global connectivity fabric. It stresses the need for coordinated investment, robust redundancy and security models, and integrated planning across terrestrial, subsea, and space‑based networks to support UMC objectives.
The report identifies high service and device costs, insufficient digital skills, and limited device availability as key barriers, and provides evidence‑based policy guidance on regulatory coherence, affordability, and demand‑side enablers. It emphasizes the importance of resilient infrastructure such as submarine cables and satellites, along with stronger national data ecosystems, to support inclusive connectivity strategies and informed digital policy‑making.
Finally, the report calls for strengthening national data ecosystems—covering data collection, governance, sharing, and analytics—as a prerequisite for effective digital inclusion strategies and evidence‑driven policy‑making. It positions mature data capabilities and coherent digital governance frameworks as key enablers for monitoring progress across the six UMC dimensions and for calibrating telecom and ICT policy in line with evolving market and technology dynamics.
References:
https://www.itu.int/itu-d/reports/statistics/global-connectivity-report-2025/
ITU’s Facts and Figures 2025 report: steady progress in Internet connectivity, but gaps in quality and affordability
ITU-R WP 5D reports on: IMT-2030 (“6G”) Minimum Technology Performance Requirements; Evaluation Criteria & Methodology
ITU-R report: Applications of IMT for specific societal, industrial and enterprise usages
https://www.itu.int/itu-d/reports/statistics/global-connectivity-report-2022/
ABI Research: 5G network slicing market to hit $67.52 billion in 2030 with Asia Pacific in the lead
ABI Research forecasts that the global 5G network slicing market will surge from $6.1 billion in 2025 to $67.52 billion by 2030, reflecting a compound annual growth rate (CAGR) of 70%. This represents a sharp upward revision from its 2023 outlook, which projected a market value of $19.5 billion by 2028.
Editor’s Note: 5G network slicing, as well as ALL 5G features and functions (including 5G Security) require a 5G Standalone (SA) core network, which up until recently had not been widely deployed. Also, there are no ITU standards or recommendations for either 5G SA or 5G network slicing or any other 5G features/functions. Those are all specified by 3GPP, for example TS 23.501 5G Systems Architecture which includes network slicing.
In a recent blog post, Dimitris Mavrakis stated that the ABI’s revised forecast is driven by intensified monetization efforts from major network operators, including China Mobile, Deutsche Telekom and T-Mobile US, together with the growing installed base of 5G Standalone (SA)-capable smartphones. At the same time, he highlighted that progress is moderated by the proven complexity of integrating 5G SA cores and cloud-native tooling into existing telco network and IT environments.
ABI indicates that so-called “carpeted” industry verticals—like retail, stadiums, and financial services do not deal with mission- and safety-critical applications. Therefore, slicing deployments are more simplistic and provide a quicker Return on Investment (ROI) than in more demanding industry sectors such as oil and gas. ABI says that industrial manufacturing will remain an important vertical for network slicing, albeit at a substantially slower growth rate than carpeted verticals.
The analysis further suggests that, for certain enterprises, network slicing delivered over public 5G infrastructure is becoming a more attractive option than 5G private networks, which introduces additional headwinds for the private networking market. While B2B use cases are expected to account for 64% of total network slicing market value by 2030, consumer applications are projected to be the single largest segment, contributing approximately $24.3 billion of revenue by the end of the period.
5G network slicing progress report with a look ahead to 2025
ABI Research: 5G Network Slicing Market Slows; T-Mobile says “it’s time to unleash Network Slicing”
Ericsson, Intel and Microsoft demo 5G network slicing on a Windows laptop in Sweden
Ericsson and Nokia demonstrate 5G Network Slicing on Google Pixel 6 Pro phones running Android 13 mobile OS
BT Group, Ericsson and Qualcomm demo network slicing on 5G SA core network in UK
Telstra achieves 340 Mbps uplink over 5G SA; Deploys dynamic network slicing from Ericsson
Samsung and KDDI complete SLA network slicing field trial on 5G SA network in Japan
Is 5G network slicing dead before arrival? Replaced by private 5G?
5G Network Slicing Tutorial + Ericsson releases 5G RAN slicing software
Network Slicing and 5G: Why it’s important, ITU-T SG 13 work, related IEEE ComSoc paper abstracts/overviews
Dell’Oro: RAN market stable, Mobile Core Network market +14% Y/Y with 72 5G SA core networks deployed
Téral Research: 5G SA core network deployments accelerate after a very slow start
Building and Operating a Cloud Native 5G SA Core Network
