The fact is that Nvidia is indeed betting big that telecom providers are ready to hand over the controls to their networks. The new autonomous AI agent platform of the company, presented at DTW Ignite 2026, will change the way telecom infrastructure is operated – right from human-led automation to AI that can autonomously make decisions 24/7.

As per a recent announcement from NVIDIA, telecom operators have already achieved outstanding returns when it comes to network management and customer care in the wake of generative AI deployments. But these gains have been restricted to task automation – systems that accelerate predefined steps, while humans manually connect insights and direct next steps. NVIDIA’s pitch? Automation is not the end line, but it is the launchpad to autonomy.

It does make a difference. Automating tasks speeds up repetitive work. They make logical choices, respond to evolving conditions, and execute complex operations without waiting for human approval. That difference could equate to billions in efficiency in operations for telecom operators handling millions of nodes in the network and customer interactions concurrently.

NVIDIA is right on time as companies roll out AI. Companies from different sectors are transitioning from AI copilots that support workers to AI agents that are autonomous. Microsoft, Google as well as OpenAI have all introduced agent frameworks in the recent months, but the one from NVIDIA is aimed at a particular vertical with bespoke infrastructure needs.

Autonomous AI is uniquely difficult for telecom networks. Customer service chatbots, along with code generation tools, are trained on data, but network management agents have to handle huge amounts of real-time data, anticipate failures of equipment before they occur, and organize failovers throughout geographically dispersed systems. And they need to be able to clarify their choices to human operators and regulators, a requirement for trust that has slowed the adoption of AI in mission-critical systems.

While it has not provided technical details about how its agents will deal with these challenges, its experience within AI infrastructure makes it a credible player. Its GPUs already enable inference and training for most massive language models, and its AI Enterprise software suite offers the foundations that telecom operators will need to set up agents safely. The question is if operators are prepared to trust AI with independent decision-making in live production networks.

Early generative AI use cases in telecom revolved around lower-risk applications such as summarizing calls to customer service, creating network configuration templates, and automating routine maintenance tickets. These use cases provided value without risking network outages or service disruption. Autonomous agents that control network traffic, allocate resources, and counter security threats on their own represent a far bigger leap in operational trust.

But the economic pressure to adopt is growing. As 5G rollouts accelerate and data traffic soars, telecom operators are facing rising infrastructure costs. Skilled network engineers are becoming harder to find, and their labor costs continue to rise. Tier-1 as well as tier-2 operations can be run by AI agents that are running 24/7, do not require instruction on new equipment, and can scale instantly across global deployments.

The announcement places the company as far more than a chip supplier but an enterprise AI platform provider battling it out with cloud giants. Amazon Web Services, Microsoft Azure as well as Google Cloud have their own AI agent frameworks, but NVIDIA has deep domain experience in computational performance and real-time inference, which is what telecom applications need.

But the larger implications are not just for telecom. If NVIDIA can demonstrate that autonomous agents are reliable in network activities, one of the most difficult enterprise environments, it could pave the way for equivalent deployments within energy grids, manufacturing plants, logistics networks, and financial systems. And all industries with intricate infrastructure and 24/7 operational requirements are suddenly potential customers.

What actually remains unclear is a business model. NVIDIA could as well license the new autonomous AI agent platform straight to telecom operators, integrate it with its AI Enterprise software, or implement it in infrastructure gear by partnering with network equipment vendors. The company’s historical bias towards new autonomous AI agent platform plays over verticals indicates a licensing approach that would enable operators to personalize agents for their own telecommunications networks.

The autonomous agent field is expanding rapidly. Anthropic recently released Claude agents for enterprise workflows, OpenAI is trialing agents in ChatGPT Enterprise, and Vertex AI from Google offers tools for building agents. But none have unveiled vertical-specific platforms for telecom operations, giving NVIDIA a competitive edge in a huge market.

The timing of the DTW Ignite also matters tactically. The event draws telecom executives who are making purchasing choices for next-generation infrastructure. NVIDIA showcases autonomous agents at industry flagship conferences, positioning itself early in budget cycles as well as technology roadmaps. In the coming months one can expect to announce partnerships with leading equipment vendors and begin deployments with tier-1 carriers.

NVIDIA’s push into autonomous agents is a calculated bet that enterprise AI is ready to transition from assisting to being autonomous. Telecom operators find the assurance of 24/7 self-managing networks an attractive proposition, provided the technology is reliable at scale. The company’s AI infrastructure strength presents a credible base, but moving that into production implementations throughout live telecom networks will call for demonstrating trustworthiness beyond research demonstrations. If NVIDIA is successful, it’s not just growing its telecom business; it will also establish the standard for autonomous agents in all sectors with critical infrastructure. This is a far bigger incentive than just chip sales.

It is well to be noted that the platform is designed to enable operators to provide AI services such as mobile data plans and charging usage based on tokens via current customer billing systems. Mavenir said operators will still have control when it comes to pricing, service-level contracts, and the models that fundamentally support the interactions with AI.

As per Mavenir, integrated AI platform for telecom operators is compatible with three operating models. They may employ it to deliver custom-branded AI services to subscribers, provide an AI infrastructure foundation for AI grid deployments, or offer managed AI features to enterprise customers on a token-based consumption basis.

Notably, the system is built on Red Hat AI and Kubernetes infrastructure via Red Hat OpenShift. The architecture is built to offer operators a versatile, sovereignty-centric platform that can run on-premises models as well as custom small language models when it comes to routine workloads, remarks Mavenir.

In addition to this, the platform also provides policy-controlled access to external frontier AI models for operations that require advanced logic or multi-modal abilities. Mavenir says operators can choose which model is taking which demand, who is paying for it, and how it is going to be billed.

Mavenir says token-based AI consumption goes on to act as familiar data-usage models, which implies that operators can make use of standard billing and service management systems so as to establish new revenue streams from AI. AI token plans that are monthly and enterprise quotas as well as SLA-backed AI service tiers could go on to open a new layer of monetization on top of connectivity, it said.

The combined AI platform integrates the AI software platform from Mavenir with enterprise Kubernetes along with the AI capabilities of Red Hat, running on verified hardware from third-party partners. The platform boasts intelligent model routing, token optimization, AI platform-as-a-service as well as MLOps capabilities, billing integration, token charging, closed-loop service assurance, and zero-trust identity controls as well as AI-specific security.

When it comes to enterprise customers, the platform allows operators to provide fee-based access to AI models, compute resources, and AI tools as value-added services. Operators can make use of it as the compute and AI fabric for network-embedded AI applications as well as third-party workloads to deploy an AI grid.

Operators can also use the platform to offer AI-powered products directly to subscribers, such as AI assistant plans charged by token consumption and AI-enhanced network services as well as operator-branded AI apps.

Mavenir says the platform is intended to promote new AI revenue streams, foreseeable AI economics, data privacy, and contract SLAs for operator-managed AI services, as well as enterprise-grade security. The company will present the platform at DTW Ignite 2026 on 23-25 June.

Let’s be honest – with the rise of AI services, telecom companies are looking for ways to get more than just connectivity revenue. Token-based billing would enable operators to bundle AI services in a conventional commercial model, leveraging prevailing client relationships, billing platforms, and service level agreements.

The announcement also marks an overall change in AI infrastructure. By integrating on-premises models with independent data controls and limited access to frontier models, operators can become AI service providers for consumers and enterprises as well as network-embedded applications and not just connectivity providers.

Introducing Ericsson AI in RAN

• AI models for telcos designed to run in real time inside the radio access network – RAN
• High-quality data for persistent learning software at scale.
• Agentic AI support to help with advanced RAN automation as well as network operations

According to Head of Networks Strategy & Product Management at Ericsson, Mårten Lerner, “Ericsson is redefining what’s possible in mobile networks by bringing powerful AI capabilities to service providers. With AI in RAN software, we are taking a major step toward AI-native networks, alongside the AI-ready radios we unveiled in February.”

The telco-grade AI models from Ericsson are optimized for ultra-low latency estimation in the microsecond range, with high robustness and dependability in varied and dynamic RAN environments. These models combine deep domain knowledge with training in terms of high-quality data, setting new standards as far as performance and efficiency are concerned.

Lerner adds that “service providers need networks that are high-performing, secure, and efficient in the AI era. With AI in RAN, Ericsson is bringing AI into networks to elevate 5G performance and efficiency through energy-efficient AI inference at scale.”

Have Been Proven in Commercial network deployments

Ericsson AI in RAN works along with Ericsson 5G Advanced on both purpose-built as well as cloud RAN platforms so as to unlock new AI-powered services. It represents the realization of the AI from the company for networks’ vision, using AI to improve the performance and productivity of networks. The aim for AI in RAN is to employ the right AI model in the correct section of the radio network, with Ericsson Silicon to drive energy-efficient AI inference within radios, and the most recent versions of RAN Compute and the portability of cloud RAN software mean AI capabilities can be implemented across partner platforms.

It is well to be noted that the first AI in RAN features will be available in Q2 2026, with additional enhancements coming later in 2026 itself. Software features involve AI-powered macro positioning, an AI-native scheduler for link adaptation, AI-managed beamforming, performance management event schema files, AI-powered multi-layer coordination, and augmented observability for AI in RAN.

AI in RAN from Ericsson is indeed proven in over 15 deployments and trials throughout the globe, offering up to 20% higher downlink speed and up to 10% better spectral performance. It also enables as much as 2x more high-traffic users, 90-95% accuracy of predictions of coverage, and almost 5x greater accuracy of user positioning.

As per Senior Vice President & CNO, SoftBank Corp., Teruyuki Oya, “Ericsson’s AI in RAN software marks an important step in bringing AI deeper into the radio access network. By enabling real-time optimization of radio performance, spectrum efficiency and user experience, it helps us turn AI innovation into practical value on live networks. We also see strong potential in how this foundation can support emerging AI-driven services, including physical AI scenarios that depend on low-latency, highly reliable connectivity and intelligent coordination between network and compute resources.”

Remarks Senior Vice President, Network Technology & Operations for Bell, Bruce Dean, “At Bell, we’re continuously evolving our network to meet growing demand for high-performance, AI-driven services. Integrating AI directly into the RAN is an important step in making networks more intelligent and efficient. Working with partners like Ericsson, we’re bringing these capabilities into our network to enhance performance, improve energy efficiency, and deliver a better experience for our customers.”

According to Head of Network Technology Office, SK Telecom, Yu Takki, “Through our collaboration with Ericsson, SK Telecom is advancing AI-RAN to enhance network performance and energy efficiency while supporting more intelligent and automated operations. By combining research, real-world validation, and software innovation, we aim to strengthen our leadership in AI-powered network evolution and help lay the foundation for AI-native 6G.”

The Chief Technology Officer at Rogers, Mark Kennedy, opines that “As Canada’s best 5G+ network, we’re proud to work with Ericsson and bring the latest 5G technology to Canadians. AI in RAN will help optimize network performance for customers in real-time and reduce energy consumption.”

Principal Analyst at Mobile Experts, Joe Madden, says that  “This could be the best ROI for mobile operators in years. With a software upgrade, operators can squeeze more capacity, better observability, and more accurate location-based services out of the 5G network they bought years ago.”

Interestingly, Ericsson has embedded AI functionality throughout its products since 4G while also adding AI-ready acceleration in RAN Compute in 2021. In February 2026, the company launched neural network accelerators in its massive MIMO radios, boosting AI inference power by 10x.

The move is part of an attempt to revitalize the traditional carrier as digitization becomes a national priority.

Charles Borome Razafimahatratra, the new CEO of GETESA, announced a rapid and short-term plan whereby network modernization is an important aspect.

The plan was recently presented to the Vice President of Equatorial Guinea, Teodoro Nguema Obiang Mangue.

A Tech Refresh

With an objective by Equatorial Guinea to bolster its digital infrastructure, the initial phase of the strategy will last 12 months. This involves optimizing the national telecommunications network, broadening mobile as well as internet coverage, and, in general, digitally transforming the business by purchasing modern equipment.

The program also looks forward to reactivating the country’s fibre optic network, which at present has been utilized only by SEGESA, the national electricity company, so as to link its power substations.

Apparently, other important efforts include the introduction of 5G services and the establishment of public Wi-Fi networks throughout the cities of Bata, Malabo, and Oyala and also in rural and urban communities throughout the country.

The strategy also includes regular improvements to the energy as well as technical infrastructure of the company. The other significant aspect is the full digitalization of operations from GETESA with a paperless management system with a view to lowering logistics expenses. The company also plans to introduce a financial platform referred to as Getesa Money, which will offer electronic payment services.

The roadmap also includes restoration of international roaming as well as launching of eSIM technology.

Connectivity problems continue

The modernization effort comes amid significant obstacles for telecommunications network of Equatorial Guinea. Cyberteq, a consulting firm, went ahead and did an audit, the inferences of which were presented in April 2026. It identified quite prominent shortcomings when it came to network speed, equipment, and capacity, as well as technical planning.

The report also cited aging infrastructure along with slow data transmission speeds in addition to dropped calls due to congestion on the network.

Cyberteq presented an itinerary to address these shortcomings by upgrading technology, boosting network capacity, and implementing an investment strategy so as to improve service quality as well as expand coverage, in accordance with the digital transformation goals of the country.

Also in April 2026, Mason, the consulting firm, recommended that Equatorial Guinea connect to the Medusa submarine cable, which would serve as the second international undersea cable of the country. The project will have a price tag of anywhere between €20 million and €60 million, which is equivalent to $23.3 million to $70 million, and aims to minimize internet downtime and improve network reliability and service quality. The infrastructure is anticipated to be fully operational between 2029 and 2030.

A Basis for Digital Transformation

Once repaired and fully operational, the GETESA network could serve as the foundation of the digital transformation strategy of Equatorial Guinea. Better facilities and service quality could speed up the digitalization of the national economy, with connectivity being an essential tool for both the private and public sectors.

When it comes to households, improved connectivity would enhance accessibility to important digital services such as communications, online learning, mobile financial services, and entertainment platforms. Better digital infrastructure would help businesses become more competitive, grow the scope for e-commerce, boost the uptake of cloud-based services, and allow more sophisticated digital management tools to be used.

By the end of 2025, Equatorial Guinea had 885,000 mobile subscribers, with a mobile penetration rate of 45.4%, as reported by DataReportal. The country also had 1.18 million Internet users, or 60.4% of the overall population.

SoftBank Group announced recently that it intends to make investments of as much as €75bn to setup 5GW AI data centers in France.

As part of phase one of the project, €45 billion will create 3.1 GW of AI data centre capability at an array of locations throughout northern France, which will include Dunkirk, Bosquel as well as Bouchain.

These new locations will be operational starting in 2031, with other places to be disclosed at a later time.

It is well to be noted that SoftBank Group will partner with EDF, the French national energy company, and digital automation specialist company Schneider Electric all through the project.

According to Masayoshi Son, the CEO of SoftBank, “SoftBank is proud to make this major commitment to France. “With its industrial capabilities, talent base, and national ambition, France is uniquely positioned to become a leading AI infrastructure hub in Europe.”

The French government welcomed the decision, additionally emphasizing the favorable conditions for setting up 5GW AI data centers in France.

The Minister of Economy, Finance & Industrial, Energy & Digital Sovereignty, Roland Lescure, said that “SoftBank’s decision to invest massively in AI datacenters in France – a first for the group in Europe – is testament to President Emmanuel Macron’s ambition to position France as a leading destination all along the AI value chain. It reflects our country’s substantial assets: fast access to the most reliable electrical grid in Europe, a strong digital and industrial ecosystem with a skilled workforce, and a government that works in unison with local authorities and stakeholders to fast-track procedures for strategic projects.”

France has quickly grown into the European frontrunner when it comes to AI data centres, with large tech and telco consortium AION announcing plans to develop an AI gigafactory in the nation as recently as May 2026.

For SoftBank, however, this declaration serves as an extension to its Stargate Project, which promises to develop $500 billion worth of AI infrastructure in collaboration with OpenAI across the next four years.

SoftBank continues to grow its AI capacity and go further into the AI value chain. In May 2026, the company said it planned to develop its own batteries so as to power its very own artificial intelligence data centres – AI data centres and proposed that these batteries may ultimately be sold to other companies.

SK hynix’s announcement is part of a trend of Omniverse-based twin fabs. SK hynix and SKT disclosed the work first at the APEC summit on October 30, 2025, with Samsung announcing its own Omniverse fab digital twins one day later, inside a 50,000-GPU AI Megafactory.

The world’s largest devoted semiconductor foundry, TSMC, unveiled its own version of an Omniverse fab environment, FabTwin, for assessing process-tool configurations.

The fabs from SK hynix in NVIDIA omniverse twin announcements adds to a list of companies that NVIDIA has been courting for months. NVIDIA announced Foxconn, Belden, Caterpillar, Lucid Motors, Toyota, TSMC as well as Wistron are building Omniverse factory digital twins at its GTC Washington, D.C., event on October 28, 2025.

SKT says it will implement Agentic Digital Twin Modeling based on the NVIDIA Agent Toolkit so as to automate the data transformation work of transforming equipment and spatial data into a functional virtual environment.

The fab-twin push is based on the same AI demand which is driving the core business of NVIDIA. SK hynix is a key supplier of the high-bandwidth memory that forms part of the AI accelerators that come from NVIDIA. The increase of HBM orders has driven memory makers to increase capacity at a rate where layout and process errors are costly. SK hynix said its quarterly net profit soared fivefold on booming demand for the memory in first-quarter earnings reported in April 2026, the WSJ reported.

The cooperation on connected edge AI products was highlighted at an event in Vienna, at the Embassy of the Republic of Latvia, wherein the representatives of LMT IoT, the Investment and Development Agency of Latvia, Infineon, as well as the members of the Latvian and European startup ecosystem gathered.

The new partnership between these two European tech companies relies on the fusion of edge AI technologies from Infineon, which include Deepcraft™ software solutions, with the IoT Shortcut connectivity platform from LMT IoT. The objective is to provide developers with a more direct route right from working AI models to deployable as well as connected products within the field.

Developers can make use of Deepcraft™ so as to turn sensor data into optimised Edge AI models for microcontrollers, whereas IoT Shortcut works to ease cellular IoT deployment with solutions to device onboarding, connectivity, data transmission, remote management as well as field operation necessities.

Combining these technologies can empower developers to create connected battery-powered products which process data locally and send only the most relevant events or information to the cloud.

According to the Head of LMT IoT, Reinis Skorovs, “The next wave of IoT products will not simply collect and transmit more data – they will understand what happens and act intelligently at the edge. That creates enormous potential across industries, but only if teams can move quickly and scale easily. Our cooperation with Infineon enables exactly that – giving companies a faster, simpler path from edge AI prototypes to connected products deployed in the real world.”

It is worth noting that this collaboration represents a development for companies creating products within industrial surveillance, maintenance prediction, ecological sensing, smart agriculture, asset monitoring, smart building systems and various other use cases where edge processing along with low-power cellular connectivity may minimise the level of complexity, enhance battery performance and facilitate real-world deployment.

For instance, a connected industrial device could leverage edge AI to locally detect anomalies only to send data when an anomaly is identified. Environmental or agricultural sensors may process the field signals received on the device and send out only relevant occurrences. For marine, logistics or asset tracking applications, connected devices may combine local intelligence with cellular connectivity in order to enable long-duration operations in remote locations.

According to Strategic Partner Manager at Infineon Austria, Andreas Mühlberger, “At Infineon, we believe that the power of our edge AI microcontrollers is only fully realized when paired with seamless, reliable connectivity. This partnership directly addresses the critical ‘last mile’ of product development: ensuring that the intelligent decisions made by our chips can instantly and efficiently reach the cloud. By integrating our Deepcraft™ software with LMT IoT’s proven cellular platform, we are giving developers a turnkey solution that combines our semiconductor expertise with their connectivity mastery by removing the technical friction.”

The partnership has already started with the joint mentorship program for teams building connected products which integrate edge AI along with low-power cellular connectivity. The program will provide startups as well as product companies with access to hardware, structured technical sessions, LMT IoT engineering expertise and support in progressing from concept or prototype to a functioning connected pilot. Notably, the current intake remains open until 31 July 2026.

It is worth noting that the initiative and partnership have also been acknowledged as an important move in Latvia-Austria technology cooperation and a pragmatic contribution to the startup as well as innovation landscape of Europe.

Says Head of the Representative Office in Austria, Investment and Development Agency of Latvia, Inga Ulmane,“This cooperation strengthens Lavia-Austria collaboration in high-value technology and serves as a strong example of how Latvia’s technology ecosystem helps power global innovation. By creating opportunities for startups, engineers, and industry partners to solve real-world challenges, LMT IoT and Infineon are laying the foundation for tomorrow’s connected products and services.”

The event at the Embassy of the Republic of Latvia featured presentations by LMT IoT and Infineon, a presentation pertaining to the joint cooperation and mentorship opportunity and participation of Latvian startups, investors, ecosystem stakeholders as well as sector partners.

The deal was signed via the Connectivity Division of Keppel and secures a standard capacity on the subsea cable system connecting Singapore to the west coast of the United States.

It is well to be noted that Bifrost is the first-ever subsea cable system linking Singapore directly to the U.S. through Indonesia, across the Java Sea as well as the Celebes Sea. The system lands in Singapore and Guam as well as Grover Beach, California, with branch facilities providing a standard connection to Jakarta and Manado, Indonesia, and Davao, Philippines, along with Winema, Oregon.

The cable will be over 20,000 km long and will have the ability to accommodate AI workloads and cloud-native platforms. Bifrost offers round-trip latency from Singapore to the U.S. of less than 165 milliseconds, up to 10 milliseconds quicker than current systems, Keppel says.

The system also brings over 240 Tbps of trans-Pacific capacity, addressing growing demand in terms of network robustness and backups across international digital paths.

The CEO of Connectivity, at Keppel, Manjot Singh Mann, said that “Finalising this IRU agreement with Telstra International reflects the growing traction of Bifrost amidst growing demand for high-quality digital connectivity infrastructure globally, as customers seek greater network resilience and alternative routes to support rising data traffic.”

He went on to add that Bifrost has functioned reliably as well as with utmost seamlessness ever since commencing commercial traffic in December 2025.

According to the CEO of Telstra International, Roary Stasko, “The Singapore-U.S. route is one of the world’s most important digital corridors, connecting fast-growing Asian markets to global cloud and content hubs. By securing a dedicated fiber pair on Bifrost, we’re giving customers more capacity and a truly diverse path, backed by an end‑to‑end service with Telstra International operating and monitoring the network.”

Notably, Keppel’s investment in the Bifrost fibre pairs is carried out in a 40-60 joint venture involving its private fund and co-investors. The company will also handle and upkeep five fibre pairs of the venture for the next 25 years.

Keppel said three of the fibre pairs were already committed to customers, with negotiations for the other two continuing, and agreements are expected to be concluded in the first half of 2026.

The agency said it was funding a feasibility analysis that would pave the way for the installation of about 1,500 mobile communications base stations built in the United States throughout Nigeria, Ghana, and Benin as well as Côte d’Ivoire, focusing on millions of people in deprived and off-grid communities.

The project will use wireless technology developed by US-based Vanu Inc., which builds software-based radio systems for tough and low-income settings.

The move of promoting wireless infrastructure throughout West Africa underscores Washington’s deepening engagement in Africa’s digital infrastructure sector as geopolitical rivalry with China intensifies, with Chinese firms having long led telecom expansion initiatives all over the continent.

Says Thomas Hardy, the Deputy Director of the US Trade and Development Agency, the effort will provide reliable and cost-effective connectivity to the internet and create possibilities for American companies in developing markets.

He adds that “USTDA is bringing private sector solutions to unlock widespread, affordable, trusted internet access in off-grid communities across West Africa. By helping American companies compete in these critical markets, we are offering an alternative to insecure infrastructure while creating export opportunities that make America more prosperous.”

For Vanu Côte d’Ivoire, the study will look into continuing telecommunications infrastructure, market dynamics, options for financing and regulatory frameworks in the four West African countries.

Apparently, it is Vernonburg Group LLC, which is Georgia-based, that has been chosen to offer technical expertise to evaluate and promote financing mobilization procedures for the planned rollout.

The project might significantly enhance connectivity in rural areas where millions still rely on inadequate 2G and 3G services or are totally disconnected from digital networks, industry experts say.

The planned deployment is additionally anticipated to create greater possibilities for American digital infrastructure service providers, such as suppliers of wireless systems and network management platforms as well as broadband support technologies.

According to the Chief Executive Officer of Vanu Inc., Andrew Beard, Vanu Inc.’s technology was purpose-built to provide broadband access in financially challenging terrain.

The initiative, he said, would show that sustainable telecom services could be provided cost-effectively in remote areas which have been ignored by established operators.

The project could assist speed the implementation of secure digital infrastructure worldwide and promote U.S. exports and investment opportunities, said Beard.

The decision comes as African governments face mounting pressure from Western nations to broaden critical infrastructure cooperation and lessen reliance on Chinese technology vendors in response to growing global concerns concerning cybersecurity and digital sovereignty as well as strategic control of communications networks.

The U.S. Trade and Development Agency stated the initiative supports its wider mission of encouraging the creation of critical infrastructure in emerging markets while also encouraging the export of trusted American tech.

The telecom industry is all set to spend $6.2 billion on agentic AI by 2030. Agentic AI systems that can rationalise and decide independently will be a major enabler of the cognitive broadband era, changing networks from basic connectivity to autonomous optimisation and AI-powered infrastructures.

According to the president of fixed networks with Nokia, Sandy Motley, AI makes your end-users less likely to churn, your engineering and helpdesk teams more productive, and your field teams connect more homes more quickly. Nokia’s Agentic AI puts 600+ million lines’ worth of broadband experience at the fingertips of every field technician, helpdesk agent, and network engineer and solves problems before the customer is even aware. We are fundamentally changing how home and broadband networks are deployed and run.

As part of new agentic AI in homes and broadband networks, Nokia employs AI agents as well as natural language interactions in its Altiplano and Corteca as well as Broadband Easy platforms in order to help telecom providers modernise their processes and cut costs. Operators can actively fix problems, optimise operations with no added headcount and identify network-related issues by means of automated root-cause assessment. The AI agents will provide immediate, tangible advantages for operators, such as raising initial contact helpdesk resolution rates over 50%, qualifying network occurrences in less than 5 minutes, and reducing return trips to construction sites and connected homes by 50%.

The new agentic AI in homes and broadband networks is based on open and safe conduct that combines AI agents, live data and external services, with guarantees surrounding regulation, the privacy of data and vendor liberty. Operators have complete control and may utilise an LLM suitable for their particular use case, deploy their own interfaces, or connect sources of data when they deploy AI across their business.

Says Grant Lenahan, Partner and Principal Analyst with Appledore Research, “AI only works with quality data and when data is AI-ready. Our recent market outlook on AI in network automation underscored that the industry is rapidly moving to build infrastructure capable of enabling powerful, successful AI. Vendors like Nokia that combine deep domain expertise with real-world scale are best positioned to deliver reliable outcomes. Nokia’s approach reflects many of the right architectural principles, including autonomous control loops, structured data models, and open APIs, which are critical to making automation easy and AI responses accurate.”

Nokia’s new AI capabilities go ahead and cover the entire broadband network lifecycle. They improve end-user experience and enhance productivity for customer care, network engineering & operations as well as field force teams –

• A chat-based AI assistant offers technicians and assistance teams immediate access to product knowledge, speeding up training and routine troubleshooting.
• AI-powered text, voice, and image guidance assist field technicians throughout surveys and installations, and computer vision technology assists in verifying the standard of work done and creating a live digital twin of the FTTH network.
• Automated diagnostics to detect the degradation and avoid the outages, providing the frontline support teams higher levels of operational precision and depth of analysis.
• An intelligent troubleshooting agent enhances the root cause analysis and accelerates remediation efforts throughout home and access networks, employing sophisticated reasoning in order to identify errors faster, lower ticket volumes and boost first call resolution rates.