The collaboration was unveiled at NVIDIA’s AI Summit in San Jose, where Zayo confirmed it would leverage NVIDIA’s networking technologies alongside its own extensive fibre footprint to build out dedicated AI transport corridors. The effort responds to a rapidly growing need for network pathways capable of handling the enormous data flows generated by AI training and inference workloads.

Why New Fibre Corridors Are Essential for AI Infrastructure

The rise of large-scale AI factories has created unprecedented demand for network capacity between compute facilities. Traditional internet and enterprise traffic patterns are being reshaped by AI workloads, which require ultra-low-latency, high-throughput connections between clusters of graphics processing units spread across multiple sites. This AI network expansion addresses a bottleneck that threatens to constrain the buildout of AI infrastructure if connectivity does not keep pace with compute deployment.

Zayo operates one of the largest independently owned fibre networks in North America, spanning more than 141,000 route miles. The company said it is now directing significant capital toward expanding capacity on routes that serve the highest concentrations of AI data centres. These corridors connect key markets where hyperscale operators, cloud providers, and AI developers are clustering their facilities.

Dan Caruso, chief executive of Zayo, said the partnership with NVIDIA reflects the reality that networking is becoming as critical as compute in the AI supply chain. He noted that Zayo’s fibre assets position the company to deliver the physical infrastructure layer that AI factories depend upon, and that the collaboration will accelerate the pace at which new capacity reaches the market.

Technical Details of the Fibre Expansion

Under the initiative, Zayo plans to deploy additional dark fibre pairs and lit services across high-demand AI corridors. The company will integrate NVIDIA’s networking technology stack to optimise data transport between AI facilities. This includes support for back-end AI cluster networking, where massive volumes of data must move between GPUs during model training.

The AI network expansion also encompasses upgrades to existing fibre routes, increasing the density of available fibre strands on pathways that connect established data centre campuses. Zayo confirmed that the buildout would span multiple phases, with initial deployments targeting corridors in the western and central United States where AI facility construction is most concentrated.

Kevin Deierling, senior vice president at NVIDIA, said that scaling AI infrastructure requires a network fabric that extends beyond the walls of individual data centres. He described the collaboration with Zayo as an important step in ensuring that connectivity keeps pace with the rapid expansion of AI compute capacity across the continent.

The initiative also aligns with broader industry trends. Demand for fibre connectivity between data centres has accelerated sharply as enterprises and hyperscalers invest heavily in AI capabilities. Network operators across North America are racing to secure and light new fibre routes, making AI network expansion one of the most active segments of telecommunications infrastructure investment.

Next Steps in the Rollout

Zayo said the first phase of new fibre deployments under the collaboration is expected to commence in the second half of 2025, with additional corridors to follow through 2026. The company indicated it would announce specific route details and capacity milestones as construction progresses.

The partnership positions both companies to address what industry observers regard as a critical constraint on AI growth. As compute power continues to scale inside AI factories, the connecting network must evolve in parallel. This AI network expansion effort represents a direct response to that challenge, with Zayo committing substantial fibre resources and NVIDIA contributing its networking expertise to ensure the infrastructure is fit for purpose.

Further updates on corridor-level deployments and technical specifications are expected in the coming quarters as Zayo advances its buildout programme alongside NVIDIA.

The announcement, made on 6 August, positions Ooredoo alongside partners Indosat Ooredoo Hutchison, Nokia and NVIDIA in building out the AI computing platform. Zankore is designed to provide AI computing capacity for cloud and enterprise customers, with ambitions to develop up to 1 gigawatt of NVIDIA DSX AI Factory capacity over time.

Ooredoo said the initial AI infrastructure investment is expected to generate around $600 million in cumulative earnings before interest, tax, depreciation and amortisation over the first five years, based on current estimates.

Platform Capacity and Technology Deployment

The first phase of the Zankore platform is expected to deliver approximately 200MW of AI computing capacity during the first half of 2027. This initial rollout will utilise NVIDIA GB300 NVL72 systems, according to the company.

Zankore will also deploy NVIDIA’s DSX MaxLPS technology, which Ooredoo said is designed to boost AI computing capacity by optimising power use across graphics processing units. The deployment of these systems underlines the scale of the AI infrastructure investment being directed toward the platform.

Indonesia was selected as the location for the project due to its growing digital economy and rising demand for AI computing infrastructure. Ooredoo indicated the platform is expected to expand across Southeast Asia over time, broadening the geographic reach of this AI infrastructure investment.

Strategic Rationale and Digital Infrastructure Expansion

Group CEO Aziz Aluthman Fakhroo said the investment forms part of Ooredoo’s broader strategy to expand its digital infrastructure business and increase its exposure to AI-related assets.

“Over recent years, we have systematically built one of the MENA region’s leading digital infrastructure portfolios. With Zankore, we are taking the next logical step by adding AI compute to that portfolio, extending our approach into the high-growth Southeast Asian market – one of today’s most dynamic AI infrastructure opportunities,” he said.

“We believe AI will define the next decade of value creation in emerging markets. Our role is to invest alongside the right partners, in scalable platforms that create long-term value for our shareholders while supporting the digital ambitions of the markets we serve,” he added.

Ooredoo’s existing digital infrastructure portfolio spans connectivity, international fibre and subsea cable networks, and AI-ready data centres. The addition of Zankore introduces AI compute as a dedicated infrastructure layer, creating what the company described as an integrated digital infrastructure platform covering networks, data centres and AI computing capacity.

The AI infrastructure investment effectively extends Ooredoo’s portfolio beyond its traditional connectivity and data centre operations into the high-demand AI computing segment, a market that continues to attract substantial capital across emerging economies.

FTI Capital Advisors served as financial adviser to Ooredoo on the transaction.

Looking ahead, the first major milestone will be the delivery of the initial 200MW phase of AI computing capacity in the first half of 2027, with further expansion across the Southeast Asia AI market anticipated in subsequent phases.

Unlike conventional data centres that primarily support cloud computing and enterprise applications, AI Data Centres are designed to process enormous volumes of data generated by artificial intelligence, machine learning, and high-performance computing workloads. These facilities require significantly greater computing power, storage capacity, and network performance, placing new demands on telecommunications infrastructure. As a result, telecom operators and infrastructure providers are investing in network modernization to ensure that data can move efficiently between users, cloud environments, and distributed computing resources.

The growing importance of AI Data Centres extends beyond computing capacity alone. High-bandwidth fibre networks, optical transport systems, edge computing infrastructure, and data centre interconnect technologies are becoming essential for supporting AI-driven applications that require real-time processing and seamless connectivity. This convergence is reshaping how telecommunications networks are planned, deployed, and managed to meet the evolving requirements of an increasingly AI-powered economy.

As demand for intelligent digital services continues to accelerate, AI Data Centres are becoming strategic assets that influence network architecture, infrastructure investment, and long-term capacity planning across the global telecommunications industry.

AI Data Centres Are Driving a New Era of Network Demand

Traditional telecommunications networks were primarily designed to support voice services, internet access, and enterprise communications. While these services continue to grow, the rapid expansion of AI Data Centres is creating a different category of network demand characterized by extremely high bandwidth, ultra-low latency, and continuous data movement between distributed computing environments.

Artificial intelligence applications generate and process significantly larger datasets than conventional enterprise workloads. Training advanced AI models, running inference engines, and supporting generative AI services require continuous communication between computing clusters, cloud platforms, storage systems, and end users. As AI Data Centres expand globally, telecommunications infrastructure must evolve to accommodate these increasingly demanding traffic patterns.

This shift is changing how network capacity is planned. Rather than focusing solely on consumer broadband growth, operators are strengthening backbone infrastructure capable of transporting massive volumes of data between interconnected data centres while maintaining consistent performance. High-capacity connectivity is becoming a strategic requirement for supporting AI-driven digital ecosystems rather than simply expanding network throughput.

High-Capacity Networks Are Becoming Essential Infrastructure

The expansion of AI Data Centres is accelerating investment in high-capacity telecommunications networks capable of supporting increasingly complex digital workloads. Fibre-optic infrastructure remains the foundation of this transformation, providing the bandwidth necessary to transport massive amounts of information between computing facilities, enterprise environments, and cloud platforms with minimal latency.

Optical networking technologies are becoming increasingly important as traffic generated by AI Data Centres continues to grow. Higher-capacity optical transport systems enable telecommunications providers to support greater data volumes while improving efficiency across long-distance and metropolitan networks. These technologies help ensure that AI applications can access distributed computing resources without compromising performance or reliability.

The demand for network scalability is also influencing long-term infrastructure planning. Instead of expanding capacity only after congestion occurs, operators are increasingly designing networks capable of supporting future AI workloads, recognizing that artificial intelligence will continue driving sustained growth in digital traffic across enterprise and consumer services alike.

Data Centre Interconnect Is Becoming a Strategic Network Priority

As the number and scale of AI Data Centres continue to grow, the ability to transfer massive volumes of data between facilities has become increasingly important. This has elevated the role of Data Centre Interconnect (DCI), which provides the high-capacity links that connect geographically distributed data centres and cloud environments. Rather than functioning as isolated facilities, modern AI Data Centres operate as interconnected ecosystems where continuous data exchange supports AI training, inference, storage, and enterprise applications.

The expansion of DCI is driving greater investment in high-capacity optical transport networks capable of delivering low-latency, high-bandwidth connectivity across metropolitan, regional, and international routes. These networks enable organizations to distribute computing workloads efficiently, improve resilience through redundancy, and optimize the use of available computing resources across multiple locations. As AI workloads continue to increase, DCI is becoming an essential component of telecom infrastructure rather than simply a supporting network service.

The growing importance of AI Data Centres also highlights the need for scalable network architectures capable of supporting future demand. Telecommunications providers are increasingly modernizing optical infrastructure to improve network efficiency while ensuring that data can move seamlessly between computing facilities, cloud platforms, and enterprise environments.

Edge Computing Is Extending the Reach of AI Data Centres

While centralized AI Data Centres provide the computational power required for large-scale artificial intelligence workloads, not every application can rely solely on centralized processing. Many AI-powered services require immediate decision-making, making low latency a critical operational requirement. This is driving the expansion of edge computing, where data is processed closer to users, connected devices, and enterprise operations.

Rather than replacing centralized facilities, edge computing complements AI Data Centres by distributing processing across multiple locations. This architecture reduces network congestion, shortens response times, and improves the performance of applications such as industrial automation, connected vehicles, healthcare systems, financial services, and smart city infrastructure.

The relationship between edge computing and AI Data Centres is creating a more distributed telecommunications ecosystem capable of supporting increasingly sophisticated digital services. High-capacity backbone networks transport large-scale AI workloads between data centres, while edge infrastructure enables localized processing for applications that depend on real-time intelligence. Together, these technologies are reshaping how telecom networks deliver both scalability and performance.

Infrastructure Challenges Will Shape the Next Phase of Growth

The rapid expansion of AI Data Centres is creating new opportunities for telecommunications infrastructure, but it also presents significant operational challenges. Supporting AI workloads requires far greater computing power, higher network capacity, and increased energy availability than conventional enterprise applications. As a result, infrastructure planning is becoming increasingly complex as operators balance performance, sustainability, and long-term scalability.

Power availability has emerged as one of the most significant considerations for new AI Data Centres. High-performance computing environments consume substantially more electricity than traditional facilities, increasing demand for reliable energy infrastructure and efficient cooling technologies. At the same time, telecommunications networks must continue expanding fibre capacity, optical transport systems, and interconnection infrastructure to accommodate rapidly growing AI traffic.

Cybersecurity and network resilience are becoming equally important. As AI Data Centres handle increasingly critical enterprise workloads, protecting network infrastructure, maintaining service availability, and ensuring secure data transmission remain essential priorities. Future network expansion will therefore require not only greater capacity but also stronger operational resilience capable of supporting business-critical AI services.

AI Data Centres Are Defining the Future of Telecom Infrastructure

The evolution of telecommunications infrastructure is increasingly being shaped by artificial intelligence rather than traditional network growth alone. AI Data Centres are becoming central to this transformation by driving demand for higher-capacity networks, intelligent traffic management, distributed computing, and more resilient digital infrastructure.

Future telecom networks will need to support continuous data movement across cloud platforms, edge locations, enterprise environments, and interconnected data centres while maintaining high performance and operational efficiency. This will require ongoing investment in fibre networks, optical transport, cloud-native architectures, and intelligent network management systems capable of adapting to rapidly evolving AI workloads.

As organizations continue expanding AI adoption across industries, AI Data Centres will remain at the centre of digital infrastructure planning. Their growing influence extends beyond computing capacity, reshaping how telecommunications networks are designed, scaled, and optimized to support the next generation of intelligent digital services.

Conclusion

The rise of AI Data Centres represents more than an increase in computing capacity. It marks a fundamental shift in how telecommunications infrastructure is planned, deployed, and managed to support increasingly data-intensive digital environments. High-capacity fibre networks, optical transport systems, Data Centre Interconnect, and edge computing are becoming essential components of AI-ready telecom infrastructure capable of delivering the bandwidth, scalability, and resilience required by modern enterprises.

While challenges surrounding power availability, network scalability, cybersecurity, and infrastructure investment remain, the continued expansion of AI Data Centres is accelerating the modernization of telecommunications networks worldwide. As artificial intelligence becomes more deeply integrated into business operations and digital services, AI Data Centres will continue shaping the future of connected infrastructure and next-generation telecom networks.

The announcement, made on 4 August 2026, confirms Intel as a Premier Member of the Intel OCuDu Foundation initiative. The collaborative effort is focused on fostering vendor-neutral Radio Access Network software across both Centralised Unit and Distributed Unit environments. The goal is to reduce integration complexity and enable rapid deployment of production-grade software for 5G and future 6G networks.

Intel joins a roster of Premier Members that includes AMD, AT&T, DeepSig, Ericsson, Nokia, NVIDIA, Qualcomm, Samsung, SoftBank, Software Radio Systems, and Verizon. The breadth of membership underscores the industry-wide commitment to open RAN principles and cloud-native infrastructure development.

Intel’s Contribution to the OCuDu Foundation

As part of its involvement with the Intel OCuDu Foundation collaboration, Intel will bring its expertise in semiconductor design alongside its capabilities in cloud-native networking and telecommunications software. The company will support the open RAN community in defining reference architectures, validating and standardising continuous integration, delivery, and testing processes, and establishing operational best practices for telecommunication companies.

The participation is expected to strengthen the foundation’s capacity to deliver standardised, interoperable solutions that reduce barriers for telecom operators looking to deploy open and vendor-neutral 5G RAN deployment infrastructure at scale. Intel’s deep experience in hardware and cloud-native infrastructure positions it as a significant contributor to the foundation’s technical roadmap.

Impact on Cloud and Enterprise Infrastructure

The Intel OCuDu Foundation partnership carries notable implications for cloud providers, enterprise IT leaders, and infrastructure professionals. By contributing to open-sourced network software, Intel aims to help telecom operators worldwide adopt AI-native, open-sourced radio access networks. The collaboration is designed to move the industry beyond prototype-stage adoption towards production-ready implementations of vendor-neutral network technologies.

Arpit Joshipura, General Manager of Networking, Edge, and IoT at the Linux Foundation, stated that Intel’s cloud-native and hardware-rooted leadership would accelerate the collaborative efforts within the Intel OCuDu Foundation ecosystem. According to Joshipura, Intel’s involvement will propel the industry forward and hasten the maturity of the technology landscape surrounding open RAN and 5G RAN deployment.

Next Steps for the Collaboration

The Intel OCuDu Foundation membership signals a deepening commitment from both Intel and the broader industry towards fully realising open-sourced network software. Intel will work alongside existing Premier Members to define reference architectures, advance cloud-native infrastructure standards, and validate testing frameworks that support production-grade vendor-neutral network deployments.

The collaboration is set to benefit telecom operators seeking to reduce reliance on proprietary solutions while accelerating the rollout of 5G and preparing pathways for future 6G wireless communications networks. With Intel now actively contributing its silicon and cloud-native expertise, the foundation’s mission to deliver interoperable, open RAN solutions moves closer to large-scale commercial reality.

During a virtual media briefing on 30 July, networking equipment provider Ciena outlined how the growing scale of AI data centre networks is reshaping demand for high-capacity connectivity services worldwide. The company said revenue from such services is forecast to grow at a compound annual rate of 18 per cent from 2025 to 2030. Southeast Asia is expected to outpace the global market, with annual growth projected at 22 per cent over the same period.

“We believe that service providers who are well-prepared to take advantage of these opportunities will unlock this new revenue growth curve by enabling this AI ecosystem,” said Francisco Sant’Anna, senior adviser for market intelligence at Ciena.

Key Drivers Behind Rising Demand for AI Data Centre Networks

Ciena identified three primary sources of demand fuelling growth in AI data centre networks and high-capacity connectivity. The first is the scale of investment by hyperscale and AI-focused cloud providers. According to the company, major cloud operators are expected to invest a combined $600 billion in new data centres in 2026 alone. When spending by smaller cloud providers specialising in AI computing referred to as “neoscalers” is factored in, total AI infrastructure investment could exceed $1 trillion.

These investments will require network providers to connect large data centres used for training and running AI models, as well as link increasingly distributed computing facilities. Smaller AI cloud providers may also need flexible bandwidth and managed connectivity services as their operations scale.

The second driver is the growing geographic distribution of data centres. The physical requirements of AI data centre networks, including access to land, power, and water are pushing facilities farther from major urban centres. At the same time, data sovereignty regulations and the need to reduce latency are encouraging companies to establish more facilities closer to their end users. Ciena said this trend is already visible in Southeast Asia, particularly in Indonesia, Malaysia, and the Philippines.

The third source of demand comes from enterprise AI adoption. As companies deploy more inference workloads, existing networks can become bottlenecks in moving data between users, cloud platforms, and computing facilities.

Southeast Asia Emerges as a Growth Hub for AI Infrastructure

Alex Wong, Ciena regional managing director for Asean, Hong Kong, and Taiwan, said Southeast Asia has the land, power, water, fibre infrastructure, and cross-border links needed to support the expansion of AI data centre networks. He also pointed to continuing investments and a developing regulatory environment across the region.

The Philippines, in particular, could benefit from several submarine cable systems expected to land in the country, strengthening its links to regional and global data centres. Ciena said it is working with local telecommunications companies including PLDT, Globe, and Converge to develop networks capable of supporting hyperscale investments. Additional data centres are also under construction in the country to meet anticipated AI demand.

Operators Must Adapt Networks for AI Workloads

However, Wong cautioned that telecommunications companies must recognise that AI applications impose different requirements from conventional internet traffic.

“AI workloads are much more dynamic, much more sensitive to latency, and the infrastructure is becoming more distributed, so operators have to think beyond simply adding more bandwidth,” Wong said.

He added that an AI-ready operator is one that can deliver more than basic connectivity. “They can provide high-performance networks that can move huge volumes of data quickly, reliably, and predictably between the distributor and compute locations. That is what separates an AI-ready network from a traditional one,” he said.

The growing investment in AI data centre networks across Southeast Asia signals a substantial shift in what telecom operators must deliver, with high-capacity connectivity and network flexibility becoming essential capabilities for those seeking to capture new revenue from the AI ecosystem.

The AI Data Centre Interconnect Superhighway is designed to connect multiple data centres across Hong Kong, enabling enterprises and cloud providers to process increasingly complex AI workloads with higher bandwidth and improved network performance.

AI Data Centre Interconnect Superhighway Delivers 3.2Tbps Connectivity

The new network is built to meet the rapidly increasing demand for AI computing infrastructure as enterprises expand the deployment of generative AI, machine learning and large language models. By providing up to 3.2Tbps of transmission capacity, the AI Data Centre Interconnect Superhighway enables high-speed communication between AI data centres, distributed GPU clusters and cloud platforms.

According to HKT, the infrastructure is designed to reduce latency while supporting large-scale AI model training, inference and data-intensive workloads that require continuous, high-bandwidth connectivity.

The company said the network also offers the scalability needed for future AI deployments, allowing enterprises to expand computing resources without compromising network performance.

AI Infrastructure Demand Continues to Grow

The launch reflects a broader shift across the telecommunications industry, where operators are increasingly investing in AI-ready infrastructure rather than traditional connectivity services alone. As organisations deploy more AI applications, demand for resilient optical networks capable of transporting massive volumes of data between data centres continues to rise.

The AI Data Centre Interconnect Superhighway positions HKT to support cloud providers, hyperscalers and enterprises building next-generation AI environments that depend on reliable, ultra-fast network performance.

Industry analysts expect telecom operators worldwide to continue expanding AI-focused network infrastructure as investments in data centres, GPU clusters and edge computing accelerate.

Telecom Operators Expand AI Network Capabilities

The introduction of the AI Data Centre Interconnect Superhighway also highlights the evolving role of telecom operators in the AI ecosystem. Beyond delivering connectivity, operators are increasingly becoming infrastructure partners for AI development by providing high-capacity transport networks that support cloud computing and data centre interconnection.

As AI adoption continues to accelerate across industries, investment in advanced optical networking is expected to become a key competitive differentiator for telecom providers. HKT’s latest deployment demonstrates how operators are adapting their infrastructure strategies to meet the growing bandwidth, scalability and low-latency requirements of enterprise AI applications.

Virtualizing the Ground Segment

At the heart of this transformation is the virtualization of the satellite ground segment. In the past, connecting to a satellite required specialized, proprietary hardware proprietary modems, baseband processors, and massive, fixed dish antennas. This rigid infrastructure was a major barrier to entry and a significant operational burden. The move toward cloud integrated satellite networks transforming telecom involves shifting these hardware functions into software running on standard off-the-shelf servers in cloud data centers. This “Ground Station as a Service” (GSaaS) model allows satellite operators to scale their ground infrastructure up or down in real-time, matching the capacity of their orbiting assets without the need for massive capital investment in physical ground sites.

This shift toward software-defined ground stations also enables a high degree of automation. Instead of a technician needing to manually reconfigure a modem for a new satellite pass, the cloud-based system can do it automatically in milliseconds. This agility is essential for managing the massive LEO constellations that are currently being launched, where hundreds of satellites are moving across the sky at all times. By leveraging the power of the cloud, operators can ensure that every satellite is utilized to its maximum potential, maximizing the return on investment and lowering the cost of data for the end-user. This virtualization is a core component of cloud integrated satellite networks transforming telecom, making space-based connectivity as flexible and accessible as a standard web service.

Edge Computing in the High Frontier

The integration of cloud and satellite technology is also moving the “edge” of the network further out than ever before. Cloud integrated satellite networks transforming telecom are increasingly incorporating edge computing resources directly into the satellite payload or the remote user terminal. This allows for data to be processed as close to the source as possible. For example, a remote industrial sensor in a deep-sea oil rig can have its data analyzed and filtered by an AI algorithm running on a nearby satellite before only the most critical information is sent back to the central cloud. This reduces the amount of bandwidth required and significantly lowers the latency for time-sensitive applications.

Edge computing also enhances the security and privacy of the network. By processing data locally, sensitive information can be anonymized or encrypted before it ever leaves the remote site. This is particularly important for industries like healthcare or finance, where data sovereignty is a major concern. Furthermore, the combination of satellite reach and edge intelligence allows for the creation of “local clouds” in areas that have no connection to the public internet. This can be a lifesaver for disaster relief teams or military units operating in hostile environments, providing them with the processing power and data they need to accomplish their missions safely. The reach of cloud integrated satellite networks transforming telecom is thus extending the digital frontier to the very edges of our planet.

Real-Time Data Processing for Global Enterprise

For the modern enterprise, data is the most valuable commodity, and the speed at which that data can be processed into actionable intelligence is a major competitive advantage. Cloud integrated satellite networks transforming telecom provide a seamless link between a global workforce and central cloud resources. Whether it is a mining operation in the Australian Outback or a research vessel in the Antarctic, employees can access the same cloud-based ERP systems, collaborative tools, and data analytics platforms as their colleagues in a metropolitan office. This level of seamless enterprise connectivity is essential for the digital transformation of industries that operate in the most challenging environments on earth.

In the logistics industry, real-time data processing allows for the dynamic routing of ships and planes based on changing weather patterns or port congestion. This not only saves time and money but also reduces the carbon footprint of the global supply chain. In the energy sector, satellite-linked sensors can monitor the integrity of thousands of miles of pipelines, detecting leaks or pressure changes instantly and preventing environmental disasters. These are not just theoretical benefits; they are the real-world results of cloud integrated satellite networks transforming telecom, proving that the integration of space and cloud is a powerful driver of economic efficiency and environmental sustainability.

Scalable Infrastructure for a Dynamic World

Scalability is perhaps the most significant benefit of the cloud-integrated model. In a traditional telecom setup, adding capacity meant physically installing more hardware. In the world of cloud integrated satellite networks transforming telecom, capacity can be added with the click of a button. By using software-defined networking (SDN) and network functions virtualization (NFV), a telecom operator can dynamically allocate bandwidth across their entire satellite fleet based on real-time demand. This agility is vital for responding to sudden shifts in the global economy, such as the rapid deployment of connectivity for a new industrial site or providing emergency bandwidth for disaster relief operations.

This scalability also extends to the “pay-as-you-go” business model that has made the cloud so successful. Instead of paying for a fixed amount of satellite capacity that may sit idle for much of the day, an enterprise can pay only for the data they actually use. This lowers the barrier to entry for smaller companies and allows them to compete on a global stage. The democratizing power of cloud integrated satellite networks transforming telecom is thus creating a more vibrant and competitive global economy, where the size of your company is no longer a barrier to the quality of your connectivity.

Enterprise IT and the “Cloud-First” Strategy

Most large organizations have already adopted a “cloud-first” IT strategy, moving their core business processes to platforms like AWS, Microsoft Azure, or Google Cloud. Cloud integrated satellite networks transforming telecom are the final piece of this puzzle, extending the reach of these cloud platforms to every square inch of the planet. Satellite providers are now forming strategic partnerships with cloud giants to co-locate satellite gateways within cloud data centers. This “direct connect” approach minimizes the number of “hops” a data packet has to take, further reducing latency and enhancing the overall security and performance of the link.

For an enterprise IT manager, this means they can manage their global satellite links using the same tools and interfaces they use for their terrestrial office networks. This unified management approach reduces the complexity of global operations and ensures that security policies are applied consistently across the entire organization. The integration of satellite into the broader enterprise IT stack is a major milestone in the evolution of telecom, moving space-based connectivity from a specialized niche into the mainstream of corporate digital infrastructure. Cloud integrated satellite networks transforming telecom are thus the bridge that finally connects the “local” cloud to the “global” reality.

The Impact on Digital Transformation Initiatives

Digital transformation is about more than just moving data to the cloud; it is about fundamentally changing how a business operates. Cloud integrated satellite networks transforming telecom are enabling this change in sectors like maritime, aviation, and logistics. A shipping company can now use real-time cloud analytics to optimize its fleet’s fuel consumption based on weather patterns relayed via satellite. An airline can provide a consistent “office in the sky” experience for its passengers by linking its onboard Wi-Fi directly to a cloud-based content delivery network (CDN). These are not just incremental improvements; they are new business models that were simply not possible before the integration of cloud and satellite technologies.

In the retail sector, cloud-integrated satellites allow for the deployment of “pop-up” stores in remote areas or at large outdoor events, providing them with the same secure point-of-sale and inventory management systems as a permanent brick-and-mortar location. In the media industry, journalists can broadcast high-definition video directly from the scene of a news event to a cloud-based production studio, allowing for real-time editing and distribution. These examples show that the reach and flexibility of cloud integrated satellite networks transforming telecom are a powerful catalyst for innovation, helping businesses of all kinds to find new ways to serve their customers and grow their bottom line.

Security and Resilience in the Cloud Era

One of the biggest concerns for any global network is security. Moving data across a satellite link was once seen as a vulnerability, but cloud integrated satellite networks transforming telecom are actually more secure than their predecessors. By using the advanced security protocols of the major cloud providers, including end-to-end encryption and identity-based access control, satellite links can be made as secure as a private fiber connection. Furthermore, the distributed nature of the cloud-satellite architecture provides a high degree of resilience. If one ground station or data center goes offline, the network can automatically reroute traffic through another path, ensuring that critical communications are never interrupted.

This resilience is particularly important for government and military users who need to maintain a “never-fail” communication link. By using a mix of public cloud resources and private satellite capacity, these users can create a “hybrid” network that is both highly secure and incredibly robust. The ability to dynamically shift workloads between different satellites and data centers makes the network much harder to target or disable. In an era of increasing cyber threats and geopolitical instability, the security and resilience provided by cloud integrated satellite networks transforming telecom are a vital asset for national security and public safety.

The Future of the Sovereign Cloud

As nations become more concerned about data sovereignty and national security, we are seeing the rise of the “sovereign cloud.” These are localized cloud environments that are governed by a specific nation’s laws and stored within its borders. Cloud integrated satellite networks transforming telecom play a vital role here, providing a way for governments to maintain a secure, independent communication network that is still fully integrated with modern cloud-based services. This capability is becoming increasingly important for military and intelligence agencies that need to operate globally while keeping their data within a trusted, sovereign environment.

Looking ahead, we can expect to see the development of “satellite-native” cloud services, where the processing and storage happen entirely in orbit. This would create a truly global, “borderless” cloud that is independent of any terrestrial geography. While this is still in the early stages of development, the ongoing convergence of space and cloud technology makes it a very real possibility for the 2030s. Cloud integrated satellite networks transforming telecom are thus not just changing how we communicate today; they are laying the groundwork for the next generation of our digital civilization, where the sky is no longer the limit, but the starting point.

Having spent the last couple of years talking up the capabilities related to its planned LEO satellite-based mobile broadband service, AST is now coming up with a major prospective customer base one of the reasons that it has billion dollars in revenue commitments. Operator partnerships as well as trials are now bound to happen in many European markets along with Asia and Africa as well as North America.

One of the latest customer announcements comes from Telus from Canada, which has inked a commercial agreement in order to launch its direct-to-device (D2D) service. As per the terms of the deal we do not have a valuation Telus is going to invest in ground-based satellite infra and is going to become an equity shareholder when it comes to AST SpaceMobile.

Starting late 2026, the customers from Telus are going to be able to make phone calls, send text messages, and make use of data through the satellite operator in some of the most remotely situated locations across Canada, remarked the company.

The fact is that the late 2026 date is important, as AST SpaceMobile has recently committed to bringing commercial services to market in 2026. But it’s worth noting that the Telus announcement does not necessarily notify if this is going to be a commercial launch or a trial launch. One will have to wait longer for this information, in addition to details on pricing, etc.

The commercial services pledge by AST SpaceMobile hinges in part on its capacity to get more satellites into orbit. It at present has just one second-generation satellite in space, which is called BlueBird 6, and as a matter of fact aimed to add BlueBird 7 into the product mix before February 2026, but it remains on the ground.

In its full-year results announcement that came to effect earlier, AST SpaceMobile went on to share that BlueBird 7 is at Cape Canaveral and is most likely going to launch sometime in March 2026. It also pushed its plan to launch somewhere between 45 and 60 satellites in 2026 alone.

BlueBird 8 to BlueBird 29 happen to be in various stages of production, it went on to add, noting that it has gone on to increase its manufacturing space via acquisition of a fourth site located in Texas. Apparently, none of this comes easy and cheap, so it does not come as a surprise that the 2025 balance sheet of AST SpaceMobile showcases hefty losses. The bottom line of the company came to $341.9 million in 2025, which was greater as compared to 2024 – a time when it was a shade over $300 million.

In the fourth quarter alone, its net loss amounted to $74 million, or 26 cents per share, which was more than double the $35.9 million figure that it reported in the year-earlier period and also behind the analysts’ anticipations; apparently Zacks had anticipated a loss of 18 cents.

Naturally, AST SpaceMobile was indeed bent toward focusing on the positives, underscoring its $3.9 billion in cash and cash equivalents on its balance sheet, along with its first-ever revenue-generation position. Reported revenue was at $70.9 million in 2025, driven by mobile network operator partners as well as the US government, said the company. That figure went on to beat the expectations from analysts.

Product revenue came from the delivery of 15 gateways across the world, it said, whereas the service revenue got generated by way of multiple contracts as well as use cases under development with the government. It anticipates increasing the revenue in 2026 ahead of the commercial services launch, on the back of a backlog of MNO partner revenue along with certain other government contract landmarks.

And more importantly, AST SpaceMobile remarked that it had secured more than $1.2 billion of the aggregate contracted revenue commitments when it comes to commercial partners. That figure happens to include a $175 million commitment that comes from the STC Group of Saudi Arabia, which inked a 10-year deal along with the satellite firm in November 2025, and also a $30 million contract with the US Space Development Agency when it comes to the use of its BlueBird constellation by the HALO Europa programme. And then there happen to be the telcos. For the majority, one doesn’t have the access to financial details of arrangements made by AST SpaceMobile along with mobile operators. However, what one does know is that the partnership announcements are coming fast.

The company started the Mobile World Congress with the news that it is going to be working with Orange and Telefonica in Spain, Germany, and Romania as well as certain other European markets through Satellite Connect Europe JV along with Vodafone. These happen to be collaboration announcements at this stage; however, they should lead to service launches as well.

In a similar way, Satellite Connect Europe went on to reveal that it has gone ahead and collaborated along with Sunrise in order to gauge how its open access D2D offer could as well go in sync with terrestrial 4G and 5G mobile networks of the Swiss telco.

And it also went on to disclose that it is going to start trials with CK Hutchison this year’s summer in both Austria and Italy, with a standpoint to launch the D2D services there, along with the telco groups’ operations based in Denmark and Ireland as well as Sweden, at a date that’s not specified.

Furthermore, Taiwan Mobile also went ahead and inked what it has termed as a Strategic Cooperation Memorandum along with AST SpaceMobile with a view to integrating the direct-to-cell into the portfolio. And Axian Telecom from Africa has also announced a D2D deal with the company at the Congress.

In order to use its own words, AST SpaceMobile also went ahead and progressed initiatives with Vodafone, which is another of the investors it has as well as its open access JV partner.

The news of trials with Vodafone 3 in the UK in the summer of 2026 was indeed widely anticipated; however, the company also went ahead and shared that it has come together with Vodafone in Romania, Ukraine as well as Ireland on a direct-to-device. Testing has already begun in Ireland, it remarked, with Vodafone having secured the first test and trial license in the country.

Satellite Connect Europe went on to say that it, Vodafone, along with other collaborating operators, is going to work with the EU in order to develop a harmonized European framework when it comes to satellite D2D, such as a simplified authorization process.

All this should indeed be music to the ears of the GSMA, which has also managed to have its say when it comes to D2D at MWC. It is well to be noted that the industry body went ahead and published a new position paper that was called ‘Regulatory Preparedness for Satellite Services,’ wherein it urged policymakers to go ahead and simplify the regulatory process while the LEO services happen to be in their infancy.

According to the Chief Regulatory Officer of the GSMA, John Giusti, “Establishing comparable requirements for mobile and satellite providers delivering similar services will help ensure consistent consumer protection, support sustainable long-term investment across communications networks, and safeguard national sovereignty – all while delivering greater value, quality, and trust for users.”

If the 2026 MWC is anything to go with, national regulators will have to get themselves rolling on if they have not already sorted out the D2D regs. Starlink has started making its mark across a number of markets, and it has also made news in Barcelona, and now AST SpaceMobile looks to be on the verge of indeed going ahead and taking the sector by storm.

Exabeam, a global leader in intelligence and automation that powers security operations, today announced the findings of its new multinational report, From Adoption to Accountability: The New Economics of AI in Cybersecurity. Based on a survey of 750 IT decision-makers responsible for security in organizations with 500+ employees across 12 countries, the research reveals a critical paradox. While cybersecurity budgets surge with unprecedented growth, security leaders race ahead on AI transformation while falling behind on measurement, justification, and strategic alignment.

According to the study, 95% of organizations are increasing cybersecurity budgets in 2026, with 74% seeing double-digit growth. However, AI simultaneously holds three contradictory positions in budget planning: it’s the top driver of increases (44%), the first investment that would be cut if budgets tightened (44%), and the most challenging spend to justify to business stakeholders (32%).

“Security leaders are getting mandates to invest in AI, but nobody’s given them a way to prove it’s working. You can’t measure AI transformation with pre-AI metrics,” said Steve Wilson, Chief AI and Product Officer at Exabeam. “The problem isn’t that security teams lack data. They’re drowning in it. The issue is they’re tracking the wrong things and speaking a language the board doesn’t understand. Those are the budgets that get cut first. The window to fix this is closing fast.”

Unprecedented Budget Growth Driven by AI Transformation

Cybersecurity investment trends in 2026 represent a significant shift, with AI and automation emerging as the primary catalyst for budget expansion (44%), followed by cloud infrastructure growth (33%) and mainstream business AI adoption (32%). This surge being channeled into technology, rather than the usual suspect of headcount, signals how the AI era is fundamentally shifting security operations.

The Value Demonstration Gap Creates Vulnerability

While 87% of security leaders express confidence that their investments are delivering business value, 30% cite a lack of board understanding of the link between cybersecurity investment and business resilience as their biggest challenge in defending spend. The disconnect reveals a critical vulnerability: 63% of security leaders report using quantified ROI and 59% use outcome metrics, yet boards and executives still don’t understand the connection between security investments and business risk.

The problem isn’t a lack of information, but a mismatch between security metrics and business-decision metrics. Security teams are relying on traditional security measurements that don’t translate into the business impact language boards need to evaluate investment decisions.

“In AI-assisted environments, traditional metrics like mean time to resolution (MTTR) becomes almost automatic, so speed alone doesn’t prove risk has been reduced,” said Kevin Kirkwood, CISO at Exabeam. “We need new ways to measure security effectiveness that actually show business impact, because boards don’t fund faster ticket closure, they fund measurable risk reduction and business resilience. We have to show that we’re not just responding quickly but eliminating and improving the conditions that allow incidents to happen in the first place.”

Regional Variations Show Diverse AI Adoption Strategies

Regional differences in AI adoption are striking. Saudi Arabia demonstrates the most aggressive position, with 75% reporting AI is already improving security operations, nearly triple the rate of Japan (27%) and the Netherlands (30%). These variations reflect different organizational priorities. Saudi Arabia’s figures align with broader national digital transformation initiatives, while European and Asian organizations emphasize careful evaluation and workforce preservation before scaling deployment.

Closing the Justification Gap

The cybersecurity industry is experiencing a rare moment of budget abundance, yet this creates a sustainability challenge. Security leaders are investing heavily in AI transformation while simultaneously struggling to articulate its business value to boards and CFOs. This isn’t a sustainable dynamic budget abundance creates expectations, and organizations that can’t demonstrate clear value from AI investments risk seeing those budgets retracted when economic conditions shift.

The organizations that will thrive are those that recognize deployment is only half the challenge. Success requires developing new frameworks for measuring AI impact, creating outcomes-based metrics that tie security performance directly to business resilience, and establishing executive-ready communication that translates technical improvements into business impact language.

To access the full report, From Adoption to Accountability: The New Economics of AI in Cybersecurity, visit: https://www.exabeam.com/from-adoption-to-accountability

Methodology

This report is based on research conducted by Sapio Research on behalf of Exabeam in December 2025. The survey captured insights from 750 IT decision-makers responsible for security in organizations with 500+ employees. Respondents represented 12 countries across Europe (UK, Ireland, France, Germany, Netherlands), North America (USA, Canada), and Asia-Pacific and Middle East regions (India, Saudi Arabia, Singapore, Japan, Australia), spanning key sectors including technology, financial services, manufacturing, healthcare, retail, telecommunications, and government.

The Structural Shift from Centralized to Distributed Cloud Networks

For the past two decades, the dominant model of the internet has been centralization. Huge “hyperscale” data centers, often located in remote areas with cheap land and power, handled the vast majority of the world’s processing needs. While efficient for bulk data storage and non-time-sensitive tasks, this model is inherently flawed for the modern era. The physical distance between the user and the data center creates a “latency floor” that cannot be overcome by simply increasing bandwidth. Edge data centers low latency networks address this by creating a distributed cloud architecture. These smaller, localized facilities are placed in urban centers, at the base of cell towers, or even within office buildings. This proximity allows for real time data processing that occurs in milliseconds rather than seconds, providing the “instant” feedback that modern applications require.

Enabling Real-Time Applications and the Internet of Things

The primary driver for the deployment of edge computing infrastructure is the explosion of the Internet of Things (IoT). In a smart factory or a modern hospital, thousands of sensors generate a continuous stream of data that must be analyzed and acted upon immediately. Sending this data to a central cloud and waiting for a response is not an option when a robot needs to adjust its grip or a heart monitor needs to alert a surgeon. Edge data centers low latency networks provide the localized “brain” required for these mission critical services. By filtering and processing data locally, these edge nodes reduce the load on the central network and ensure that critical decisions are made with zero perceptible delay, paving the way for a more efficient and safer industrial landscape.

Telecom Edge Architecture and the Integration with 5G

The rollout of 5G networks and the expansion of edge computing are two sides of the same coin. While 5G provides the high-bandwidth “pipes,” edge data centers low latency networks provide the “engine” that powers the content moving through them. Telecom edge architecture involves integrating small-scale data centers directly into the telecommunications network. This allows mobile operators to offer “Edge as a Service” (EaaS) to businesses and developers. For the consumer, this means that high-fidelity VR gaming or real-time language translation can happen on a smartphone without any lag. For the enterprise, it allows for the deployment of private 5G networks that can manage an entire warehouse of autonomous robots with absolute precision and security.

Network Optimization and the Efficiency of the Edge

Beyond speed, edge data centers low latency networks offer a significant advantage in terms of network optimization and cost-efficiency. In a centralized model, every byte of data no matter how trivial must be sent across the backbone of the internet. This creates massive congestion and requires expensive bandwidth upgrades. Edge nodes act as a first line of defense, processing and “cleaning” data locally. For example, a high-resolution security camera can use edge-based AI to identify a potential threat and only send the relevant video clip to the central server, rather than streaming 4K footage 24/7. This reduction in “data traffic” saves money, reduces energy consumption, and ensures that the core network remains available for the tasks that truly require a global reach.

The Rise of Modular and Containerized Data Centers

The physical form of the edge data center is as innovative as its logical function. Because these facilities must be placed in dense urban environments or remote industrial sites, they often take the form of modular, containerized units. These “data centers in a box” are pre-fabricated, self-contained environments that include their own cooling, power backup, and security. This modularity allows for the rapid expansion of edge computing infrastructure, as a new node can be deployed and brought online in a matter of days. As we move toward a world of “micro-data centers,” we will see these units integrated into our cities’ fabric tucked into the corners of parking garages or hidden within the basements of retail stores creating a seamless, invisible layer of digital intelligence.

Addressing Challenges in Security and Decentralized Management

Decentralizing the cloud also means decentralizing the security perimeter. Managing thousands of small data centers is inherently more complex than managing a few large ones. Edge data centers low latency networks must be protected by a “Zero Trust” architecture that treats every node as a potential point of entry. Automated security tools and remote management platforms are essential for maintaining the integrity of these distributed networks. Furthermore, the physical security of edge nodes which are often located in unstaffed or public areas requires advanced biometric access controls and environmental sensors. The future of the edge depends on our ability to manage this complexity through AI-driven orchestration, ensuring that the entire network remains secure and performant without the need for a massive human workforce.

The Impact on Immersive Entertainment and the Metaverse

Perhaps the most visible impact of edge data centers low latency networks will be in the realm of entertainment. The “Metaverse” a persistent, shared virtual world cannot exist without the edge. For millions of people to interact in a high-fidelity virtual environment in real-time, the graphical processing must happen close to the user to avoid “motion sickness” caused by lag. Edge nodes can handle the heavy lifting of 3D rendering and physics calculations, delivering a smooth, immersive experience to even low-power devices like mobile phones or lightweight AR glasses. This democratization of high-end computing will transform how we play, learn, and socialize, making the virtual world as responsive and “real” as the physical one.

Building the Infrastructure for Autonomous Systems

In the final analysis, edge data centers low latency networks are the essential foundation for the age of autonomy. Autonomous vehicles, drones, and delivery robots all require a high-speed, local data link to navigate their surroundings and interact with other autonomous agents. A city filled with self-driving cars is essentially a giant, moving edge network, where every vehicle is a node that shares data on traffic, weather, and road conditions. This collective intelligence, supported by a network of edge data centers, will create a transportation system that is safer, faster, and more efficient than anything we have known. By pushing the limits of the cloud to the very edge of our world, we are building a more responsive and resilient foundation for the next century of human progress.

Key Takeaways:

1. Edge data centers are the necessary solution to the “latency floor” of centralized cloud computing, bringing processing power to within milliseconds of the end-user.
2. The integration of edge computing with 5G and IoT is enabling mission-critical services in healthcare and industry that require absolute real-time responsiveness.
3. Modular and containerized data centers are allowing for the rapid, scalable deployment of digital intelligence into the urban fabric, creating a more efficient and optimized global network.