AI Agent Competitive
Intelligence
Intelligence Journeys
AI Use Cases for Utilities
Start New Project →
Private Broadband for Utilities
Start New Project →

Automation

Network automation replaces manual configuration and operations with software-driven processes, ranging from scripted tasks to fully autonomous, self-optimizing networks. Driven by the complexity of 5G standalone, cloud-native architectures, and multi-vendor environments, operators are pursuing higher autonomy — often framed against the TM Forum’s autonomous networks levels — to cut costs, speed service delivery, and improve reliability. Automation increasingly relies on AI and closed-loop systems that sense, decide, and act with diminishing human intervention. For operators and enterprises, the practical path runs through incremental autonomy: automating well-defined tasks before attempting end-to-end self-operation. This channel covers network automation across RAN, core, and operations — including orchestration, closed-loop control, and the AI techniques behind autonomous networks — with analysis of where automation is delivering measurable results and how operators are progressing toward higher levels of autonomy.

AI-Powered Semantic Communication in 6G Networks

AI-Powered Semantic Communication in 6G Networks
According to telecom experts, 6G communication is expected to be path-breaking in its offerings. Artificial intelligence (AI) is being portrayed as the prime contributor to the enormous success of 6G networks. AI is set to play a pivotal role in shaping 6G to be relevant and rewarding for businesses and individuals. Several other digital technologies gel well to present 6G as the game-changing phenomenon in the communication world. One noteworthy facet is that the recent concept of semantic communication is to be elegantly realised through 6G networks. In this AI-first 6G book, we have elucidated how the predictive, generative, and agentic capabilities of AI are to make 6G communication penetrative, pervasive and persuasive too.

5G at Stadium of Light by Boldyn, Virgin Media O2, and JMA Wireless

5G at Stadium of Light by Boldyn & Virgin Media O2
Boldyn Networks and Virgin Media O2 have launched the UK’s first full RAN managed 5G service at Sunderland’s Stadium of Light. Powered by JMA XRAN® and a neutral host architecture, the deployment transforms fan experience, reduces energy use by 60%, and boosts operational safety and efficiency—setting a new benchmark for smart stadiums across the UK.

Is AI Underperforming in Telecom? Challenges, Use Cases & the Road Ahead

Is AI Underperforming in Telecom? Challenges, Use Cases & the Road Ahead
The telecom sector once hailed AI as a game-changer, but is it delivering? This article explores why many operators report low ROI on AI tools, and how legacy systems, cultural resistance, and regulatory hurdles stall adoption. Despite challenges, AI shows targeted promise in predictive maintenance, fraud detection, and 5G network slicing.

Tampnet Delivers Private 5G and Edge Connectivity to Island Innovator Rig

Tampnet Delivers Private 5G and Edge Connectivity to Island Innovator Rig
Tampnet has secured a five-year contract to deliver a fully managed private 5G network with LEO satellite, LTE, and edge computing to Island Drilling’s Island Innovator rig. Operating in the North Sea, the solution ensures low-latency, AI-orchestrated data flow for safer, smarter offshore operations, enabling automation, predictive maintenance, and real-time decision-making even in extreme conditions.

Lumen 400G Metro Data Center Connectivity for AI

Lumen 400G Metro Data Center Connectivity for AI
AI buildouts and multi-cloud scale are stressing data center interconnect, making high-capacity, on-demand metro connectivity a priority for enterprises. Training pipelines, retrieval-augmented generation, and model distribution are shifting traffic patterns from north-south to high-volume east-west across metro clusters of data centers and cloud on-ramps. This is the backdrop for Lumen Technologies push to deliver up to 400Gbps Ethernet and IP Services in more than 70 third-party, cloud on-ramp ready facilities across 16 U.S. metro markets. The draw is operational agility: bandwidth provisioning in minutes, scaling up to 400Gbps per service, and consumption-based pricing that aligns spend with variable AI and data movement spikes.

Vodafone Idea and IBM Launch AI Innovation Hub for 5G Telecom

Vodafone Idea and IBM Launch AI Innovation Hub for 5G Telecom
Vodafone Idea (Vi) and IBM are launching an AI Innovation Hub to infuse AI and automation into Vis IT and operations, aiming to boost reliability, speed delivery, and improve customer experience in Indias fast-evolving 5G market. IBM Consulting will work with Vi to co-create AI solutions, digital accelerators, and automation tooling that modernize IT service delivery and streamline business processes. The initiative illustrates how AI and automation can reshape telco IT and managed services while laying groundwork for 5G-era revenue streams. Unified DevOps across OSS/BSS enables faster rollout of plans, bundles, and digital journeys.

Chesapeake Launches City-Owned Private Network to Power Smart City Vision

Chesapeake Launches City-Owned Private Network to Power Smart City Vision
Chesapeake, Virginia, in partnership with Boldyn Networks, has launched Chesapeake Connects, a city-owned private LTE and IoT network aimed at transforming public services, improving digital equity, and reducing reliance on commercial carriers. The hybrid system leverages CBRS for Fixed Wireless Access and LoRaWAN for citywide IoT, supporting smart city infrastructure like flood sensors, smart traffic lights, and more.

Airtel Congo & Wing Wah Launch First Private Oilfield Network in Congo-Brazzaville

Airtel Congo & Wing Wah Launch First Private Oilfield Network in Congo-Brazzaville
Airtel Congo and Wing Wah have launched Congo-Brazzaville’s first private network at the Banga Kayo oil field, aiming to boost oilfield connectivity, network security, and digital transformation in Central Africa’s energy sector. This five-year agreement supports real-time monitoring, automation, and future 5G integration, setting a new precedent for telecom and oil industry partnerships in the region.

AI Traffic Growth: Ciena Report on Optical Network Readiness

  • Tech News & Insight
  • August 13, 2025
AI Traffic Growth: Ciena Report on Optical Network Readiness
A new Ciena and Heavy Reading study signals that AI will become a primary source of metro and long-haul traffic within three years while most optical networks remain only partially prepared. AI training and inference are shifting from contained data center domains to distributed, edge-to-core workflows that stress transport capacity, latency, and automation end-to-end. Expectations are even higher for long-haul: 52% see AI surpassing 30% of traffic and 29% expect AI to account for more than half. Yet only 16% of respondents rate their optical networks as very ready for AI workloads, underscoring an execution gap that will shape capex priorities, service roadmaps, and partnership models through 2027.

Korean Telecoms Launch 300B-Won AI & Semiconductor Fund

  • Tech News & Insight
  • August 13, 2025
Korean Telecoms Launch 300B-Won AI & Semiconductor Fund
South Korea's government and its three national carriers are aligning fresh capital to speed AI and semiconductor competitiveness and to anchor a private-led innovation flywheel. SK Telecom, KT, and LG Uplus will seed a new pool exceeding 300 billion won (about $219 million) via the Korea IT Fund (KIF) to back core and foundational AI, AI transformation (AX), and commercialization in ICT. KIF, formed in 2002 by the carriers, will receive 150 billion won in new commitments, matched by at least an equal amount from external fund managers. The platforms lifespan has been extended to 2040 to sustain long-cycle bets.

Rohde & Schwarz and Taiwan Space Agency deliver a dual-function satellite test chamber

  • Tech News & Insight
  • August 13, 2025
Rohde & Schwarz and Taiwan Space Agency deliver a dual-function satellite test chamber
A new joint solution from Rohde & Schwarz (R&S) and the Taiwan Space Agency (TASA) consolidates electromagnetic compatibility (EMC) and antenna measurements into a single, production-grade test chamber, signaling a shift in how satellite payloads will be validated for Non-Terrestrial Network (NTN) and mission-critical services. By integrating both disciplines in one chamber, TASA can validate RF performance, emissions, and immunity under consistent test conditions and configurations, improving time-to-launch and de-risking interoperability with terrestrial networks. The TASA deployment combines R&S hardware, software, and engineering with a locally built Compact Antenna Test Range (CATR) reflector to achieve dual-mode EMC and antenna measurements in one chamber.

NTT DATA and Google Cloud: Agentic AI & Sovereign Cloud

  • Tech News & Insight
  • August 13, 2025
NTT DATA and Google Cloud: Agentic AI & Sovereign Cloud
NTT DATA and Google Cloud expanded their global partnership to speed the adoption of agentic AI and cloud-native modernization across regulated and dataintensive industries. The push emphasizes sovereign cloud options using Google Distributed Cloud, with both airgapped and connected deployments to meet data residency and regulatory needs without stalling innovation. The partners plan to build industry-specific agentic AI solutions on Google Agent space and Gemini models, underpinned by secure data clean rooms and modernized data platforms. NTT DATA is standing up a dedicated Google Cloud Business Group with thousands of engineers and aims to certify 5,000 practitioners to accelerate delivery, migrations, and managed services.

Frequently Asked Questions

What’s the difference between automation and AI in a telecom context?
Automation, in its traditional form, generally follows pre-defined rules and scripted logic: a specific condition triggers a specific, predetermined response, with no real interpretation or judgment involved beyond what was explicitly programmed in advance. AI adds the capacity to learn from data, recognize patterns that weren’t explicitly anticipated, and make more nuanced decisions about what action makes sense in a given situation, even one the system hasn’t seen in exactly that form before. In practice, most modern telecom systems combine the two: AI analyzes a situation and decides what should happen, while automation infrastructure actually executes that decision reliably and consistently across the network, a combination often described as the foundation for agentic AI.
What is ‘zero-touch’ network operation, and how close is the industry to achieving it?
Zero-touch network operation describes the long-term industry goal of running networks with minimal direct human intervention, where the network itself handles configuration, fault recovery, and optimization automatically and continuously. It’s a meaningful aspiration rather than a fully achieved reality; the industry is progressing toward it in stages, with specific functions, like automated fault detection or dynamic capacity adjustment, achieving meaningful levels of automation well before the broader vision of an entirely self-managing network becomes reality. Standards bodies including ETSI have working groups specifically dedicated to defining the requirements for zero-touch network and service management, reflecting that this remains an active area of ongoing standardization rather than settled, widely deployed technology.
Why is automation considered essential for managing modern 5G networks specifically?
5G networks are substantially more complex than earlier generations for several compounding reasons: they rely heavily on virtualized network functions running across cloud infrastructure rather than fixed dedicated hardware, they support network slicing, meaning managing multiple distinct virtual networks with different performance guarantees simultaneously, and they often combine equipment and software from multiple different vendors rather than one integrated supplier. Traffic patterns also shift constantly and unpredictably as device density and application types continue to grow. Attempting to manually manage this level of complexity at the scale of a national or global network simply isn’t realistic, making automation effectively a practical requirement for operating a modern 5G network reliably at all.
How does automation relate to network orchestration?
Automation and orchestration are closely related but distinct concepts. Automation generally refers to executing a specific task without manual intervention, like automatically restarting a failed process or adjusting a configuration parameter. Orchestration refers to the broader coordination of multiple automated tasks and virtualized network components across their full lifecycle, deciding where different network functions should run, how they should scale, and how they interact with each other to deliver a complete service. In practice, orchestration systems often rely on underlying automation capabilities to actually carry out the individual tasks they coordinate, providing higher-level coordination while automation provides the lower-level mechanism for reliably executing decisions.
What are the risks of relying heavily on automated network systems?
Heavy reliance on automated systems introduces specific risks alongside its clear efficiency benefits. If an automated system makes an incorrect decision, that error can potentially propagate quickly and broadly across the network before a human notices and intervenes, compared to a manual process where mistakes tend to be more contained. There’s also a risk of reduced visibility and understanding among human staff over time, since heavily automated systems can create a gap between what the network is actually doing and what engineers fully understand about why, particularly as AI-driven decision-making becomes more involved. Operators generally manage these risks by maintaining careful guardrails for automated actions, expanding autonomous scope gradually as confidence grows.
How has automation changed the day-to-day role of network engineers?
Automation has shifted network engineers’ day-to-day work away from repetitive, manual configuration and troubleshooting tasks and toward higher-level responsibilities like designing automation policies, overseeing AI-driven systems, and handling more complex or novel problems that automated systems aren’t yet equipped to resolve independently. Rather than manually configuring each new service or personally diagnosing every fault, engineers increasingly spend time defining the rules, guardrails, and escalation criteria that govern how automated systems behave, then stepping in directly for situations that fall outside those parameters. This represents a meaningful skills shift, with growing demand for engineers comfortable working with automation platforms and AI systems alongside traditional networking expertise.
What’s ‘closed-loop automation,’ and why does it matter?
Closed-loop automation refers to systems that don’t just execute an automated action once, but continuously monitor the result of that action, compare it against the intended outcome, and adjust automatically if the result doesn’t match expectations, creating a self-correcting cycle without requiring a human to manually verify and re-trigger each step. A closed-loop system managing network capacity, for example, might automatically increase resources in response to rising traffic, then continuously monitor whether that adjustment actually resolved the congestion, and make further automatic adjustments if it didn’t. This concept is considered a meaningful step toward the zero-touch network vision, since it moves automation beyond simple one-off actions toward genuinely self-managing behavior based on real-world feedback.
AI Agent for Telecom Competitive Intelligence

Partner Hubs

Download content, access intelligence tools, and hear from executives.

Partner Events

  • Network X Vienna 2026
Scroll to Top