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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.

Ericsson’s Private 5G Network Transforms Smart Manufacturing

Ericsson’s Private 5G Network Transforms Smart Manufacturing

Award Category: Private Network Excellence in Manufacturing

Winner: Ericsson


Ericsson has been recognized with the TeckNexus 2024 Award for "Private Network Excellence in Manufacturing" for its transformative work at the USA 5G Smart Factory in Lewisville, Texas, and global deployments such as the Smart Factory Innovation Centre in Wolverhampton, UK, Atlas Copco Tools, and Toyota Material Handling’s facility in Columbus, Indiana. By integrating private 5G connectivity with advanced Industry 4.0 technologies, Ericsson has set new benchmarks for optimizing manufacturing processes, enhancing supply chain resilience, and elevating operational efficiency. This award underscores Ericsson’s leadership in leveraging private 5G to drive innovation in areas such as remote inspections, predictive maintenance, and sustainable production, redefining modern manufacturing standards through secure and scalable connectivity solutions.

Ericsson Launches Seven 5G Advanced Software Products for Next-Gen Networks

Ericsson Launches Seven 5G Advanced Software Products for Next-Gen Networks
Ericsson’s new 5G Advanced software suite empowers communications service providers (CSPs) to achieve high-performance programmable networks with advanced AI-driven automation, service-aware RAN, and intent-based networking. These innovations enable CSPs to optimize connectivity, drive revenue through network monetization, and deliver top-tier user experiences as 5G capabilities continue to evolve.

AI and Innovation: The Telecom Industry’s Key to Success

AI and Innovation: The Telecom Industry’s Key to Success
The telecom industry is rapidly evolving through the adoption of AI and a culture of continuous innovation. High-performing companies are leveraging technologies like 5G, AI-driven automation, and network slicing to improve efficiency and reduce costs. A recent Upwork Research Institute study reveals that companies focusing on workforce upskilling and aligning technology with business goals are better positioned for long-term success in a competitive market. These strategies are transforming telecom operations, making them more agile, cost-effective, and prepared for future challenges.

AI in Telecom: Why Healthy Skepticism Drives Better Adoption

AI in Telecom: Why Healthy Skepticism Drives Better Adoption
AI and generative AI hold significant promise for telecom, from network optimization to customer service automation. However, a cautious approach is necessary, as over 80% of AI projects fail. Telecom professionals remain skeptical, questioning AI's scalability and transparency. A balanced, evidence-based outlook can help telecom operators responsibly integrate AI, avoiding the pitfalls of early adoption while maximizing its transformative potential.

Cloud-Based Inventory Management Software: Smart Inventory Control

Cloud-Based Inventory Management Software: Smart Inventory Control
Cloud-based inventory management software is transforming how businesses handle their inventory, offering real-time tracking, cost savings, and enhanced collaboration. Unlike traditional systems, cloud-based solutions provide scalability, live data insights, and seamless integration, enabling businesses to efficiently manage orders, track stock, and optimize decision-making. With features like automated backups, powerful analytics, and 24/7 accessibility, companies can reduce costs and streamline operations.

Ignoring Customer Experience devalues Cutting-Edge Technologies

Ignoring Customer Experience devalues Cutting-Edge Technologies
Paul Warburton, Chief Digital and Marketing Officer NSC takes a look at the importance of prioritising the customer experience in the rapidly evolving landscape of technology, particularly with the advent of AI, 5G, and IoT. He warns that businesses risk stagnation if they focus solely on adopting cutting-edge technologies without aligning them with customer needs. The convergence of AI, IoT, and 5G is transforming industries and creating new possibilities, but this progress must be balanced with considerations of privacy, sustainability, and accessibility.

5G Smart Farming: Boldyn Networks & West Sussex Lead

5G Smart Farming: Boldyn Networks & West Sussex Lead
Boldyn Networks and West Sussex County Council are launching a £3.8M project to transform food and wine production through private 5G networks. The Growing Sussex 5G Innovation Region aims to boost sustainability and productivity in agriculture with technologies like AI, automation, and real-time data monitoring. The initiative also focuses on bridging the digital skills gap in the sector, supporting local businesses and educational institutions.

MWC Las Vegas 2024: Showcasing the future of industry at North America’s leading enterprise 5G gathering

MWC Las Vegas 2024: Explore 5G Innovations in Enterprise and Vertical Sectors
MWC Las Vegas 2024, running from October 8-10, is North America's top event for the enterprise 5G ecosystem. With keynotes from major players like Intel, Nvidia, Qualcomm, and T-Mobile for Business, this event brings together leaders from 5G carriers, hardware manufacturers, and technology vendors. Attendees will explore cutting-edge 5G use cases across sectors like aviation, automotive, manufacturing, and government, where AI, edge computing, and connected networks are revolutionizing industries.

Generative AI For Telecom and Technology

Generative AI For Telecom and Technology | Magazine Edition
In the latest edition of TeckNexus Magazine, explore how Generative AI is transforming the telecom industry. Dive into Jio’s JioBrain platform, the Supermicro-Nvidia partnership for scaling AI infrastructure, and Generative AI use cases for operators with insights from RADCOM. In an exclusive interview, Hardik Jain of GXC discusses integrating Generative AI with private 5G networks. Plus, gain insights from Eugina Jordan on Generative AI for business, Fiducia’s 5G and AI-driven stadium innovations, and strategies from 12 global operators on harnessing Generative AI for growth.

Generative AI and JioBrain: Exclusive Insights with Aayush Bhatnagar

Generative AI and JioBrain: Exclusive Insights with Aayush Bhatnagar
Explore how Reliance Jio’s innovative platform, JioBrain, leverages generative AI to transform telecom operations. In this exclusive Q&A, Aayush Bhatnagar discusses JioBrain's key features, 5G optimization, 6G readiness, and its impact on the Indian and global telecom sectors.

How Is Generative AI Optimizing Operational Efficiency and Assurance?

RADCOM Logo
How Is Generative AI Optimizing Operational Efficiency and Assurance? – TeckNexus and RADCOM Whitepaper
The whitepaper, "How Is Generative AI Optimizing Operational Efficiency and Assurance," provides an in-depth exploration of how Generative AI is transforming the telecom industry. It highlights how AI-driven solutions enhance customer support, optimize network performance, and drive personalized marketing strategies. Additionally, the whitepaper addresses the challenges of integrating AI into telecom operations, offering strategies to overcome obstacles such as data management, privacy, and the need for specialized telecom expertise.

MWC Las Vegas 2024

MWC GSMA - Las Vegas 2024 event
Event Start Date: 8th Oct, 2024
Event End Date: 10th Oct, 2024
Location: Las Vegas Convention Center, West Hall
Free Discovery Pass Code: FVPDEGBNPV

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.
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