The journey from manually managed networks to fully autonomous systems marks a significant transformation in telecommunications. Traditionally, network operations relied on human expertise to monitor performance, troubleshoot issues, and optimise processes. While this reactive approach sufficed for simpler networks and times, it has become unsustainable in today’s complex environments.
Modern networks, powered by software and cloud technologies, span multiple physical, virtual, and logical layers. While 5G rollouts continue to introduce advanced capabilities like cloudification, network slicing and private networks, with more to come in Release 18, they have added significant complexity and an onus to see in real-time what is happening on the network. As the saying goes, ‘you can’t monetise what you can’t monitor’. However, the true promise of this evolution lies in the path to autonomy. As telcos look toward 2030, autonomy represents the ultimate goal, offering transformative benefits such as self-optimisation, proactive problem-solving, and scalable efficiency. For now, achieving this vision requires automation at scale to manage growing complexities and lay the foundation for fully autonomous networks.
Automation First
If autonomy is running, automation is walking—and it is the essential first step towards fully autonomous networks. This journey starts with the discipline of automation itself. Operators must evaluate how their networks and systems fit into an overarching automation strategy. Automation must be seen as a foundational capability that evolves, not just as a tool for efficiency.
The growing complexity of network environments, fuelled by technologies like 5G and network slicing, makes manual processes unsustainable. Automation is essential for managing the scale and dynamicity of modern telecommunications. Insights from existing Network Service Assurance systems—such as historical data, anomaly detection patterns, and troubleshooting workflows—are valuable assets for guiding automation strategies.
Dedicated teams that identify repetitive tasks and transition them to automated systems are critical to this process. By combining past learnings with advanced technologies, operators can streamline current operations and build a solid foundation for autonomous networks. This approach is already becoming a reality, with even smaller operators taking steps to implement automation-led network operations.
What Defines a Fully Autonomous Network?
A fully autonomous network can monitor, analyse, and act independently with minimal human intervention. It goes beyond automation, enabling systems to make real-time decisions aligned with business objectives. The TM Forum categorises this evolution into five levels, from basic automation (Level 1) to fully autonomous, intent-driven operations (Level 5).
Key characteristics of a fully autonomous network include:
The Challenges in Achieving Autonomy
Realising fully autonomous networks comes with challenges:
Autonomous systems require vast amounts of high-quality data to function effectively. The sheer volume and variety of data—from performance metrics to subscriber behaviour—can overwhelm traditional systems, especially as networks grow more complex with technologies like 5G, network slicing, and edge computing. Managing and integrating these datasets in real time is critical for enabling AI-driven automation.
Modern networks often include a mix of legacy systems and next-generation technologies, creating significant integration challenges. Autonomous systems must seamlessly span these boundaries, ensuring data flows freely between disparate platforms and that older systems can align with the demands of newer, software-defined environments.
Trust in AI systems is essential for operators to embrace autonomy fully. This requires explainable AI models and robust validation processes to ensure decisions align with business objectives and operational standards. Transparency is vital in areas like SLA management and regulatory compliance, where decisions must be clear and accountable.
Transitioning from manual operations to autonomy requires substantial investment in AI tools, infrastructure, and upskilling teams. Operators must also modernise outdated systems to be compatible with automation, all while maintaining service continuity. Balancing the upfront costs of this transformation with the long-term efficiencies and revenue opportunities it creates is a significant challenge.
While autonomy reduces the need for constant human intervention, oversight remains vital to ensure ethical, strategic, and operational alignment. Operators must establish transparent processes for monitoring AI-driven actions, intervening when necessary, and ensuring autonomous systems deliver on their intended goals. This is especially important for critical decisions impacting customer experience or regulatory compliance.
Strategic vs Tactical
There is a natural divide between strategic and tactical priorities in the differing focuses of a CTO and a Director of Network Operations. A CTO prioritises the long-term vision of building a future-ready, autonomous network, investing in innovation, and positioning the organisation for success in 2030 and beyond. Meanwhile, the Director of Network Operations is grounded in the immediate need to keep the network running smoothly, manage performance, resolve faults, and maintain service quality today. This highlights the importance of balancing ambitious transformation goals with the operational realities of daily network demands. For the business and the network to achieve autonomy as one, these roles must work in close alignment—ensuring that operational insights guide strategic investments in automation and AI. In contrast, operational priorities are shaped to support the broader vision of an autonomous and future-proof organisation.
|
Challenge |
Strategic Focus |
Tactical Focus |
|
Data Complexity |
Build scalable data platforms; invest in unifying disparate datasets. |
Optimise real-time data ingestion, reduce redundancy, and ensure data quality. |
|
Interoperability |
Roadmap for integrating legacy and next-gen systems; work with vendors supporting open standards. |
Address API integrations, wrap legacy systems, and ensure seamless data flows between old and new. |
|
Trust & Transparency |
Invest in explainable AI, ethical frameworks, and validation processes. |
Monitor and refine AI decisions; establish audit trails and real-time decision tracking. |
|
Cost of Transition |
Develop phased roadmaps and demonstrate ROI; align leadership to support transformation. |
Manage training, optimise current systems, and pilot cost-effective automation projects. |
|
Maintaining Oversight |
Embed human oversight into governance; define escalation paths and intervention points. |
Implement alert systems, monitor anomalies, and create playbooks for human intervention as needed. |
Why This Shift is Necessary
Embracing autonomy is a profound shift that directly impacts operators’ bottom lines. While challenging, modern networks require scalable solutions to manage growth and complexity in both the network and the offers without proportional cost increases.
Automation and autonomy enable operators to reduce manual effort, lower Mean Time to Repair (MTTR), and minimise service disruptions. These efficiencies translate into lower operational expenditure (OPEX), improved uptime, and greater customer satisfaction—key to retaining subscribers and reducing churn. In competitive markets, faster service deployment, optimised resources, and consistent quality give operators a significant edge. The return on investment makes this transition an imperative rather than a choice.
The Benefits of Autonomy
Automation eliminates manual processes, reducing costs and enabling teams to focus on strategic activities like planning and innovation. Routine tasks such as fault resolution, updates, and optimisation are handled faster and more accurately.
Real-time anomaly detection and predictive analytics address issues before they escalate, reducing downtime and improving network reliability. Faster resolution reduces MTTR and prevents service disruptions.
Consistent service quality and faster issue resolution improve satisfaction. Autonomous networks adapt to user needs, optimising performance for applications like streaming, gaming, or enterprise-critical services.
Autonomous systems scale to handle increasing demands from IoT, 5G, and edge computing without requiring proportional operational resources. Networks dynamically adjust to changes in traffic and application requirements.
Automation accelerates service deployment by removing bottlenecks in provisioning and configuration, enabling quicker responses to customer demands and new market opportunities.
Cost reductions from streamlined operations, better resource use, and fewer service disruptions improve OPEX. New revenue streams from advanced services, such as premium SLAs or private networks, enhance profitability.
Autonomous systems optimise energy use by adjusting power consumption to demand. Efficiency improvements reduce operational costs while supporting environmental goals.
Automation prepares operators for emerging technologies like intent-based networking and advanced IoT applications, ensuring networks remain agile and competitive.
What It Means for Customers
Autonomous networks promise more than reliability—they open new possibilities across diverse applications. Individual subscribers will benefit from ultra-reliable connectivity, faster issue resolution, and personalised services tailored to their usage. Whether streaming, gaming, or working remotely, users will experience seamless performance with networks that proactively optimise resources to meet their needs.
The impact will be transformative for enterprises, particularly those relying on private networks or mission-critical systems. Industries like manufacturing, logistics, healthcare, and transportation will benefit from networks that dynamically adjust to operational requirements. Autonomous systems enable real-time monitoring and troubleshooting, ensuring uninterrupted factory automation or smart port operations. Private networks will also leverage autonomy to enhance security and scalability, adapting to changing demands without manual intervention.
Autonomous networks will empower industries to innovate, enabling technologies like IoT, edge computing, and smart cities to thrive. Whether it’s predictive maintenance, optimised supply chains, or adaptive public safety systems, autonomy will reshape how networks serve industries and consumers. By driving reliability, responsiveness, and scalability, autonomous networks will meet today’s challenges and unlock the future’s potential.
This is Part 1 of a 3 in a series. Coming shortly:
Understanding the Role of AI in Autonomy
AI needs Service Assurance