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Empowering networks to think and adapt
Voice and Data|January 2025
Networks are leveraging Al and automation to simplify telecom complexities, enabling seamless operations and transformative efficiency
- BY SUDAKSHINA LAHA
Empowering networks to think and adapt

Autonomous networks represent a transformative approach to achieving self-managed, self-configurable, and self-optimising systems. As defined by TM Forum, they leverage real-time data to make self-adjusting predictions and implement network changes, constantly striving to achieve the intended state of the network while aligning with business objectives.

Autonomous operations, on the other hand, extend this concept beyond networks to encompass a broader operational model. They involve using autonomous systems to perform tasks with minimal human intervention, automating the capabilities for learning, self-governance, and adaptation across an organisation's value streams. These operations aim to deliver stakeholder value in a seamless, closed-loop manner.

Such advancements rely on a structured framework built on cutting-edge technologies like Artificial Intelligence (AI), Machine Learning (ML), and advanced automation techniques. These technologies are applied to optimise network flows, manage network element actions, and streamline complex business and service delivery processes or tasks. Together, they lay the foundation for a future of intelligent, adaptive, and efficient operations.

AUTONOMOUS SOLUTIONS:

FUTURE OF TELECOM?

The telecom and associated industry verticals are witnessing unprecedented market growth, driven by surging demand for the Internet of Things (IoT) connectivity, extensive deployment of 5G, advanced and private 5G networks, and diverse macro and enterprise use cases. Emerging trends such as network slicing, zero trust security systems, network API exposure, extended reality applications, and the push for energy efficiency are accelerating the demand for innovative use cases.

This story is from the January 2025 edition of Voice and Data.

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This story is from the January 2025 edition of Voice and Data.

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