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In today’s rapidly evolving digital landscape, telecom networks are undergoing a profound transformation, with Artificial Intelligence (AI) emerging as a pivotal driver of innovation and efficiency. Telecom service providers possess a vast reservoir of data—an untapped resource with immense potential to become a strategic asset. By leveraging AI and Machine Learning (ML), these networks are poised to revolutionise their operations, from network design and deployment to optimisation, predictive maintenance, and energy efficiency enhancements tailored to dynamic traffic patterns.
AI also has the potential to elevate telecom networks to comprehensive platforms that will drive the next wave of technological innovation. Beyond networks, AI is also set to power advanced use cases, further unlocking value across sectors. A deeper exploration of these transformations reveals how AI is shaping the future of telecom and industrial applications.
Network Optimisation and Automation
AI and ML are revolutionising network planning and driving automation by abstracting network complexities.
Network planning and optimisation: AI can process vast data to enhance network coverage, detect interference, and identify anomalies with unprecedented precision. This intelligent approach enables telecom providers to create more robust, efficient network architectures. According to a Nokia Bell Labs report, AI can boost productivity by 17% to 24% for network planning and optimisation.
Autonomous network management: End-to-end network automation is no longer a future concept but an emerging reality. AI enables dynamic adaptation of network and cloud resources, allowing rapid service deployment and failure mitigation while significantly reducing operational expenditures.
AI-driven networks can boost productivity by up to 40%, transforming telecom operations with smarter automation and customer-centric solutions.
Enhanced user experience and security: While AI can transform user interactions and network security, real-time AI-powered solutions can detect and mitigate security risks, identify abnormal network behaviours, and protect sensitive customer data. It can also add device-level intelligence since advanced AI applications like facial recognition can help improve device security and operational ease.
Customer care and operations: AI presents a transformative opportunity for customer care and operations, enabling organisations to enhance customer experience and reduce operating expenses simultaneously. The Nokia Bell Labs report indicates that telecom companies can expect a productivity increase between 25% and 40% with AI.
Emergence of AI-RAN: The convergence of AI, accelerated computing, and Radio Access Network (RAN) technologies is giving birth to AI-RAN. This powerful new paradigm promises to revolutionise network performance. AI-RAN can leverage billions of data points to develop optimal network adjustment algorithms. It can also help predict real-time capacity requirements and enhance user experiences for emerging technologies like augmented reality and high-bandwidth applications.
Energy efficiency and sustainability: Up to 80% of a mobile network’s energy is consumed by base station sites. Mobile operators face an overall increase of 10%–30% annually in mobile network energy use. Managing energy efficiency is necessary to control costs while maintaining the service level that end users expect. AI can play a crucial role in optimising energy consumption, enabling dynamic energy savings based on network traffic and user experience without compromising service quality.
Benefits Beyond Connectivity
AI in telecom networks is not just about connectivity. It is also about enabling transformative solutions across critical sectors.
Smart and sustainable farming: AI-powered telecom networks are transforming agriculture with real-time crop monitoring, precision resource management, and reduced pesticide and water use. For instance, AeroFarms, a global leader in vertical farming, has set up a private 5G network to enable drone-mounted cameras to transmit detailed crop images. By leveraging AI, they analyse and track plant interactions and variations, showcasing how the technology can directly enhance food production.
Personalised and proactive healthcare: The convergence of AI, IoT, and telecommunications is transforming healthcare delivery by enabling personalised and proactive healthcare solutions. Advanced wearable technologies can facilitate remote patient monitoring, while AI-powered predictive analytics provide personalised interventions tailored to individual needs. Real-time health data collection and analysis can further enhance the ability to deliver targeted and efficient healthcare services.
Intelligent industrial ecosystems: AI-driven future networks can help unlock intelligent industrial ecosystems with transformative capabilities. These include the creation of highly detailed digital twins of physical environments, enabling remote interaction with machines and robots, and capturing human gestures to translate them into precise machine actions. Enhanced industrial automation and control mechanisms are also advancing the development of sophisticated digital twin technologies, paving the way for a new era of industrial innovation.
As the journey towards 5G-Advanced and 6G unfolds, AI is well-positioned to be the cornerstone of distributed intelligence, seamlessly integrating devices and network edges. This progression will unlock immersive experiences, unparalleled connectivity, and groundbreaking technological possibilities.
Telecom service providers that embrace AI will not just enhance their networks–they will play a catalyst role in driving the digital transformation that will define the next decade, paving the way for innovation across industries.
By Tarun Chhabra
The author is Senior Vice President and Country Head of Nokia India.
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