By Vikram Meghal, SVP and Global Head of Engineering – Networks, Communications, Media, and Technology, Infosys
The telecommunications industry is on the cusp of a revolutionary transformation, driven by the integration of AI into network infrastructure. Traditional telecommunications networks, or “smart pipes”, were designed primarily for efficient data transmission. The focus was primarily on bandwidth, reliability, and cost-effectiveness, with limited intelligence embedded within the infrastructure. While they were effective for traditional voice and data services, smart pipes became a bottleneck as the demands of modern applications—streaming, gaming, IoT, and augmented reality—outpaced their capabilities. This underscored the need for networks that could do more than transmit data: networks that could think, learn, adapt, and respond.
Smart platforms, powered by AI are intelligent systems capable of real-time decision-making and optimisation. This evolution signifies a shift from passive data handling to proactive network management, where AI algorithms analyse vast amounts of signals to enhance performance and user experience.
One of the key technologies shaping this evolution is Agentic AI, which powers autonomous systems with self-healing, predictive maintenance, real-time threat mitigation, and seamless resource optimisation. The integration of 5G technology further enhances these platforms by enabling low-latency, high-capacity connectivity for real-time performance. Additionally, IoT connectivity will rely on AI to manage the massive data generated by interconnected devices, streamlining communication and operational efficiency across industries, transforming networks into proactive, user-centric ecosystems.
Advantages of smart platforms
Dynamic traffic management: AI algorithms can monitor network traffic in real time, identifying patterns and anomalies that may indicate congestion or potential failures. By predicting traffic loads and adjusting resource allocation accordingly, networks can maintain optimal performance levels without human intervention.
Predictive maintenance: Through advanced analytics, AI can forecast equipment failures before they occur. By leveraging historical performance data, telecom operators can proactively schedule maintenance, thereby minimising downtime and enhancing service reliability.
Resource optimisation: AI enables telecom companies to allocate resources more effectively by analysing usage patterns and predicting future demands. This not only minimises wastage but also enhances the overall efficiency of network operations. For instance, in 5G networks, AI can dynamically manage spectrum usage, allocate bandwidth for critical applications, and ensure energy-efficient operation.
Enhanced customer experience: By utilising AI-driven insights, telecom providers can offer personalised services tailored to individual customer preferences. Whether it’s tailored data plans or real-time assistance through AI-powered context aware chatbots, the focus shifts to creating meaningful and engaging user experiences.
Enhanced security: AI-powered security systems can detect and respond to cyber threats in real time, protecting networks and user data from malicious attacks.
Impact on the telecommunications industry
The shift to smart platforms is not merely an upgrade in technology—it represents a fundamental reimagining of business models in telecommunications.
- Operational efficiency
Automation, together with AI-aided decision-making, can lead to a significant reduction in operational costs and improvement in service quality. Tasks like fault detection, network configuration, and capacity planning are streamlined, allowing human resources to focus on strategic innovation.
- New revenue streams
With smart platforms, telecom operators can offer platform-as-a-service (PaaS) solutions to businesses, enabling applications like smart cities, autonomous vehicles, and industrial IoT. These partnerships unlock new markets and revenue opportunities.
- Improved scalability
AI-powered networks are inherently scalable, capable of adapting to the explosive growth of connected devices and data traffic in a hyper-connected world.
- Service innovation: The integration of AI into telecommunications infrastructure opens new avenues for service innovation. Companies can develop new business models based on real-time analytics and adaptive service delivery, positioning themselves competitively in a rapidly evolving market.
Challenges ahead
Despite the promising outlook for AI-driven smart platforms in telecommunications, some challenges remain:
- Data Privacy and Security Concerns: As networks collect and analyse vast amounts of data, ensuring user privacy and compliance with regulations like the EU AI Act assumes paramount importance. AI systems must be designed with strong security protocols and guardrails to protect against sophisticated cyber threats.
- Integration Complexities: Merging AI technologies with existing systems requires careful planning and execution to avoid disruptions during the transition phase.
As telecommunications continue to evolve, the next frontier lies in fully autonomous networks. These self-healing, self-optimising systems will integrate AI and Machine Learning and operate with minimal human intervention. Future networks will also incorporate edge computing and quantum communication, pushing the boundaries of speed and intelligence.