The objective is to explore the key trends that will be driving the adoption of AI in network infrastructure in 2024 and how they will shape the future of telecom.
Of all the trends taking place in communications and IT infrastructure and the cloud in 2024, there are none that loom as large as artificial intelligence (AI). The role of AI in network infrastructure is becoming all the more crucial as the years go by. It is going to continue to be an arena that both companies and individuals will need to pay attention to this year, especially if they want to stay competitive. With the increased adoption of 5G networks, the speedy growth of cellular data, and with 6G potentially right around the corner, AI is all set to revolutionise the way and methods in which network operators optimise and manage their IT systems and infrastructure. AI is all set to particularly have an impact in the networking markets, affecting how infrastructure will be designed and built to support AI-enabled applications. In this article, we will delve into the world where networking infrastructure and AI intersect. Th objective is to explore the key trends that will be driving the adoption of AI in network infrastructure in 2024 and how they will shape the future of telecom.
Security and Automation through AI
AI is also playing an increasingly important role in fortifying network security by automating network processes. Due to a myriad of virtualised network functions and endpoint devices, there is no doubt that network architecture is becoming increasingly heterogenous and complex.
In this case, AI solutions are indispensable for efficient network maintenance, monitoring, and configuration. AI algorithms can autonomously and dynamically detect anomalies by analysing network logs and trigger corrective actions, thus reducing the need for manual human intervention. Moreover, AI-powered security solutions can employ techniques such as machine learning-based threat intelligence, anomaly detection, and behavioural analytics to help identify and respond to potential threats in real-time. Furthermore, AI can facilitate forensic investigations, enforce security policies, and detect and isolate malicious activities by monitoring user behaviour and network traffic continuously, thus strengthening the network’s overall security posture.
Network Performance Optimisation
One of the most significant and rather critical benefits of incorporating AI into network infrastructure is due to its ability to optimise network performance. Improving enterprise network connectivity and performance is one of the most critical ways in which businesses can stay ahead of the competition. As cellular data traffic surges day by day, network operators are looking to leverage AI algorithms to analyse network traffic patterns and help them make real-time decisions for load balancing and routing.
By employing techniques such as deep learning and machine learning, AI can predict potential bottlenecks and holdups, identify optimal network configurations, and actively allocate resources for mitigating network congestion, thus also minimising latency. This proactive approach to network management will not only reduce service disruptions and prevent outages, but also greatly enhance the overall QoS (quality of service) for end-users.
The Rise of AI Affordability and Edge Computing
The proliferation of edge computing is another important trend that has catalysed AI adoption in network infrastructure. By pushing data storage and computation closer to the network edge, edge computing decreases the bandwidth constraints and latency associated with centralised cloud processing. This decentralised architecture greatly benefits AI applications that require low-latency responses and real-time processing, such as augmented reality, industrial automation, and autonomous vehicles. Network operators can improve the resilience and scalability of AI-powered services, reduce data transmission costs, and ensure faster decision-making by deploying AI models at the edge. At the same time, they will also be addressing the growing concern from end users as to how their data is being used and stored.
Going further, the increasing accessibility and declining costs of AI solutions are further driving their adoption in network infrastructure. The emergence of AI-as-a-Service (AIaaS) platforms, proliferation of open-source AI frameworks, and advancements in GPU technology are democratising AI and making it more accessible and affordable to all kinds and sizes of network operators. This democratisation of AI has been fostering innovation and allowing operators to leverage AI capabilities without any significant upfront investments in expertise and infrastructure.
AI for Multi-cloud
Last but not least, AI is also set to fuel the growing need for multi-cloud networking. Since a lot more data will be shuttled between clouds for collection, organisation, and analysis, it will also mean more data collection at the edge. With AI, networking companies targeting apps and data at the edge will benefit from the need for secure connectivity.
Global spending on AI for network orchestration is expected to increase from USD 6 billion in 2024 to a whopping USD 20 billion by 2028, which is a stupendous 240% increase. With 5G networks maturing and 6G networks starting to materialise, AI will be instrumental in managing the explosive growth of cellular data traffic, edge computing deployments, and increasing complexity of virtualised network functions. All in all, artificial intelligence is all poised to revolutionise the network infrastructure landscape will assist network operators in delivering better customer experiences and unlocking newer revenue streams in the age of 5G and beyond.
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