Cloudera urges telcos to invest in AI or risk falling behind
Use cases for artificial intelligence in telecommunications are broad, such as predictive maintenance, automated anomaly detection, real-time network optimisation, and proactive service delivery. However, Anthony Behan, Global Managing Director, Communications, Media & Entertainment at Cloudera, says a lack of modernised data infrastructure could see organisations struggle to keep pace in a market experiencing sluggish growth.
Cloudera works with 80 of the world's top 100 telecom providers and reports that telcos are under increasing pressure to reduce costs, modernise infrastructure, and deliver better customer experiences, all while transforming their networks to meet new demands. The company stresses that scalable AI cannot happen without unified, reliable data; without AI, Behan warns, telcos could lose ground to competitors. "Telcos are drowning in vast volumes of operational and telemetry data – yet they can't act on it effectively," says Anthony Behan, Global Managing Director, Communications, Media & Entertainment at Cloudera.
Behan further highlights, "Regulatory compliance, cyber threats, and the slow pace of network virtualisation show just how overstretched networks already are. AI can really help, and the problem isn't a lack of data – it's that it's siloed, unstructured, and untrusted. Without strong data foundations, telcos can't scale AI."
Cloudera has recently joined the AI-RAN Alliance, a coalition including global companies such as Dell, NVIDIA, SoftBank, and T-Mobile, aiming to advance the integration of AI in developing telecommunications infrastructure.
Behan notes the importance of scaling AI applications, stating, "The next phase of AI will be about scale and production. Private AI allows for that kind of automation in the network, at carrier scale."
Barriers to adoption
Data across telecommunications networks is often siloed and managed through disparate systems, creating significant hurdles for organisations wanting to deploy AI at scale. Cloudera's advice to telecom operators includes supporting hybrid workload mobility across both cloud and on-premises environments via Private AI; establishing unified data governance covering both data platform domains and BSS/OSS stacks; allowing AI workloads to be trained on-premises and deployed either in the cloud or directly in the network; and reducing vendor lock-in by running workloads where it makes the most business sense.
Recent research from Cloudera shows that AI is already being utilised in some areas within telecommunications, including customer service (49%), experience management (44%), and security monitoring (49%). However, Cloudera points out that extending the benefits of AI to more advanced network functions such as predictive maintenance and real-time optimisation will depend on a scalable data and AI infrastructure.
AI-native opportunities
With improved data foundations, networks could unlock AI's greater potential, including automation of operations, performance gains for 5G and edge, and development of new revenue streams such as smart city solutions and support for autonomous technologies.
Looking ahead, Behan outlines his vision for the future of telecom networks: "If I could wave a magic wand and build the ideal telecom network, it would have GPUs in every base station and use AI not just for communication, but for distributed, sovereign, local intelligence. That's where Private AI comes in - you can't run everything in the public cloud, especially with sensitive data. You need on-premises capabilities for control and security, but also the flexibility to use the cloud where it makes sense. The network would be highly secure, fast, and elastic – capable of spinning up virtual resources automatically to handle congestion or block fraud in real time. While this vision is still perhaps five to ten years away telcos must begin laying the groundwork now. More investment and experimentation are needed today to realise the network of tomorrow."
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