As an example, mobile network operators are increasing their investment in big data analytics and machine learning technologies as they transform into digital application developers and cognitive service providers.

With a long history of handling huge datasets, and with their path now led by the IT ecosystem, mobile operators will devote more than $50 billion to big data analytics and machine learning technologies through 2021, according to the latest global market study by ABI Research.

Cognitive technologies market development

"Machine learning-based predictive analytics are applicable to all aspects of the telecom business," said Joe Hoffman, vice president at ABI Research. "It's important that operators master and internalise these technologies and not rely solely on their vendors’ expertise. Executives that overlook big data and machine learning risk irrelevance."

Machine learning can deliver benefits across telecom provider operations with financially-oriented applications - including fraud mitigation and revenue assurance - which currently make the most compelling use cases.

Legacy analytics are rule-based solutions that cannot keep pace with the criminal element, but machine learning excels at spotting trending anomalies, according to the ABI analyst assessment.

Predictive machine learning applications for network performance optimization and real-time management will introduce more automation and efficient resource utilization.

Telecom big data solutions include the commercial IT infrastructure, such as the open source, Java-based Hadoop ecosystem, SQL/NoSQL data management, and associated orchestration platforms.

Outlook for IT infrastructure investment

Spending on this infrastructure will exceed $7 billion in 2021. But the greatest benefits are from using predictive analytics to improve telecom business performance, with machine-learning-based predictive analytics to grow at nearly 50% CAGR and reach $12 billion through 2021.

"These are exciting times for mobile broadband as we see the convergence of IT and telecom, virtualisation with SDN or NFV, the adoption of artificial intelligence machine learning, and the ubiquitous coverage of all-IP 4G and 5G networks," concludes Hoffman.

Aided by cloud computing infrastructure and machine learning, mobile service providers can become a data-driven business that's accelerated via DevOps and automated processes. In a few years, mobile networks will transform into supercomputer hubs with cellular radios attached, continuously re-engineered for optimal performance.

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