This article was written in collaboration with Santeri Jussila, Head of Analytics Product Line Management at Nokia.
The global artificial intelligence (AI) market is booming. Market research firm Tractica estimates annual global AI revenue to grow from $9.5 billion in 2018 to $118.6 billion by 2025. For industries that capture and store vast volumes of data sets, AI can unlock new sources of growth opportunities, and reduce operating costs.
The telecommunications industry is keen to harness the potential of AI. Not only are they accustomed to large volumes of data – which both AI and machine learning (ML) require – telcos automate systems, processes and networks. By injecting AI into their systems, telcos benefit from ML feedback loops that further improve automated processes.
For telecommunications companies across the globe, AI is a game changer. Let’s look at three ways telcos can leverage AI:
1 Improve data-capture processes to achieve real-time insights
AI is powered by complex algorithms that require vast amounts of high-quality data to operate effectively. Telcos have access to large amounts data but it is often inconsistent, and/or fragmented. Much of this fragmentation is due to the legacy methods used in historical data capture. For many telcos, this can stall an AI project before it begins.
Nevertheless, the lack of perfectly clean data lakes should not preclude AI implementation, but instead, motivate telcos to adopt a more agile approach to harness the powers of AI.
Over time, telcos will need to clean and label historic data sets and identify gaps where data was not captured at the right level of granularity required by ML. Telcos must, therefore, improve and advance real-time data capture processes and determine which data sets are fed into the ML models. By improving the quality of real-time data used by AI algorithms, telcos can automate decisions quickly, and with a higher degree of confidence.
2 Need to work in an agile and iterative manner
AI capabilities are developing quickly and many telcos need to consider how to work in an agile and iterative manner to innovate and incubate new solutions beyond the traditional use cases. Strong collaboration between telcos and leading analytics vendors is needed to achieve common goals and interests.
Cleaned and labelled data is a valuable asset when the teams select specific data sets for training and tuning the AI models. It is key to introduce new capabilities into production as soon as possible. In order to make this possible, a strong data processing and analytics framework is needed to enable large scale experiments and high reliability in production use.
3 Reduce 5G operating costs, provide new applications and services
Telcos operate in a capital-intensive industry with high fixed costs and are constantly looking for solutions to control operating expenses. All the while, they must allocate significant financial investments now, to profitably manage and operate the next generation of 5G IoT networks in the not-so-distant future.
The rollout of 5G, and the resulting operating, monitoring and management costs of 5G networks, can be largely automated through AI. By analyzing 5G data sets in real-time, AI can reduce costs by proactively boosting network efficiencies and performance without human intervention. Furthermore, AI provides telcos opportunities for new applications and services such as customer service virtual assistants, intelligent customer relationship management (CRM) systems, real-time cybersecurity and targeted marketing.
5G networks will undoubtedly require significant investment in AI software, hardware and services to build a backend infrastructure that can analyze massive data sets. Telcos must also invest heavily in people with the right skill set in AI implementation and management to mitigate the current in-house skill gap. Tractica forecasts that global telecommunications industry investment in AI solutions will reach $36.7 billion annually by 2025.
The future of telcos is AI
The telecom industry is fertile ground for AI solutions such as machine learning, deep learning, natural language processing and machine reasoning. These applications will lower costs and boost efficiencies through automation. By analyzing vast volumes of data lakes in real-time, AI will revolutionize telcos as we migrate to 5G IoT future – where everything connects to the internet.