Generative AI: Transforming the telecoms landscape and driving innovation

Over the last few years, telecommunications operators have been at the centre of industry-wide disruption that shows no signs of slowing. From stagnating revenues and the ever-increasing strain on networks - resulting from the relentless demands of 5G – to the ongoing pressure and challenges to deliver exceptional and innovative customer experiences - communications service providers (CSPs) have reached a pivotal juncture.

While the lion’s share of an operator’s budget has and continues to be spent on infrastructure and data management, the integration of artificial intelligence (AI) into the operations of telecom providers has led to groundbreaking changes across the landscape. With the introduction of generative AI (GenAI), this cutting-edge technology has the potential to revolutionise the telco industry – changing the way we communicate, reshaping the way services are provided, optimising network performance, improving how networks are managed, and enhancing the customer experience.

Showing great potential across industries and functions, GenAI is a type of AI. Whereas AI uses algorithms to analyse data and make decisions based on the inputted data, the abilities of GenAI are widespread, providing for new opportunities to innovate. GenAI uses a variety of prompts (existing text, audio, or images), as well as neural networks to identify patterns in existing data to create new content such as text, images, videos, sounds, code, 3D designs, and other media. This technology “learns” based on existing material and continues to evolve as more data is provided, enabling it to perform creative tasks and predict outcomes in much the same way as a human.

GenAI is pivotal to telecom transformation

Increasingly becoming a boardroom agenda item, GenAI is accelerating transformation across industries, and CSPs are no exception. A survey, conducted by Capgemini Research Institute, found that telecom company leaders are strong advocates of GenAI (96 per cent of respondents). The report, Harnessing the value of generative AI: Top use cases across industries, also uncovered that 69 per cent of telecom executives believe that the benefits of using GenAI outweigh associated risks, and only 12 per cent believe GenAI will significantly disrupt their industry.

Although not known to pioneer new technologies, nearly half of telecom executive respondents currently have ongoing GenAI pilots. Among these telcos, 36 per cent have a dedicated team and budget, and nearly half (47 per cent) have started to explore GenAI’s capabilities and functions. Among large telecom companies, 71 per cent of the surveyed respondents are using or are planning to use GenAI for IT functions. While GenAI has applications across different functions, exploration of use cases differs between industries.

Top GenAI use cases for telecommunications providers

One of the most significant ways GenAI is transforming the telecom industry is by improving network performance. Its ability to optimise networks and make them more efficient provides the opportunity for networks to provide faster speeds, improve reliability, and reduce costs. GenAI also provides the potential to improve the customer experience. By creating virtual assistants that can quickly and accurately respond to customer questions and provide support, telcos will have the ability to greatly enhance customer experiences. One of CSPs key use cases, Capgemini’s research uncovered that 36 per cent of telco respondents are piloting call centre analytics and two per cent have already implemented GenAI-based call centre analytics. Other telecom GenAI use cases include:

Co-pilots for fraud management and business assurance: By analysing data for anomalies, patterns, and compliance, GenAI can aid telcos in fraud management and business assurance. GenAI can ensure real-time monitoring, issue alerts, and enhance efficiency, reducing false positives. Given its 24/7 vigilance and collaboration with human experts, telcos will be able to optimise fraud prevention, improve regulatory adherence, and enhance service quality, improving the operator’s integrity and customer trust.

Enhanced customer experience: Using AI chatbots and virtual assistants, customers will receive 24/7 personalised interactions and services that are tailored to individual preferences. GenAI will ensure that responses are precise and provided in natural language, boosting customer engagement and loyalty.

Network optimisation and management: With the proliferation of devices and the demand for high-speed, low-latency connectivity, telecom networks have become increasingly complex. GenAI algorithms can analyse vast amounts of data to predict network congestion, optimise routing, and enhance overall network performance. By constantly adapting to changing conditions, GenAI can ensure seamless connectivity and improve end user quality of service.

Predictive maintenance: By offering predictive capabilities, GenAI enables CSPs to anticipate equipment failures before they occur so that proactive measures can be taken. It accomplishes this by analysing historical and real-time data, reducing downtime, decreasing costs, and improving maintenance efficiency.

Network security and fraud detection: Given the vast amounts of sensitive data that telecom networks handle, security is a top concern across the industry. GenAI can detect anomalies in network traffic, identify fraud-like SIM card cloning, and expose unauthorised billing, enabling CSPs to proactively counter security threats.

Content generation and advertising: Telecom operators can use GenAI to create personalised marketing content based on user preferences and behaviours. This level of automated customisation – across web and social content creation – enhances the effectiveness of advertising campaigns for improved customer engagements and decreases the number of resources needed for these tasks.

The future of telecom providers lies in GenAI

As GenAI matures, it will continue to be a catalyst for change – driving innovative use cases such as automating the generation, debugging, and testing of code, as well as enabling humans to self-generate new content. Not mutually exclusive, traditional AI and GenAI each have unique roles; however, when used in tandem their power becomes exponentially greater. For instance, traditional AI excels at analysing data and making predictions, whereas GenAI uses its training data to create something new – providing telcos with new avenues for innovation, productivity improvements, and efficiency enhancements.

Harsha is responsible for steering the strategic direction of the company. His responsibilities encompass shaping corporate initiatives, developing and executing growth strategies, portfolio transformation and fostering innovation within our technology landscape. He runs the AI business of Subex driving the strategy & roadmaps across Conventional and Generative AI applications. Harsha comes aboard with a wealth of entrepreneurial leadership and strategic insight.