From voice calls to internet access, the telecom industry represents the cornerstone of communication in today’s always-on world. However, as the demand for faster, more reliable services grows, communication service providers (CSPs) need help meeting these expectations, particularly while trying to recoup the costs of 5G network rollouts.
Operational challenges are familiar to the telecom industry. Network congestion, high levels of competition, customer churn, and pressure to innovate are just some of the issues faced daily. These problems have typically been approached using manual intervention and rule-based systems, but these methods often fail to offer sustainable solutions to complex problems.
As we are seeing in so many industries around the world, the application of AI has the power to reshape the telecom landscape in profound ways to help CSPs unlock new insights, optimise operations, and enhance the overall customer experience. While there are some associated challenges with AI adoption, its ability to identify insights, patterns, and predictions from huge amounts of data, achieve high levels of automation, and even interact with humans using natural language processing can all help transform telecom operations with great potential for service providers.
Operational Optimisation
AI algorithms are worth their weight in gold for recognising and resolving issues based on network data to maximise performance and ensure efficiency across the board. By analysing traffic patterns, usage data, and network demand, for example, resource allocation of bandwidth, spectrum, and infrastructure investments can all be optimised for effective utilisation. AI-powered systems can automatically detect network faults and anomalies, diagnose the root causes, and suggest or implement corrective actions in real time. By analysing historical data, sensor data, and other relevant parameters, AI can proactively predict equipment failures before they occur, enabling pre-emptive maintenance. The result? More cost effective maintenance strategies, reduced repair time, minimised service disruption and improved network reliability for a better customer experience.
A Guide for Strategic Decision-Making
From a less technical standpoint, AI algorithms can also be harnessed to analyse market trends, competitor strategies, and customer behaviour to guide strategic decision-making. This includes predicting demand for new services, identifying potential revenue opportunities, and augmenting marketing campaigns.
Indeed, generative AI can significantly enhance telcos’ ability to target niche markets through more precise and personalised strategies. AI models allow the analysis of vast amounts of data across the network, BSS applications or any digital channel to gain deeper insights into specific niche segments’ preferences, behaviours, and needs. Workflow-based decision rulesets can automatically detect particular trends and use cases to trigger the right action at the right time with personalised customer engagement, targeted campaigns, loyalty incentives, and tailor-made propositions.
This level of personalisation humanises the conversation and improves customer experience and brand perception, ultimately increasing customer loyalty, reducing churn and boosting average revenue per user (ARPU). By understanding the customer and what they’re doing in more detail, the AI can present them with opportunities – whether a cheap coffee in a nearby shop or the best service bolt-on based on user activity. This data-driven approach enables telcos to orchestrate their products, services, and marketing campaigns with a higher degree of accuracy, resonating more effectively with the unique requirements of niche markets.
Enhanced Customer Experience
AI also has the power to enhance the customer experience in several ways. While billing and fraud aren’t always top of mind when it comes to customer experience, service providers soon know about them when something goes wrong. AI can be used to analyse telecom billing data to identify errors and anomalies and optimise pricing plans based on individual customer usage patterns. This helps reduce revenue leakage and improve overall billing accuracy, which can only enhance the customer experience.
Similarly, when it comes to fraud, AI and machine learning can be used to develop predictive models, assess susceptibility, and instantly react to fraudulent activity, safeguarding both customers and the network. By leveraging AI across billing and fraud, telcos can promptly identify and neutralise threats, enhance efficiency, protect revenues and improve customer experience, ultimately saving on infrastructure and operations costs.
Gen AI, epitomised by language models like ChatGPT, also has the potential to revolutionise the customer service landscape for telcos and service providers. By integrating these advanced models into existing BSS systems, CRM and chatbots, telcos can provide customers with immediate, detailed responses imbued with a uniquely conversational touch. Incorporating specific tones, writing styles, and messaging ensures accurate information delivery and fosters a distinct brand identity, elevating the overall customer experience and strengthening brand loyalty in a competitive market. This not only improves customer satisfaction but also reduces the human workload.
Challenges of AI Implementation
While the promise of AI in telecoms is undeniable, its implementation is not without challenges. Central to the discussion of GenAI usage in customer service is whether brands should be required to openly disclose how they use customer data, whether customers should have the right to access and review the data collected about them, and whether consent is needed before using data for AI applications. Moving forward, it will be essential to establish clear boundaries so that there is a thorough understanding of why something happens, whether it should have happened, and the potential consequences of that automated action.
Integrating AI into existing systems and workflows requires careful planning and strategic investment. Organisations need to find skilled AI talent to ensure successful implementation or re-skill existing employees. However, with the right approach and mindset, these challenges can be overcome, paving the way for a more AI-driven future in telecom.
Unlocking New Opportunities
AI can unlock new opportunities for telcos, from driving operational efficiencies and delivering superior services to their customers. As AI technologies continue to advance and mature, we can expect to see even more significant innovations and disruptions in the industry. From autonomous network management to personalised customer experiences, the possibilities are endless. While challenges remain, the potential benefits far outweigh the risks. Telecom companies, including MNOs and MVNOs, must stay informed and proactive when embracing AI-driven innovations to remain competitive in the ever-evolving landscape. If they do then they can embrace the transformative potential of this technology and chart a course towards a brighter tomorrow.
About the Author
Kelvin Chaffer is Chief Executive Officer at Lifecycle Software. With a software engineering background and an ever-growing passion for technology, Kelvin is known for driving growth and innovation in the product portfolio. Kelvin has worked at Lifecycle for 20 years using his positive attitude and tireless energy to inspire and lead the team. In his spare time, he runs ultra marathons.