Unlock the potential of AI in the telecommunications industry

This image portrays the integration of AI with telecommunication, highlighting the future possibilities and advancements in this field.

The telecommunications industry is facing unprecedented challenges as the global economy struggles with rising inflation and squeezed revenues. The pressure on telco budgetsparticularly on personnel costs, energy, external spending on services, leases, and capital expenditures, which equates to 60 percent of the telco spendingis putting a strain on the industry’s profitability. However, technology can offer a solution to these challenges. AI in particular has the potential to help telcos manage these difficulties by reducing costs, optimizing their networks, and improving customer experience.

With the global AI in telecom market projected to reach $38.8 billion by 2031¹, the significance of AI in the industry is hard to ignore. The rise of AI-enabled smartphones, the availability of on-demand hyper-scale computing and storage, and the development of large language models such as GPT-3 are leading the charge for this transformation. The time has come for telcos to seize this unique opportunity and harness the power of AI to remain competitive and stay ahead of the game.

In this blog, we delve into the role of AI in the telecom industry, examining its practical applications, and exploring the ways in which telcos can adopt and utilize AI to drive their businesses forward.

AI has the potential to improve various aspects of the telecommunication industry

The use of AI in customer service within the telecommunication industry can greatly improve the customer experience by automating routine tasks and freeing up human representatives to handle more complex inquiries. Call centers in the telecom industry are often overwhelmed by repetitive requestsleading to long wait times and ineffective customer service. In an industry where customer satisfaction is critical and the cost of customer acquisition is high, improving the customer experience is crucial.

AI-powered chatbots can provide instant, everyday support to customersreducing wait times and improving overall satisfaction. A recent study by TIDIO² suggests that AI-powered chatbots are gaining huge popularity and are set for big adoption in 2023 and beyond. The study found that about 88 percent of customers had at least one conversation with a chatbot within the past year and 62 percent of consumers would prefer to use a customer service bot rather than wait for human agents to answer their requests. Further, in 2022, the total cost savings from deploying chatbots reached around $11 billion, thus prompting a faster adoption of this technology by businesses of all sizes.

Conversational AI, in the form of chatbots, and voice AI powered by large language models, is quick, efficient, accurate, and real-time with its responses. Large language models like GPT-3 and its ChatGPT prompt-based interface can further improve the customer experience by providing human-like responses to customer inquiries. ChatGPT, for example, can understand the context of a customer’s query and provide accurate, relevant responses in real time. It has the ability to document, summarize, and index callsenabling quick and easy access to customer information. This can significantly improve the efficiency of customer service and provide customers with a more personalized experience.

Copilot in Dynamics 365 Customer Service, is another example of how AI empowers Telco customer service agents to deliver exceptional customer care. Dynamics 365 Copilot drafts contextual answers to queries in both chat and email, in addition to providing an interactive chat experience over knowledge bases and case history so this AI-powered expertise is always available to answer questions.

From faster customer query resolution to driving self-service payments to automated field visit bookings, the potential for AI-powered chatbots to enhance customer service in the telecommunication industry is huge.

One good example is Vodafone, which leveraged the power of Microsoft Azure AI services to create a conversational digital assistant named TOBi. This bot was specifically designed to cater to the needs of Vodafone customers and was rolled out to 16 markets in 15 different languages. With the help of Microsoft, Vodafone was able to provide fast, relevant, and engaging customer support, which has increased customer satisfaction and reduced operational costs. Currently, TOBi handles 25 to 30 million customer conversations each month and is expected to reach 500 million conversations in the coming years.

Network optimization and maintenance

The complexity of networks is projected to skyrocket in the next five years as the deployment of 5G technology gains momentum. According to Nokia, Network growth is expected to increase by a staggering 73 percent, outpacing the growth rate of the previous five years by a factor of five. Ericsson has reported that the implementation of AI-powered solutions in networks can lead to a 35 percent decrease in critical incidents and a 60 percent decrease in network performance problems. Additionally, energy costs can be reduced by 15 percent through the automation, making the network more environmentally sustainable.

AI can help telcos optimize their networks by automatically adjusting network settings and configurations to improve performance and reduce costs. AI algorithms can further be used to analyze vast amounts of data generated by telecommunication networks, providing valuable insights into network performance, and helping to identify and resolve issues in real-time. This can significantly improve network reliability and reduce downtime, ultimately leading to enhanced customer satisfaction.

Telcos like Ooredoo are already deploying Ericsson’s new optimization solution on Azure. This solution uses digital twin technology and advanced AI techniques, like deep reinforcement learning, to analyze the radio access network (RAN) to proactively provide mobile network optimization recommendations and resolve specific network performance issuesenabling a superior subscriber experience while reducing operating costs.

Fraud detection and prevention

The telecommunication industry is grappling with declining sales and rampant fraud, compounded by intense competition. Telecommunications fraud poses a significant risk to operators, businesses, and consumers alike. It has become a major pain point for the industry, leading to an astonishing USD39.9 billion in global telecom revenue loss in 2021, equating to 2.22 percent of the total revenue according to Communications Fraud Control Association (CFCA). Despite the growing threat of fraud, the adoption of AI, machine learning, and decision engine technology in fraud management in the sector is still limited. The reliance on manual processes remains a critical issueespecially in the wake of the shift to remote work and digital environmentsmaking it a vulnerable point in fraud management departments.

To address these challenges, AI algorithms can play a crucial role by analyzing massive amounts of data to detect and prevent various forms of fraudulent activities in real time, such as SIM-swapping, unauthorized network access, fake profiles, and bill fraud. Some of the practical examples of where AI can help are:

AI algorithms can detect and prevent SIM-swapping fraud by analyzing patterns in the usage of SIM cards, such as sudden changes in location, device type, and calling behavior.
AI models can detect and prevent unauthorized network access by monitoring network activity and identifying unusual patterns of usage that may indicate fraud.
AI can detect and prevent bill fraud by analyzing customer billing data, detecting unusual patterns and anomalies, and flagging any suspicious activity.

By incorporating these AI-powered solutions, telcos can enhance their fraud management capabilities, reduce fraud-related losses, and improve the overall customer experience.

AI can be enhanced further with biometric security solutions like Nuance Gatekeeper, which authenticates legitimate persons via their unique voice print and detects fraudsters wherever and however they engage. Telefnica leveraged Gatekeeper to ensure its most vulnerable customers could access the support they needed and fasttrack them to priority assistance.

Some of the other compelling AI use cases are:

Predictive maintenance: AI can analyze data from telecom equipment to predict when it will require maintenancereducing downtime and costs associated with maintenance.
Personalized marketing: AI can analyze customer data to create targeted marketing campaignsimproving customer engagement and reducing the costs associated with marketing efforts. Using machine learning models to recommend products or services to customers based on their usage patterns and preferences.
Automated decision making: Using deep learning models to automate decisions such as network routing, dynamic pricing, and more.

The potential for AI to revolutionize the telecommunications industry is immense. However, despite the numerous opportunities to leverage AI across the telco value chain, the adoption of AI by telecom companies has been slow and fragmented.

Challenges to AI adoption in the telecom industry

Telecom operators generate mass amounts of data and are in persistent need to reduce costs, this is where AI can help, yet, telcos are facing a number of challenges in scaling AI initiatives and realizing their full potential. Some of these challenges include a lack of the right skills and resources, unclear objectives for implementing AI, lack of data analysis, concerns about security, difficulty in integrating AI with existing systems, and a culture that is not conducive to innovation.

To overcome these challenges, telecom companies can take several steps to facilitate a successful AI adoption:

Setting clear goals and objectives for implementing AI.
Investing in training and hiring data science and AI experts.
Forming strategic partnerships with AI vendors and hyperscalers.
Taking the time now to invest in data infrastructure, as AI relies on good data to do its job.
Making AI a central component of product development and processes.
Establishing robust data privacy and security protocols.
Conducting pilot projectswith lower barriers firstto test the feasibility and benefits of AI and having a clear, scale-up plan in place.
Investing in change management strategies to help employees adapt to new technologies and processes and foster a culture of experimentation and learning. By involving employees in the implementation process and communicating the benefits of AI, companies can create a more open and accepting environment for new technologies.

The telecommunications industry is facing new challenges and increased pressure to maintain margins in the face of rising costs and economic uncertainty. However, adopting AI technology offers a solution to these challenges by providing a way to improve efficiency, reduce costs, and enhance the customer experience. AI has the potential to revolutionize the telecom industry, and there are numerous compelling use cases that can be leveraged to drive the adoption of AI in the industry.

Telcos have a unique opportunity to leverage AI to stay competitive in an increasingly challenging market. By investing in AI and adopting best practices, telcos can future-proof their operations and remain competitive in the years to come. As the field of AI continues to evolve, we can expect to see even more exciting and transformative developments in the telecommunications industry.

How can Microsoft help organizations navigate AI revolution?

Microsoft is committed to making the promise of AI real with advancements grounded in its mission to help every person on the planet to achieve more. Microsoft is focused on creating AI systems that help people solve real-world challenges.

Microsoft Azure AI is a collection of AI services offered by Microsoft as part of its Azure cloud platform. These services are designed to make it easy for developers and organizations to add AI capabilities to their applications, without requiring extensive expertise in AI. Microsoft Azure AI includes pre-built application programming interfaces (APIs) for natural language understanding, computer vision, and speech recognition, including models from partner OpenAI, as well as a cloud-based platform for building and deploying machine learning models.

These services are integrated with the Microsoft Azure platform, which provides capabilities such as scalability, security, and compliance, as well as a number of other tools and services that can be used to build and deploy AI-enabled applications. Microsoft Azure is currently the only global public cloud that offers AI supercomputers with massive scale-up and scale-out capabilities. With a unique architectural design that combines leading graphics processing unit (GPU) and networking solutions, Microsoft Azure delivers best-in-class performance and scale for the most compute-intensive AI training and inference workloads.

Microsoft Azure AI integration in AI Builder within the Microsoft Power Platform allows businesses and developers to quickly and easily build and deploy custom AI models, and to integrate them with Power Apps, Power Automate, and Power Virtual Agents, in order to add advanced capabilities and improve data management and security. It also allows us to easily scale up and improve the performance of the models, as well as easily integrate with other Microsoft Azure services.

Microsoft has adopted Azure AI across a wide range of its products and services, in order to improve functionality, performance, and user experience.

With Microsoft Azure OpenAI Service now generally available, businesses can access some of the most advanced AI models in the world, including GPT-3.5, Codex, and DALL-E 2, backed by the enterprise-grade capabilities and AI-optimized infrastructure of Microsoft Azure. The Microsoft Azure OpenAI Service will also provide access to ChatGPT, a fine-tuned version of GPT-3.5 that has been trained and runs inference on Microsoft Azure AI infrastructure soon.

GPT-4 is also available in preview in Azure OpenAI Service. While the recently announced new Bing and Microsoft 365 Copilot products are already powered by GPT-4, Azure OpenAI Service allows businesses to take advantage of the same underlying advanced models to build their own applications.

Microsoft recognizes the importance of responsible innovation in AI, especially with powerful new technologies like generative models. As such, Microsoft has taken an iterative approach to large models, working closely with OpenAI and customers to carefully assess use cases, learn, and address potential risks.