Artificial intelligence in telecom

Main article: Artificial Intelligence

• Global Telecom Trends
• Telecommunications Services (Global Market)

History

2024

The volume of the global AI market in the telecom sector for the year reached $3.34 billion

In 2024, the cost of artificial intelligence technologies in the telecommunications sector amounted to $3.34 billion. Approximately 27% of global spending was in the North American region. Such data are provided in the Fortune Business Insights review published on April 30, 2025.

Using AI and machine learning algorithms, operators optimize network performance, automate routine tasks and personalize customer interactions. In particular, AI can be used to automatically detect failures, manage traffic and resources. Such algorithms allow real-time load estimation and appropriate redistribution of data streams to maximize efficiency. In addition, AI is able to predict possible equipment failures, allowing operators to take the necessary measures in advance to prevent problems.

AI systems can analyze the behavior and profile of subscribers to determine their needs. Using habits and preferences data, AI forms personalized service schemes. This helps operators increase revenue per user. In addition, AI systems analyze information about demand and market trends, which helps in optimizing business operations. For example, AI helps providers predict demand for services at different times of the day or in different geographical areas. Telecommunications companies are implementing generative AI to estimate costs and ROI times.

AI-based chatbots are actively used in customer support services. Such systems are increasingly complex and functional: they understand natural language and context, and provide real-time answers. AI bots reduce the burden on call centers employees and allow you to solve certain issues in a fully automatic mode - without involving operators. As a result, companies are able to improve user support, which increases customer satisfaction and helps to retain them.

One of the restraining factors of analysts is the issues related to the confidentiality and protection of personal data. Huge amounts of subscriber information pass through AI systems, which raises concerns about leaks and potential misuse of personal information. There is also a shortage of qualified specialists in the field of AI.

According to the deployment model, the market is segmented into local and cloud solutions. The former hold the largest share due to the need to ensure data protection and control over the infrastructure. At the same time, cloud systems show higher growth rates due to availability, scalability, flexibility and cost-effectiveness. In terms of the application of tools, machine learning, natural language processing, working with big data, etc. are distinguished. In 2024, the big data sector accounted for more than half of the costs - 53%. Geographically, North America was leading with costs of $0.9 billion. Globally, significant players are named:

• Infosys Limited;
• IBM;
• Cisco;
• Telefonaktiebolaget LM Ericsson;
• Nokia;
• Intel;
• Alphabet;
• Nuance Communications;
• Nvidia;
• AT&T.

In 2025, AI spending in the telecom sector is expected to amount to $4.73 billion. Fortune Business Insights analysts believe that in the future, the CAGR will be at 43.3%. As a result, by 2032, costs could increase to $58.74 billion.^[1]

Introduction of artificial intelligence brings tens of billions of dollars to telecom

Many telecommunications companies have begun introducing generative artificial intelligence (GeniI), generating significant cost savings in areas such as marketing, sales and customer service. These technologies can provide industry participants with a significant revenue increase, as stated in the McKinsey review published on October 18, 2024.

It is noted that telecom market players are facing increasingly tough competitive pressure from rapidly developing technology companies. To stimulate revenue growth, operators are forced to develop new areas such as the Internet of Things (IoT), SaaS (software as a service) and streaming video platforms. In addition, companies are entering related industries including insurance, financial services and healthcare to offer new B2C and B2B services. McKinsey analysts say that in the resulting macroeconomic situation, AI technologies give telecom operators the opportunity to rethink themselves, optimize business processes and, ultimately, stimulate growth.

The McKinsey report said that for telecoms companies, the goal is to introduce AI into all aspects of the business. We are talking about improving customer experience, optimizing internal operations and infrastructure, as well as reducing costs by automating certain tasks. At the same time, it is emphasized that industry participants need to focus on responsible use of AI (Responsible AI, RAI). This is an approach involving the design, evaluation and deployment of AI systems in compliance with the principles of security, reliability and ethics. As AI is widely adopted, ensuring privacy and protecting personal and business information are becoming more important and complex tasks. Therefore, the concept of RAI is extremely important for gaining customer trust and preventing threats.

According to McKinsey estimates, AI can increase the profits of telecommunications companies by 3-4% in two years and by 8-10% over five years (until the end of 2029). At the same time, the implementation of RAI best practices can bring up to $250 billion by 2040. Analysts emphasize that like all AI deployments, RAI can significantly improve business processes and optimize technology integration to reduce costs. Effective RAI can also strengthen the brand's reputation, and higher customer acquisition and retention rates often drive revenue growth. In addition, RAI can help reduce commercial and reputational risks across the spectrum of AI tools and applications by ensuring that they operate at the highest level of accuracy. For example, thanks to RAI methods, the company's customer support chatbot will not use biased or incorrect language and will never recommend a competitor's product or service.

Telecommunications companies can benefit from RAI in several ways. Among them, McKinsey specialists name: improved business results, competitive advantage, sustainable growth, increased customer confidence, improved operational efficiency, attracting qualified specialists and financial benefits. Market participants acknowledge that robust control of the RAI serves as an "effective brake" that allows "moving faster" to harness the full potential of AI while reducing risks. However, one of the most significant barriers to RAI deployment is the lack of industry standards.^[2]

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