According to a survey conducted by NVIDIA, 95% of telecom service representatives south korea phone number library responded that they use AI. Of these, 34% said they have been using AI for more than 6 months, and 18% indicated that they are in the trial or pilot stage of launching AI projects.
At the same time, 23% of respondents reported that they are currently exploring possible use cases, including MCN Telecom.
The virtual operator has developed a bot named Vasilisa, whose intellectual capabilities anyone can test for free by phone. Since its launch, the speed of Vasilisa's responses and their relevance to requests have been significantly improved. You can verify this by calling +7 958 798 00 63. Based on the analysis of requests, a plan will be developed for using ChatGPT in telecom platform products.
In July of this year, the analytical company Precedence Research presented a report on the state of that part of the global communications services market that has already managed to implement generative AI, and the trends predicted in this area. Below, we will consider the main points from this study.
A Brief Overview of the AI Market in Telecom
In 2022, the generative AI market in telecommunications was valued at $150 million. In 2023, this figure is 213 million and is expected to reach over $4.8 billion by 2032, growing at an average annual rate of 40 percent.
The main areas of application of AI in telecom are customer service, network management systems, predictive analytics, security and fraud prevention, and stimulating innovation.
As AI solutions become more accessible, it will largely determine the future of the telecoms industry. This fact has a downside: British Telecommunications plc has already announced that it will cut 55,000 jobs by 2030, replacing people with smart programs.
Growth Drivers, Constraints and Potential Opportunities
The use of AI for customer service and network performance management is expected to be the major drivers of the market growth during the forecast period.
Chatbots and natural language processing-based recommendation services help automate support request resolution and personalize customer experiences. In network management, AI is used to plan network infrastructure, predict failures, and improve network performance.
Factors that are holding back the market's development include a shortage of experts in machine learning and artificial intelligence engineering, as well as the need for large investments in technological resources and infrastructure.
Analysts see great potential in optimizing operational activities and maintenance with the participation of AI:
Improving IT development productivity by writing and testing code
Speed up diagnostics and help troubleshoot equipment issues
Improving the training of technical specialists
