Telco AI: State of the Market, Q2 2024
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AI in telecoms – in theory and in action
AI is a transformative technology, but it is important to look beyond the hype and identify the parts of the innovation cycle that matter most. How do they translate into commercial activity and possible changes in corporate strategy?
GSMA Intelligence is launching this research series to investigate how telcos are putting AI to use, how they are innovating and what they (and supporting ecosystem players) need to be thinking about as they continue their AI journeys. The series will look at strategy and technology planning, AI sustainability, and the results of a benchmarking exercise establishing how advanced telcos are in their adoption and use of AI.
This first edition explores the expanding use of AI in telecoms, examining both core AI and genAI. It highlights key use cases, contrasts AI with genAI adoption, and delves into the increasing role of large language models (LLMs) in driving industry advancements.
Related research
AI inference in practice: time is money
As AI adoption grows, inferencing will accelerate, raising the question of where workloads will be processed and how they translate into business benefits. This analysis examines AI on the near edge in distributed telco data centres, with Kinetica highlighted as an example.
Edge AI: how IoT hardware and connectivity companies can drive ecosystem adoption and scale
Edge AI has gained major momentum during 2024–2025 as Qualcomm, Nordic Semiconductor, Synaptics and many others have launched significant innovations in edge silicon and hardware. This report focuses on the industrial IoT part of the market.
AI opens a new front in the fight against unwanted calls to fixed lines
Although the number of unwanted calls to fixed lines has been decreasing due to efforts from stakeholders (including operators, network and customer-premises equipment vendors and regulators), the emergence of AI, especially generative AI, could reverse this trend while also making consumers more vulnerable to scams. However, AI can also be used to tackle the scourge of unwanted calls. In this report, we examine the approach taken by key stakeholders in various countries, notably the UK and the US, highlighting some of the risks and opportunities in the struggle against unwanted calls.
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Learn moreRelated research
AI inference in practice: time is money
As AI adoption grows, inferencing will accelerate, raising the question of where workloads will be processed and how they translate into business benefits. This analysis examines AI on the near edge in distributed telco data centres, with Kinetica highlighted as an example.
Edge AI: how IoT hardware and connectivity companies can drive ecosystem adoption and scale
Edge AI has gained major momentum during 2024–2025 as Qualcomm, Nordic Semiconductor, Synaptics and many others have launched significant innovations in edge silicon and hardware. This report focuses on the industrial IoT part of the market.
AI opens a new front in the fight against unwanted calls to fixed lines
Although the number of unwanted calls to fixed lines has been decreasing due to efforts from stakeholders (including operators, network and customer-premises equipment vendors and regulators), the emergence of AI, especially generative AI, could reverse this trend while also making consumers more vulnerable to scams. However, AI can also be used to tackle the scourge of unwanted calls. In this report, we examine the approach taken by key stakeholders in various countries, notably the UK and the US, highlighting some of the risks and opportunities in the struggle against unwanted calls.
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