Use of generative AI by operators: where do network decision-makers see the business impact?

This report is available to those subscribed to the Mobile Operators and Networks module.
GSMA Intelligence's Chart of the Month is a visual way of telling an important story in the mobile and broader tech ecosystem. From the shape and size of markets to trends in consumer behaviour, we aim to provide food for thought through informative visuals designed to bring colour and clarity to complex issues facing the industry. In this edition, we look at how operators expect generative AI to impact the telecoms sector.
Related research
Telco AI: State of the Market, Q2 2025
If 2024 was about establishing the strategic rationale for AI, 2025 is about assessing progress. To this end, GSMA Intelligence has evolved this research series to establish a baseline that can be tracked over time for the industry, its supply chain and partnership ecosystem. As well as recent developments from the telco AI space and the Telco AI tracker, this edition provides a deep dive of AI at the edge, looking at the strategic value of different AI inference options.
The mobile churn challenge: where loyalty is lowest and four recommendations for operators
The latest consumer survey by GSMA Intelligence reveals that around one in seven mobile users changed their service provider over the previous 12 months. The main reasons for churn have stayed largely unchanged over the last five years, at the aggregate level, with value for money by far the top reason. However, variations exist between consumer segments in terms of the degree of churn and the drivers.
AI inference in practice: new intelligence from the hospital floor
Enterprises need to understand that where inferencing happens – whether at the user edge (device and enterprise/on-premises) or network edge (far edge, near edge and telco private cloud) – will have major implications for application performance, data sovereignty, resilience and energy efficiency. This analysis focuses on how running AI workloads on the enterprise edge (on-premises) can deliver improved outcomes.
Authors
How to access this report
Annual subscription: Subscribe to our research modules for comprehensive access to more than 200 reports per year.
Enquire about subscriptionContact our research team
Get in touch with us to find out more about our research topics and analysis.
Contact our research teamMedia
To cite our research, please see our citation policy in our Terms of Use, or contact our Media team for more information.
Learn moreRelated research
Telco AI: State of the Market, Q2 2025
If 2024 was about establishing the strategic rationale for AI, 2025 is about assessing progress. To this end, GSMA Intelligence has evolved this research series to establish a baseline that can be tracked over time for the industry, its supply chain and partnership ecosystem. As well as recent developments from the telco AI space and the Telco AI tracker, this edition provides a deep dive of AI at the edge, looking at the strategic value of different AI inference options.
The mobile churn challenge: where loyalty is lowest and four recommendations for operators
The latest consumer survey by GSMA Intelligence reveals that around one in seven mobile users changed their service provider over the previous 12 months. The main reasons for churn have stayed largely unchanged over the last five years, at the aggregate level, with value for money by far the top reason. However, variations exist between consumer segments in terms of the degree of churn and the drivers.
AI inference in practice: new intelligence from the hospital floor
Enterprises need to understand that where inferencing happens – whether at the user edge (device and enterprise/on-premises) or network edge (far edge, near edge and telco private cloud) – will have major implications for application performance, data sovereignty, resilience and energy efficiency. This analysis focuses on how running AI workloads on the enterprise edge (on-premises) can deliver improved outcomes.
- 200 reports a year
- 50 million data points
- Over 350 metrics