The essential role of AI in improving energy efficiency
Please sign in or register for a free public account to access this report.
Telecoms operators recognise the need for an energy efficiency plan to reduce CO2 emissions and lower costs without compromising on network performance and customer experience. According to our new report, in partnership with Nokia, 83% of operators rate energy efficiency as extremely or very important to their network transformation strategy, while 78% expect AI-driven solutions to be an extremely or very important part of their network transformation strategy.
To operate an energy-efficient network, a multitude of optimal decisions need to be made every minute, in real time and in various parts of a mobile network. As AI allows vast amounts of data from different sources to be analysed quickly and efficiently, it expands the potential for several energy-saving opportunities across the whole network. Network operators cannot efficiently process information and make real-time decisions at scale without the use of AI. As energy consumption is a key operational cost for all operators, those that are currently not planning to use AI-driven energy management risk having a long-term competitive disadvantage.
In parallel, GSMA Intelligence has also released Industry pathways to net zero in partnership with Nokia. Both reports have significance for the telecoms ecosystem and enterprise customer segments in understanding the value of mobile and digital technology in transitioning towards a sustainable future and ultimately net zero.
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.
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
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.
- 200 reports a year
- 50 million data points
- Over 350 metrics