The Information and Communication Technology (ICT) sector accounts for approximately 2–3% of global energy demand, and telecom networks are a major contributor. According to the International Energy Agency (IEA), global data traffic is doubling roughly every two years, pushing infrastructure to grow faster than ever.
The challenge? Growth often means more energy consumption, more electronic waste, and more carbon emissions. To align with GSMA’s Net Zero 2050 goals, operators are adopting greener network strategies—and AI is becoming central to that transformation.
The Sustainability Imperative in Telecom
The ICT sector accounts for approximately 2–3% of global energy demand, and telecom networks are a major contributor. According to the International Energy Agency (IEA), global data traffic is doubling roughly every two years, pushing infrastructure to grow faster than ever.
The challenge? Growth often means more energy consumption, more electronic waste, and more carbon emissions. To align with GSMA’s Net Zero 2050 goals, operators are adopting greener network strategies—and AI is becoming central to that transformation.
How AI Makes Network Operations More Sustainable
Here are four key ways AI is enabling sustainability across telecom operations:
A. Energy Optimization
AI algorithms analyze traffic patterns in real-time and dynamically power down unused base stations or components during low-traffic periods. This approach is known as “sleep mode management” and can save up to 20–30% of energy in mobile networks.
Example:
Telefonica uses AI for “Intelligent Energy” management across 90,000 sites, reducing energy usage by 7.5% annually, even as traffic increases.
B. Predictive Maintenance
Instead of scheduled (and often unnecessary) maintenance, AI systems can detect anomalies and predict hardware failures. This reduces unnecessary truck rolls and part replacements—lowering fuel consumption, labor costs, and e-waste generation.
Example:
Nokia AVA platform provides predictive analytics for MNOs, identifying equipment degradation before failures occur—reducing downtime and material waste.
C. AI-Driven Network Planning
AI helps operators simulate and plan new infrastructure in a way that minimizes environmental impact. By forecasting usage demand and evaluating energy/resource intensity of different rollout strategies, AI ensures more efficient capital investment.
Example:
Ericsson's Network Planner integrates AI to forecast 5G rollout demand, improving coverage while reducing over-deployment.
D. Dynamic Cooling and Smart Grids
AI-enabled climate control systems regulate temperature in data centers and base stations more precisely than traditional thermostats. In some advanced cases, AI integrates with smart grid technology to use cleaner electricity at optimal times.
Financial and ESG Benefits for MNOs
✔️ Lower Operational Costs:
AI reduces power bills and equipment replacements—often yielding ROI in less than 12 months.
✔️ Improved ESG Scores:
Energy-efficient operations directly contribute to lower Scope 2 and Scope 3 emissions, helping MNOs meet their sustainability KPIs.
✔️ Regulatory Alignment:
Governments and regulators are increasingly mandating sustainable reporting. AI helps operators collect and analyze carbon data for compliance with frameworks like TCFD and CDP.
Real-World Impact: Vodafone & Deutsche Telekom
Vodafone
By applying AI across its European networks, Vodafone reduced energy use by 6.5% in FY22, despite a 14% increase in traffic. Their AI-led sleep mode saved enough electricity to power over 28,000 homes for a year.
Source: Vodafone Sustainability Report 2023
Deutsche Telekom
Using AI-powered resource optimization tools, DT saved 1.5 million kWh in one year. Their AI model predicts low-traffic windows and powers down components intelligently.
Challenges to Adoption
While the benefits are clear, AI implementation isn’t without hurdles:
- Data Quality: AI models need high-quality, real-time data from diverse systems.
- Legacy Infrastructure: Older networks may require upgrades to support AI-based automation.
- Skill Gaps: Telecom teams need training in AI integration, analytics, and model governance.
However, as AI tools become more plug-and-play and cloud-native platforms mature, barriers to entry are falling quickly.
The Future: AI + Circularity in Telecom
AI isn’t just about software optimization. It also plays a growing role in enabling circular supply chains by:
- Identifying underutilized assets for resale or redeployment.
- Tracking device lifecycle emissions.
- Powering digital twins for sustainability simulations.
As platforms like NetZero.tel help operators manage circular inventory and surplus equipment, AI will increasingly connect the dots between operational efficiency and material sustainability.
Conclusion: Smarter Networks, Greener Future
Artificial Intelligence is reshaping telecom’s sustainability playbook. From smarter cooling systems to dynamic sleep modes and predictive repair, AI allows operators to scale their networks without scaling their footprint.
As NetZero strategies mature, integrating AI is no longer optional—it’s essential. Telecoms that embrace AI not only stand to save millions but also lead the way in environmental stewardship.