Bangladesh’s telecom operators and tower companies are increasingly using artificial intelligence to reduce energy consumption, predict equipment failures and automate network operations, with early deployments reporting measurable reductions in power use, operating expenditure and engineering workload.
AI systems are being used to switch network equipment on and off according to traffic demand, monitor batteries and generators, predict site and transmission failures, correlate alarms and reduce unnecessary field visits.
The potential impact is significant because of the scale of Bangladesh’s telecom infrastructure, which included 46,504 towers as of June 2026, according to Bangladesh Telecommunication Regulatory Commission data.
AI cuts energy consumption as traffic fluctuates
One of the most immediate applications is network energy optimisation.
Telecom equipment has traditionally remained active continuously to ensure sufficient capacity is available whenever demand rises. AI allows operators to analyse traffic at individual cells and reduce network resources during lower-demand periods without materially affecting service quality.
Grameenphone said its AI-based autonomous network management has generated energy savings of between 7% and 8%.
Syed Shakil Ahmed, head of AI Strategy and Development at Grameenphone, said the operator had initially targeted a 7% reduction.
The system analyses cell-level traffic patterns and identifies periods when power consumption can be reduced while maintaining the required customer experience.
Tower companies use AI to optimise batteries and generators
AI adoption is also expanding into the physical infrastructure that powers mobile networks.
Tower companies are using predictive analytics to assess electricity consumption, battery condition, generator use, fuel demand and grid availability.
Summit Communications said preliminary estimates across selected sites and operational areas indicate AI-assisted systems have reduced energy consumption by around 5% to 8%.
The savings are attributed to remote monitoring, predictive maintenance, automated operations, improved work scheduling and fewer unnecessary site visits.
edotco Bangladesh is also using AI to forecast requirements for batteries, power systems, solar installations and backup energy resources based on network traffic, grid availability and site-specific conditions.
Al Batuni Mohammad Sayed Ahmed, country managing director of edotco Bangladesh, said AI-driven analytics are helping the company make faster planning decisions, improve resource allocation and reduce unnecessary capital expenditure.
Bangladesh has more than 46,000 telecom towers
The scale of the infrastructure means even relatively small efficiency improvements can translate into significant operational savings.
According to BTRC data cited in the report, Bangladesh had 46,504 telecom towers in June 2026.
Of these, 11,788 were associated with Grameenphone, 3,910 with Banglalink, 3,469 with Teletalk and 2,189 with Robi.
Tower-sharing companies also operate substantial infrastructure, including 16,979 sites operated by edotco and 5,539 by Summit Communications.
With thousands of sites requiring continuous power, maintenance and monitoring, automation creates opportunities to reduce both electricity and operational costs.
Predictive maintenance reduces emergency intervention
AI is also changing how operators maintain equipment.
Instead of relying primarily on scheduled inspections, network teams can use real-time data and historical patterns to identify equipment likely to fail before an outage occurs.
At edotco, AI-enabled systems are being used for predictive fault detection, automated event analysis, root-cause identification and intelligent ticket management.
Banglalink is similarly using AI to predict site, power and transmission failures, enabling teams to deploy additional batteries or take other preventive action before service is affected.
The operator is also using AI-powered alarm correlation and root-cause analysis to reduce mean time to repair.
Banglalink adjusts network equipment according to demand
Banglalink is applying AI to optimise radio and transmission equipment according to the time of day.
Taimur Rahman, chief corporate and regulatory affairs officer at Banglalink, said the approach helps reduce fuel, battery and grid electricity consumption.
The company is positioning AI as an operational technology rather than simply an emerging digital service.
“We see AI not as a headline but as an enabler of smarter infrastructure management, higher service reliability, and better decisions,” Summit Communications Managing Director Arif Al Islam said.
Summit reports lower operating expenditure
The benefits extend beyond power consumption.
Summit Communications estimates that selected operational areas have achieved an 8% to 10% reduction in operating expenditure through AI-assisted monitoring, predictive maintenance, automation and improved scheduling.
Reducing physical intervention can be particularly valuable in a large distributed tower network because every field visit involves labour, transport and potentially fuel costs.
Predicting faults before they become emergencies can also reduce downtime and avoid more expensive reactive repairs.
AI cuts DDoS response from hours to under a minute
Cybersecurity operations are another area where automation is producing measurable gains.
Summit said automated distributed denial-of-service attack detection and mitigation can now identify and respond to an attack in under one minute.
The process previously required engineers to manually analyse network traffic and implement mitigation measures, which could take several hours.
According to the company, automation has reduced associated manual engineering effort by approximately 90%, while protected services have maintained around 99.95% uptime.
Summit stressed that any 100% saving reported for specific automated tasks applies only to that individual cost category and should not be interpreted as a complete elimination of overall operating expenditure.
