Safaricom has notified its customers of a scheduled M-PESA system maintenance set to take place on Monday, March 25, 2025.
According to a notice released on Saturday, March 22, 2025, the maintenance exercise will begin at 1:00 AM and is expected to last for 30 minutes, ending at 1:30 AM. The telecommunications company assured users that this temporary service interruption is part of its commitment to improving system reliability and security.
“To meet our promise to always offer reliable, safe, secure, and a superior customer experience, we will be conducting a scheduled system maintenance,” the statement read.
Minimal Disruptions Expected
Safaricom clarified that only M-PESA services will be affected during this period, with all other services, including calls, data, and SMS, remaining available and uninterrupted. The telco further emphasized that the maintenance window has been strategically scheduled to minimize inconvenience for customers.
“The timing of this maintenance has been planned to result in the least inconvenience to our customers,” the statement added.
Safaricom’s AI-Powered Digital Transformation
In addition to system improvements, Safaricom is advancing its Artificial Intelligence (AI) strategy to enhance customer experiences. The company has been actively incorporating AI and machine learning algorithms to provide more personalized, efficient, and impactful services.
Joseph Kanyua, Safaricom’s Digital Transformation Lead, highlighted that AI integration is a key pillar in the company’s mission to become Africa’s leading technology company by 2030.
“We are taking the lead in this; we run the largest network in the region, and we’ve set our ambitions to become Africa’s leading technology company by 2030. There’s no way we are going to achieve that objective without figuring out AI – and not just figuring it out, but actually taking it for a spin,” he stated.
Sustainability and Energy Optimization
Beyond customer service enhancements, Safaricom is also leveraging AI for sustainability. The telco is deploying predictive models and intelligent solar solutions across its infrastructure to optimize energy usage and support its green energy initiatives.
