DEWA Showcases AI-Powered Asset Management Strengthening Dubai's Power Network

Dubai Electricity and Water Authority CEO Saeed Mohammed Al Tayer toured the authority's Distribution Power complex in Al Ruwayyah this week, reviewing a cluster of technologies aimed at pushing the emirate's electricity network from reactive maintenance toward predictive, data-driven operations. Al Tayer was accompanied by Rashid Bin Humaidan, Executive Vice President of Distribution Power, and senior DEWA officials, according to a WAM report on the visit.

The centrepiece of the tour was DEWA's Asset Health Centre, which uses real-time data on the condition, risk profile and maintenance requirements of network assets, generated with AI and machine learning algorithms, to support risk-based maintenance planning and optimise the timing of asset replacement before failures occur. Alongside it, DEWA's Distribution Automation programme uses RF-Mesh technology to enable remote monitoring and control from Distribution Control Centres, part of the broader Smart Grid effort to improve network reliability without waiting for a fault to be reported.

The visit also highlighted a genuine technical first: DEWA says it is the only utility in the world using X-ray inspection to examine capacitor bank circuit breakers without taking them offline or risking damage, letting engineers catch internal defects early and reduce the risk of unplanned outages. Al Tayer also inspected two of the complex's accredited laboratories, an ISO/IEC 17025:2017-certified Cable Lab supporting root-cause analysis and lifecycle management, and an Energy Meter Testing Lab handling accredited testing of energy meters and current transformers, both of which feed data back into the same asset-health model rather than operating as standalone quality checks.

This tour is one data point in a considerably longer pattern. DEWA has been building toward this kind of predictive-maintenance capability for years through its Space-D programme, and Al Tayer used a World Governments Summit appearance earlier this year to announce a "Virtual Engineer," an AI system intended to continuously learn from operational data and offer predictive failure alerts, root-cause analysis and real-time scenario simulation for the power network, alongside an AI-powered gas turbine controller already running at the Jebel Ali Power and Desalination Complex. The Al Ruwayyah showcase suggests that ambition is now extending from generation assets to the distribution network that actually delivers power to customers, where equipment failures are more numerous, more distributed, and historically harder to predict.

The approach is consistent with the broader, government-driven push toward applied AI across Dubai's public institutions that this site has tracked elsewhere, including the use of AI digital twins to model and de-risk energy infrastructure decisions across the Gulf and Dubai Chambers' recent rollout of Agentic AI training to more than 14,000 member companies. What distinguishes DEWA's version is that it is being deployed on infrastructure where the cost of getting predictions wrong is measured in outages rather than inconvenience, which makes the Asset Health Centre a more consequential test of whether Dubai's AI-first public sector strategy holds up under operational pressure rather than in a pilot environment.