Moscow Region Is Building an Intelligent Utility Management System
Artificial intelligence technologies are becoming more widely used by fuel and energy companies and utilities across Moscow Region. Companies are readily sharing their experience with digital tools to give residents greater comfort and safety.
Representatives of Moscow Region's fuel and energy and utility companies have long worked together to share experience and discuss the deployment of AI and other digital technologies. This time, representatives of Mosoblenergo and Rosseti Moscow Region visited Mosoblgaz. The focus was not on emerging technologies, but on solutions that have already been proven in practice.
Mosoblgaz representatives described the company's integrated system for handling resident requests. All existing communication channels – hotline calls, requests submitted through the Dobrodel (Good Deeds) portal, social media and chatbots – are consolidated in a single registry built on the Bitrix24 platform. The registry records not only complaints and suggestions, but also the applicant's contact information and deadlines for carrying out the decisions made in response.
One of the most effective tools for processing requests is now a voice robot running on the ZIAX platform. It currently handles about 850,000 of the 1.3 million calls received by the Mosoblgaz hotline each year. That means the AI assistant handles 65.5% of all phone requests, up from 32% four years ago.
Mosoblgaz also uses neural-network technologies to manage its internal operations, supported by an in-house AI agent deployed on the company's own GPU cluster. The company is also actively adopting predictive analytics algorithms. Analyzing incoming complaints is already helping it address systemic problems.
From Reactive to Proactive Management
The biggest opportunities for further AI adoption in the fuel and energy and utility sectors lie in processing and analyzing large volumes of data. A stream of requests tied to specific districts, combined with information from sensors installed across infrastructure facilities, makes it possible to move from reactive to proactive management. Neural networks can detect system failures and pinpoint their location before they develop into accidents. That allows companies to prevent problems instead of dealing with their consequences. The approach matters not only to gas distribution network operators, but also to companies such as Mosoblenergo and Rosseti Moscow Region. Meanwhile, sharing experience with technologies that have already been tested allows companies to put proven tools into practice quickly rather than spending time on experimentation.
AI Expands Across Moscow Region
The first steps toward deploying AI technologies in Moscow Region's utility and fuel and energy sectors began in 2020. That year, the regional Ministry of Housing and Utilities launched a chatbot to handle requests related to municipal solid waste. In 2021, Mosoblgaz introduced a voice assistant with limited functionality on its hotline. In 2023, the assistant was integrated with the company's corporate systems, significantly expanding what it could do. By 2026, Moscow Region had 67 AI projects operating across eight areas, including utilities, transportation, health care and education.
From Bots to Digital Control Rooms
Over the next several years, companies in the fuel and energy and utility sectors are expected to step up the pace of sharing experience. And with the federal push to digitize the housing and utilities sector, technologies developed and tested in Moscow Region are likely to be deployed in other regions as well.
The next step could be the development of standardized AI modules that classify requests, respond to complaints and analyze collected information to forecast potential failures. These modules could then be quickly adapted to the needs of individual companies, regardless of their area of operations.
Unified digital control rooms could also emerge, automatically processing requests received through common channels and routing them to the appropriate organizations. At the same time, municipal and regional authorities would gain a single view of infrastructure conditions. In practice, AI would become an operational tool for significantly improving the reliability and quality of utility services for residents.
