BAKU, Azerbaijan, October 31. Kazakhstan's
Ministry of Energy has presented the Energy AI Kazakhstan concept
to introduce artificial intelligence into production and management
processes across the country's fuel and energy sector by creating a
unified digital environment, the ministry said.


The concept was presented at a working meeting chaired by Kazakh
Energy Minister Yerlan Akkenzhenov to discuss the application of
artificial intelligence in the sector. Participants included Kai-Fu
Lee, Chairman of the Board of Directors of 01.AI and a freelance
adviser to the President of Kazakhstan, who joined the meeting
online, as well as representatives of the Kazakhstan office of
Q.AI.


During the meeting, Lee presented the company's approaches to
applying AI in the energy sector. Participants reviewed the
proposed platform's architecture, functionality, and potential
applications within the ministry and its subordinate
organizations.


The solutions presented included early detection of risks of
fuel shortages, automation of report preparation and verification,
and industrial safety monitoring. Their application is intended to
improve the speed of industry data analysis and support
better-informed decision-making.


Particular attention was paid to digital twins of energy
facilities. These tools make it possible to model production
processes, assess equipment conditions, identify potential
deviations, and evaluate the consequences of different scenarios
before technical decisions are made.







The proposed architecture combines industry-specific knowledge
bases, information systems, and specialized AI agents designed to
perform specific production and management tasks.


One of the key principles of the concept is ensuring
Kazakhstan's technological and information sovereignty. The
initiative envisages locating data, computing infrastructure, and
industry-specific models within the country, under the ministry's
control.


The meeting also addressed possible implementation stages,
including pilot testing using real industry data, assessing the
effectiveness of the proposed solutions, and subsequently scaling
up tools that demonstrate practical benefits for the sector.