Kazakhstan's State Company Launches 62 AI Projects With KZT 711 Billion Target
Samruk-Kazyna, Kazakhstan's sovereign wealth fund, is deploying 62 artificial intelligence projects across its holdings, expecting KZT 711 billion in economic value by 2030. The initiative aims to cut costs, improve efficiency, and drive growth in mining, oil and gas, manufacturing, telecommunications, and transportation.
The company built SKAI, a proprietary AI platform that operates in a closed, secure environment powered by the Al FARABIUM supercomputer. SKAI includes digital assistants across seven business functions, including risk management and procurement.
Performance Targets for 2026
Samruk-Kazyna targets a 5% EBITDA increase through AI adoption by 2026. The company is investing in internal AI capabilities rather than relying on external vendors, ensuring solutions fit its specific operational needs.
The 62 projects span sectors critical to Kazakhstan's economy. AI deployment focuses on optimizing resource extraction, streamlining production, and reducing operational expenses across subsidiaries.
How SKAI Works
SKAI functions as an internal AI ecosystem rather than a public-facing tool. The platform handles decision-making support and operational tasks across the company's group of businesses.
- Risk management and assessment
- Procurement processes
- Production optimization
- Resource planning
Operating within a closed environment reduces security risks and keeps proprietary data internal. The Al FARABIUM supercomputer provides the computational foundation, with plans to expand capacity further.
Economic Impact and Scope
The KZT 711 billion projection reflects expected gains across mining, metals, oil and gas, and transportation. These sectors represent the backbone of Kazakhstan's economy and account for a significant share of state revenue.
By improving resource extraction efficiency and reducing production costs, AI is expected to increase overall productivity. The economic benefits extend beyond Samruk-Kazyna to broader national development priorities.
What This Means for IT Professionals
Organizations deploying enterprise AI face similar infrastructure and integration challenges. Samruk-Kazyna's approach-building proprietary systems on dedicated hardware-represents one strategy for managing security and performance at scale.
For IT teams, the project highlights the operational complexity of supporting AI across multiple business units. Integration with existing systems, data governance, and computational resource management remain critical concerns.
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