• KZT/USD = 0.00222
  • TJS/USD = 0.10830
  • UZS/USD = 0.00008
  • TMT/USD = 0.29760
  • KZT/USD = 0.00222
  • TJS/USD = 0.10830
  • UZS/USD = 0.00008
  • TMT/USD = 0.29760
  • KZT/USD = 0.00222
  • TJS/USD = 0.10830
  • UZS/USD = 0.00008
  • TMT/USD = 0.29760
  • KZT/USD = 0.00222
  • TJS/USD = 0.10830
  • UZS/USD = 0.00008
  • TMT/USD = 0.29760
  • KZT/USD = 0.00222
  • TJS/USD = 0.10830
  • UZS/USD = 0.00008
  • TMT/USD = 0.29760
  • KZT/USD = 0.00222
  • TJS/USD = 0.10830
  • UZS/USD = 0.00008
  • TMT/USD = 0.29760
  • KZT/USD = 0.00222
  • TJS/USD = 0.10830
  • UZS/USD = 0.00008
  • TMT/USD = 0.29760
  • KZT/USD = 0.00222
  • TJS/USD = 0.10830
  • UZS/USD = 0.00008
  • TMT/USD = 0.29760
13 October 2026

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Central Asia in the Global Innovation Rankings: Supercomputers, Engineers, and the Economics of Government Ambitions

In the Global Innovation Index (GII), published on September 29 by the World Intellectual Property Organization (WIPO), Kazakhstan climbed eight places to rank 73rd among 139 economies. Uzbekistan ranked 77th and Kyrgyzstan 92nd. Tajikistan placed 112th, while Turkmenistan was not included in the study. The overall rankings, however, conceal some interesting details. Uzbekistan ranks second worldwide in the share of graduates in science and engineering. Kyrgyzstan ranks second in labor productivity growth, while Tajikistan leads in utility model applications relative to the size of its economy. Utility models are a simpler form of patent protection, usually for smaller inventions. Such strong results in individual indicators stand in contrast to the countries' relatively modest overall rankings. Part of the explanation lies in the study's methodology. WIPO evaluates education and scientific capacity alongside infrastructure and investment. It also considers business activity and research output. A country may train large numbers of engineers or register technical innovations while lagging in research output and investment, with limited commercial activity. For Central Asia, the rankings also offer a way to compare economic performance with the scale of governments' technological ambitions. Kazakhstan: Supercomputers in Search of Customers In recent years, Kazakhstan has assembled an impressive portfolio of digital projects. The Alem.Cloud and Al-Farabium supercomputers, along with the Data Center Valley project in Ekibastuz, are intended to improve the country's computing infrastructure. The Alem.ai artificial intelligence (AI) center and the KazLLM and AlemLLM large language models are designed to develop its AI capabilities. Training opportunities are also expanding through AI-Sana and Tomorrow School, with TUMO Astana offering education in AI and other digital fields. However, the wider use of AI remains relatively modest. The Digital Qazaqstan strategy through 2029 cites figures for the second half of 2025 showing that generative AI adoption in Kazakhstan stood at 13.7%, compared with a global average of 16.3%. Kazakhstan ranked 24th in the United Nations (UN) E-Government Development Index in its 2024 survey but 73rd in the 2026 GII. Kazakhstan's digitalization model has long centered on government services. The country's high position in the UN study reflects this focus. Commercial technologies present a more complicated picture: here, the government must rely on research teams, private developers, investors, and customers willing to pay for their services. The arrival of supercomputers expands the country's technical capabilities. How extensively they will be used outside government projects remains to be seen. Uzbekistan: Engineering Education and IT Services Exports The country has long focused on workforce development for the IT industry. An export-oriented digital services sector is growing around IT Park. Foreign companies are operating in the country, while training programs in programming and AI are expanding. Tashkent intends to support its workforce development policies with domestic computing infrastructure. Under the AI development strategy adopted in 2024, Uzbekistan plans $50 million in AI infrastructure spending and the training of one million specialists. AI laboratories are also planned at 15 universities. A smaller supercomputer is already operating, and preparations are underway to acquire a more powerful system....