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Technological Infrastructure. 
Uzbekistan’s technological infrastructure for supporting AI in 
the financial sector is still nascent. The challenges range from limited high-speed internet access, 
outdated computer systems, lack of cloud infrastructure, and insufficient data management 
facilities. The country's rural areas, in particular, suffer from poor connectivity, impeding the 
outreach of AI-powered financial services. Additionally, the absence of modern data centers 
hampers the processing capabilities needed for complex AI algorithms. The legacy systems used 
by many financial institutions are incompatible with advanced AI technologies. 
Regulatory Environment. 
The legal and regulatory framework governing AI in Uzbekistan's 
financial sector lacks both depth and breadth. There is uncertainty around compliance, 
intellectual property rights, consumer protection, and anti-competitive practices. Ambiguity in 
regulations creates a risky environment for both investors and innovators. The lack of clear 
guidelines regarding AI's ethical usage, transparency, and fairness leads to hesitation in adoption. 
Moreover, misalignment with international regulatory standards further complicates cross-border 
financial activities. 
Talent and Education. 
Uzbekistan faces a shortage of skilled professionals capable of 
designing, implementing, and maintaining AI systems in the financial industry. The educational 
system lacks specialized courses, and there is a dearth of continuous learning opportunities. The 
absence of university programs focused on AI, machine learning, and data science creates a 
barrier to fostering local talent. The limited collaboration between the academic sector and 
industry leads to a mismatch between the skills taught and those required by the financial 
industry.
Access to Capital. 
The investment needed to foster AI innovation in Uzbekistan's financial 
sector is significant. However, both public and private funding sources are limited, leading to a 
scarcity of financial resources for research, development, and implementation. The lack of 
venture capital, government grants, and international funding hinders startups and existing 
financial institutions from investing in AI technologies. This stifles innovation and restricts the 
exploration of new financial products and services.