PLUS-Forum Digital Uzbekistan discussed future and present of AI

How to formulate rules that won’t quash innovations in the field of artificial intelligence, but will contribute to their development, making them even more popular and secure? These and other pressing issues were discussed at the session “Artificial intelligence. The role and place of AI at the national level, in business, IT and finance” on May 28, 2025, in Tashkent. 

The session was moderated by Vladislav Dolenko, Director for Digitalization and Innovation, AIN Property Management LLC. 

Scott Reiser, Technology Consulting Manager at KPMG Caucasus and Central Asia, noted in his report “Governing AI adoption” that 92% of

financial services companies worldwide reported generating profits from AI. According to him, AI not only increases productivity, but also serves as a catalyst for innovation. At the same time, Reiser emphasized that to enable returns, a company needs a structured transformation, rather than a mere implementation of the technology. KPMG offers comprehensive solutions for AI integration and long-term use strategies. 

In his report “Innovative Lenovo solutions for the AI ​​era”, Lenovo representative Grigory Prilukhin noted that businesses are no longer experimenting with AI, but are systematically implementing it into their processes. Lenovo offers infrastructure solutions, an extensive portfolio of equipment and software capable of supporting resource-intensive AI tasks. The company is continuously updating its product line to meet the requirements of the new technological cycle. 

Sberbank Executive Director Yuri Perevezentsev spoke about Sber's experience in creating business solutions for data analytics. The speaker considered three main stages of working with data and gave examples of three SberTech products used in each of them. This includes the Data Tracker, Navigator and Process Mining systems. As examples, the expert offered cases with specific banks, including those from Central Asian countries with Uzbekistan among them. 

Andrey Zavarzin, Deputy Board Chairman of Halyk Bank, focused his report on new opportunities emerging from the synergy of Big Data and machine learning. The speaker reviewed new opportunities for working with big data through the prism of the experience of the largest bank in Central Asia. 

Yulia Andrianova, Sr. Account Manager at Amazon Web Services, discussed how generative AI is changing business, especially in retail. She presented specific cases of using generative AI, which enable automation of interactions with clients, personalization of offers and help streamline internal processes. 

Daniyar Omurzakov, CyberNet Regional Director for Central Asia, reported on “AI-agents and a 10x economy: the new norm for business”. The company is developing voice AI and handles up to 7 million dialogues per month for partners worldwide. Omurzakov emphasized that such technologies are especially relevant for the financial sector: in the rapidly growing credit market of Uzbekistan, debt servicing costs can reach a critical value, if processes are not automated. Generative voice agents are becoming the basis for sustainable collection and business scalability. 

Dmitry Sheranov, Director for International Business Development at Arenadata, considered corporate data warehouses as the foundation for the use of artificial intelligence to effectively solve business problems. He took as an example business cases of companies using his company's products. Today, Arenadata dominates in the segment of Big Data platforms for digital transformation, continuing to expand its product stack. 

Arman Assakayev, Head of non-profit organization FinTech AI Center (Kazakhstan), raised the issue of public and private data democratization for AI. According to the speaker, data is getting more expensive with every passing year (by about 11% annually), while the price growth rate is expected to reach 15%. At the same time, the combination of confidential computing technologies and 

synthetic data allows for the implementation of a number of projects for secure data sharing, which significantly reduces costs. This is the approach proposed by a special platform developed for the purpose of data democratization.

 

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