Russian business plans to increase investments in AI and data offices

According to a study by VK Tech and the MARC agency, AI has become a catalyst for the transformation of the entire data ecosystem: 74% of companies plan to invest in AI solutions in the next two years, and 71% plan to increase data office budgets as early as 2026.

The online survey covered 154 large business companies from trade, e-commerce, industry, development and other industries. The majority of respondents are businesses with an annual turnover of 10 billion rubles or more, where the volume of structured data reaches 260 TB on average and increases by about 50 TB annually.

In the next two years, companies plan to invest in AI agents (62% of respondents), machine learning (53%), and generative AI and LLM technologies (51%). Each of these areas has an infrastructure requirement: for an AI agent to work quickly and securely, we need fault-tolerant storage, unified data platforms, and data quality management tools. That is why 45% of companies call the implementation of AI/LLM solutions a key task of the data office, 40% focus on upgrading the data infrastructure, and another 39% on improving the quality and security of data.

"Companies no longer perceive AI as a separate experiment, but as part of a broad transformation of working with data. This can be seen from several signals: the business is putting significant budgets on AI, at the same time strengthening the data office, modernizing the infrastructure and increasing requirements for data quality and security. Against this background, the demand for data storage tools will grow, including S3-compatible object storage and unified data platforms based on lakehouse architecture. For businesses, this is a way to simultaneously contain scaling costs, reduce infrastructure complexity, and improve data quality for analytics and AI scenarios," said Ekaterina Kanunnikova, Product Director of Data Services at VK Tech.

AI application scenarios also confirm the infrastructural focus. Today, businesses use artificial intelligence primarily to improve operational efficiency (51% of respondents), analytics and BI (44%), marketing and personalization (39%). But the main challenge for companies is data security (45%), followed by quality control (34%) and increasing technology stack requirements (32%). In such a situation, investments in infrastructure become not optional, but mandatory for realizing the AI potential.