Key Russian IT Trends for 2026: Research by HSE Graduate School of Business
In 2026, digital technologies continue to play a central role in the growth of Russian businesses. Efforts to overcome import dependence, improve operational efficiency, and meet rising requirements for corporate digital maturity are driving increased interest in resilient and adaptable IT solutions.
Professor and Head of the Department of Business Informatics at the HSE Graduate School of Business
Our goal was to identify the technologies that will deliver the greatest value to Russian enterprises in the coming years. The competitiveness of organizations increasingly depends on making the right choices in digital tools.
ВHSE Business School experts focused both on solutions that are already being implemented and on emerging technologies that are only beginning to penetrate corporate processes. The study also identified the areas in which IT adoption generates the greatest impact, along with the key barriers to digital transformation.
Ten Promising IT Trends for 2026
Based on an analysis of Russian and international best practices, as well as a survey of 306 representatives of Russian companies, the researchers identified the following ten trends as the most significant for business development:
1. Data enrichment and integration
2. Domain-Specific Language Models (DSLM)
3. Low-code and no-code platforms
4. AI agents
5. Mobile robots and autonomous drones
6. AI-powered business analytics
7. Everything-as-a-Service (XaaS) models
8. Synthetic data
9. Proactive cybersecurity
10. Adaptation and import substitution of IT management practices
AI Agents: The Leading Technology Focus of 2026
AI agents are attracting the greatest interest from organizations: 59% of respondents are actively exploring opportunities for their implementation. These solutions make it possible to automate processes that previously required manual effort or complex custom development.
AI agents can process requests in natural language, execute tasks, and propose different formats for presenting results. For example, an analytical agent can independently analyze monthly sales data, identify anomalies, and generate actionable recommendations.
Experts note that, in the near future, businesses will be able to combine multiple agents into a single ecosystem. One agent may handle customer consultations, another process sales transactions, while a third updates product listings. In effect, this represents a shift toward fully automated end-to-end process chains.
Data Enrichment and Integration: The Most Widely Adopted Trend
61% of companies are already using data integration solutions, while an additional 26% plan to implement them. Modern enterprises operate with highly diverse data sources, including cloud platforms, sensors, social media, and partner services. The ability to consolidate, cleanse, and normalize large volumes of data is becoming critical not only for business growth, but also for organizational resilience. Companies also report growing risks related to unreliable external data and personal data compliance. As a result, greater attention is being paid to digital hygiene, data governance, and source verification.
XaaS Losing Ground
The Everything-as-a-Service (XaaS) model proved to be the least adopted trend: only 14% of companies have implemented it, while 61% do not plan to adopt it. Despite its advantages, which are lower capital expenditures, faster deployment, and operational flexibility, organizations remain cautious about transferring data and business processes to external providers. Organizations are placing growing emphasis on data security, control, and off-perimeter storage.
Synthetic Data: Opportunities and Limitations
One of the most debated trends for 2026 is synthetic data. These artificially generated datasets replicate the key characteristics, structure, and relationships found in real data, while containing no information about specific individuals, objects, or events.
This approach enables companies to train their own AI models without violating personal data protection requirements. At the same time, experts point to limitations related to data quality, representativeness, and the risks of bias embedded in synthetic datasets.
Research Methodology
The study was conducted in several consecutive stages. First, experts from HSE Business School analyzed a broad range of Russian and international publications on modern digital technologies and compiled an initial list of IT trends most relevant to Russian enterprises.
Next, the researchers conducted a series of expert interviews with representatives of large Russian companies across various industries. These discussions helped refine the preliminary list and align it with real-world business needs.
The final stage involved a large-scale survey with 306 employees from Russian organizations.
