How AI Agents Are Taking Over Investment Management
Sberbank is expanding the capabilities of its AI assistants for retail investors. By the end of the year, the algorithms are expected to start analyzing securities not only through issuers’ financial reports but also against the news cycle, creating personalized selections of recommended securities and funds for users.
AI-powered investment services will go beyond analyzing portfolio structure and market conditions. Over time, they are expected to execute trades autonomously once the client confirms them. Perhaps, the AI will also be able to buy and sell groups of assets at once rather than handling them one by one.
Moving to Agentic Systems
AI has long been used by banks for risk assessment, credit scoring and the automation of internal processes. Now, however, banks are building agentic systems that can string together multi-step actions. These systems analyze a client’s portfolio in real time, compare issuers’ financial metrics with macroeconomic indicators, monitor the news cycle and generate personalized recommendations. In effect, they act as investment analysts, offering portfolio-management services to a broad range of investors.
Many investors appear interested in that prospect. According to Sberbank, 1.3 million of its clients have already used AI agents for investing.
Expanding the range of AI agents could open investing to millions of people without specialized financial knowledge. That could bring additional capital into the market and, to some extent, support a goal set by Russian President Vladimir Putin in 2024: raising the capitalization of the Russian stock market to 66% of GDP by 2030. By adopting these technologies, banks are moving in line with that strategy. They are evolving from processing centers into broader financial-wellness ecosystems, while bringing new investors into the market and increasing overall liquidity.
Drivers of IT Market Growth
Sberbank plans to eventually combine its AI agents into a single service for managing investment capital. The service will be able to prepare and execute decisions independently with the user’s consent. Requiring a person to confirm every trade is intended to reduce the risk of errors and keep the system under human oversight, in line with regulatory requirements. The architecture of AI agents can also be extended to lending, insurance and personal financial planning. In the short term, these systems are expected to learn how to assess a client’s financial position, track volatility, account for taxes and suggest suitable strategies.
The growth of consumer-facing services is also giving the IT industry a boost and helping build Russia’s technological independence. The banking sector is a key customer for Russian AI developers, creating sustained demand for software, server hardware and professionals in the field. That demand, in turn, supports the development of related industries.
Growing Trust in AI
The widespread integration of AI into consumer services began with lending. In 2022, Sber introduced Kreditnaya mashina (Credit Machine), which can process up to 1.2 million applications a day. This allowed the bank to automate 99% of retail loans and demonstrated that AI platforms could handle workloads at that scale.
In 2023, the bank launched its own neural network, GigaChat, giving the market a domestic alternative to foreign LLMs that could work with context, generate code and analyze text. By 2024, Sber was already using AI in 85% of its banking processes, from customer service to internal document management.
Last year, financial companies began rolling out a new generation of AI assistants for investing. T-Bank’s investment assistant, for example, analyzed the market and answered complex queries. Meanwhile, the Intellekt (Intellect) investment service from VTB My Investments adapted its securities selection to an investor’s profile. Investors themselves were also turning to AI for advice: according to the Vyberu.ru marketplace and IT Smart Finance Group, one in three used AI to gather information about the market, while one in five trusted algorithms to select securities.
Over the next few years, AI is expected to become fully integrated into mass-market services, changing how people interact with the economy. AI assistants will become a familiar everyday tool for interacting with the financial system. Russia’s banking sector is also at the forefront of integrating AI into operational processes, creating sustained demand for large language models (LLMs), machine-learning systems, and technologies for processing and storing large volumes of information. That demand is helping drive the IT industry and becoming a new force behind the digital transformation of the national economy.
