The Association of Ukrainian Banks held a webinar on the application of artificial intelligence in the financial sector. AI expert Mykhailo Patsan discussed practical examples of how the technology is being used in banks and explained how the role of artificial intelligence in business has evolved in recent years.
According to him, today artificial intelligence is increasingly viewed not merely as a tool, but as a digital assistant that can be entrusted with specific tasks. In various companies, such systems are called assistants or agents, but the essence is the same—these are technologies capable of performing tasks assigned to them by humans.
“While AI was previously used mainly for text generation or information retrieval, systems are now emerging that can independently perform an entire chain of tasks,” explained Mykhailo Patsan.
The rapid pace of AI development is particularly evident when looking at changes over just the last three years. In 2023, most users were introduced to generative AI—primarily ChatGPT versions 3 and 3.5. The model generated text by predicting the next word, but it had significant limitations: it could make mistakes, “hallucinate,” and did not always have sufficient context.
In 2024–2025, AI assistants marked the next stage of development. These are corporate systems designed to help employees complete work tasks. One of the best-known examples is Microsoft Copilot, which can analyze documents, search for information within the company, and assist employees in their daily work.
In 2026, a new stage in the development of the technology began to take shape—agent-based artificial intelligence. Unlike assistants, such systems can independently perform more complex tasks: launch tools, analyze results, and make decisions without constant human involvement. One example of such systems already on the market is OpenClow.
For the financial sector, the development of artificial intelligence opens up new opportunities—from automating operational processes to improving customer service and risk management. At the same time, according to Patsan, the technology is evolving so rapidly that approaches considered innovative just a year ago may already be losing their relevance today. That is why it is important for banks not only to implement individual AI tools but also to develop a long-term strategy for working with this technology.
