The main trends in the development of FinTech in Ukraine and the in world in 2024 are analyzed in the article. Three areas in the FinTech development are currently identified as the most relevant: use of artificial intelligence, the latest technologies, and changes in financial services. Each area is analyzed and characterized in terms of content and development prospects. The impact of the regulator, the National Bank of Ukraine, on the activity of FinTech companies is considered separately. Plans to attract investments by Ukrainian FinTech companies in 2024 are analyzed: 45% of companies plan to develop by their own expense, and 39% plan to attract private investors’ resources. Plans for Ukrainian FinTech companies to enter the international market this year were analyzed: almost half of Ukrainian FinTech companies (47%) are already operating in international markets, and 38% plan to enter in the future. The analysis of the dynamics of the global artificial intelligence market in 2021-2023 and its forecast until 2030 shows that in 2023 the global artificial intelligence market was evaluated at about USD 200 billion. According to the Statistics Portal, this market is expected to grow significantly to almost $2 trillion by 2030. Based on the analysis of literature sources, it has been determined that new technologies that become popular in the FinTech sector will be: open banking, e-wallets, digital currencies, etc. To support their systemic development, it is necessary to use digital technologies. Thus, the article identifies promising areas of artificial intelligance use in the process of FinTech development in banking institutions: automated trading and investments (in the short term, investors will be able to focus on the development and implementation of specific strategies by outsourcing trading technologies to artificial intelligence), customer support system (text, voice, and video chatbots will be improved through integration with ChatGPT), fraud protection (automatic analysis of large amounts of data to identify potentially dangerous transactions will take much less time than manual analysis).