The European Securities and Markets Authority (ESMA) recently published a detailed analysis exploring how artificial intelligence is being adopted by European Union investment funds. The findings, released in February 2025, show that operational use of artificial intelligence is limited: among 44,000 EU funds, just 145 explicitly disclose using artificial intelligence or machine learning in their investment processes. These funds account for less than 0.1% of assets under management, totaling around €1 billion as of the second quarter of 2024. Adoption peaked in 2023 but has since plateaued, highlighting the nascent nature of artificial intelligence deployment in the European finance sector.
Asset managers primarily use artificial intelligence tools to support rather than replace human decision-making. The most prevalent applications involve generative models and large language models (LLMs) for research, risk management, compliance, and administrative tasks, rather than for core portfolio decisions. Only a small subset of funds rely on artificial intelligence as the main driver for investment choices. Performance data reveals no significant return premium for funds promoting artificial intelligence, and asset flows have been inconsistent, indicating that investors remain cautious.
Larger asset managers tend to lead experimentation with artificial intelligence, while smaller firms are hampered by costs and lack of in-house expertise. Many smaller firms rely on third-party vendors, which introduces concentration risks in the wider ecosystem. Industry surveys show most asset managers believe artificial intelligence will transform finance, but actual investment processes have been slow to adapt. The strongest uses to date involve data analysis, compliance, and productivity-focused enhancements, rather than fundamental or fully automated decision-making.
Infront contributes to this evolving landscape with its own research and product development in artificial intelligence and artificial general intelligence. The company acknowledges the utility of LLMs—such as OpenAI, Gemini, Llama, and Claude—for tasks like summarizing financial documents and providing real-time news insights, while noting their limitations in numerical precision and complex contextual reasoning. To address these gaps, Infront has developed hybrid approaches, combining LLMs with machine learning and quantitative models. Notable innovations include the Infront Professional Terminal and Investment Manager platforms, which use natural language processing to enhance news flow and analytics, and Infront Quant IQ Risk, which leverages advanced risk models. Infront’s collaborative efforts with Google on a Gemini chatbot further push the boundaries, integrating vector databases and data APIs to power real-time calculations and hinting at future agentic artificial general intelligence frameworks. Despite industry hesitation, Infront’s solutions demonstrate the potential for artificial intelligence to reshape European financial data, risk assessment, and investment research workflows.
