At the end of September 2025, Brussels hosted the EFPA Think Tank 2025, which was held on the occasion of the 25th anniversary of EFPA Europe. This year we focused on AI and its use in the financial advisory business. The original topic AI: Large Language Models and the Financial Advisor was divided into three sub-topics and subgroups, where the participants formulated their research questions, gathered evidence and provided their conclusions, which are summarized below.
Topic 1: Ethical and Regulatory Considerations
AI introduces new dynamics in the Financial Advisor value chain, reshaping relationships with clients and AI providers. However, the social relationship between the advisor and the client remains unchanged. AI exists to enhance, never replace, professional judgement and the ethical principles of the EFPA Code of Ethics continue to apply in full: client centricity, transparency, fairness and above all, human oversight and professional accountability for all advice provided.
Drawing insights from 19 interviews (including AI experts, ethicists, academics and practitioners) the consensus is that advisors should never rely on general consumer tools such as ChatGPT or Gemini to inform financial recommendations. These cannot satisfy the regulatory requirements for explainability, privacy, safety and reliability. Instead, advisors should use domain-specific AI solutions designed to meet regulatory standards and keep data stored within the organisation.
In addition, AI literacy is crucial as a first line of defence, ensuring advisors understand how the technology works, its limitations, and critically evaluate its outputs. This should be supported by governance mechanisms that document how AI is used in each investment recommendation, along with the client’s acceptance. Much like an aircraft’s “black box,” this record should capture what has been done, the rationale behind it, and what was deliberately not done, while ensuring client privacy is protected.
Before adopting any AI tool, the first question should always be ‘why’, clearly defining the problem it aims to solve and assessing whether it genuinely adds value for the client. Responsible AI adoption ultimately depends on combining robust due diligence of vendors, regulatory compliance and strong ethical principles. When these work together, AI becomes a powerful tool for enhancing, not diminishing, the trusted advisor-client relationship.
Topic 2: AI Integration and Best Practices
The integration of Artificial Intelligence (AI) into financial advisory represents a transformative opportunity to enhance personalization, efficiency, and transparency across the profession. When applied responsibly, AI can support advisors in creating more tailored investment strategies, improving client profiling and risk assessment, optimizing portfolio allocations, and streamlining the financial planning process. However, human judgment and personal relationships remain at the heart of quality advice, and AI should be viewed as a powerful assistant, not a replacement, for professional expertise.
To ensure ethical and compliant implementation, we emphasize the importance of high-quality data governance, adherence to GDPR and other regulatory standards, and the use of transparent, explainable AI models. Advisors and institutions must prioritize continuous education, enabling professionals to understand both the capabilities and limitations of AI tools. Clear corporate guidelines, practical training, and safe experimentation will foster trust and help advisors adopt AI effectively while protecting client privacy.
Ultimately, AI should serve to strengthen, not substitute, the human element in financial advice. If the AI technologies adoption is done responsibly and with professional ethics, it will protect client interests and enhance the value and trust of financial advice across Europe.
Topic 3: Impact of AI on the Financial Advisor Profession and Future Outlook
This topic focused on providing a comprehensive overview of the impact and implications of Artificial Intelligence (AI) adoption within the financial advisory industry, comparing the perspectives of AI models (Grok, Copilot, Claude, ChatGPT) with human brainstorming insights. We try to identify how AI could help financial advisors in their job, so we focused on AI’s role in risk and market prediction, on AI impact on financial advisor job roles, and AI’s influence on advisor-client relationship and future AI implications.
From the point of risk and market prediction, AI’s core value is its ability to process vast datasets, detect new correlations, and monitor markets in real-time. AI models primarily focus on technical applications such as predictive analytics and sentiment analysis, stress tests, anomaly detection, and dynamic portfolio optimization. On the other hand, the quality of the output can be impacted by human/organizational factors such as the risk of over-reliance on AI (“lazy advisors”), unpredictable discontinuities such as black swan events, errors in model verification and potential negative impacts on client trust.
AI plays and will continue to play a important role in financial advisor´s job, such as by automating routine tasks. From an optimistic point of view, AI will act as a “co-pilot,” freeing advisors for high-value tasks like empathy, trust-building, and strategy. It will lead to new hybrid roles (e.g., AI ethics specialists) and emphasize upskilling. More pessimistically, there may potentially be reductions in employment opportunities, especially for analysts and those performing routine tasks. Some clients may prefer cheap AI-only services, and over-reliance on AI could lead to negative implications for human creativity.
In the future, AI could change the relationship between clients and advisors, in positive but also negative ways. The consensus supports an “augmented advice” model that combines algorithmic precision with human empathy. Ultimately, most people seek verification from a human advisor, which underscores the need for human involvement to preserve emotional and ethical support. Hybrid roles are expected to become dominant. Early AI adopters will thrive, while others risk obsolescence. From the client’s point of view, AI is projected to become the leading source of investment advice in the near future, offering greater inclusion but potentially leading to trust gaps. AI bring some advantages, like companies gain enhanced operational efficiency, innovation in risk management, and revenue boost through scalability and cost reductions. On the other hand, a big issue is that companies face the need for high initial investments and must manage new and evolving cyber risks and data security concerns. In the long term, ethical and regulated AI implementation will be crucial for firms to gain trust and provide market leadership.