Source: Pisaneschi, B., 2025, Agentic AI For Finance: Workflows, Tips, and Case Studies:
In many ways, this evolution simply extends the multihoming strategy, combining multiple tools and platforms into a single user interface. Claude for Financial Services reflects this approach, connecting with market databases and traditional platforms like Excel to produce reports and analyses for the user. In this way, AI functions as an application layer on top of other software tools, interfacing with the human analyst who retains oversight and accountability.
Professional judgment remains essential to test assumptions and validate data sources and references. Moreover, effective use of these tools also depends on strong foundational knowledge in finance and investing, enabling analysts to trust and own model outputs and maintain a reasonable basis for investment decisions.
Professionals will also need soft skills that cannot be outsourced to machines, including relationship-building and exercising duties of loyalty, prudence, and care, grounded in ethical values.
Going forward, CFA Institute will conduct in-depth research on workflows and skills as AI reshapes the investment profession. While the mix of tasks and the skills needed to perform them will undoubtedly continue to evolve, and in ways we may not foresee, we expect the AI+HI principle to remain the foundation of ethical professional practice and sound investment management.
We invite practitioners to share their thoughts in the Comments section on the skills and workflow shifts you are observing.
[1] Our research inventory on AI includes:
AI in Asset Management: Tools, Applications and Frontiers
AI Pioneers in Investment Management (2019)
T-Shaped Teams: Organizing to Adopt AI and Big Data at Investment Firms (2021)
Ethics and Artificial Intelligence in Investment Management: A Framework for Professionals (2022)
Handbook of Artificial Intelligence and Big Data Applications in Investments (2023)
Unstructured Data and AI: Fine-Tuning LLMs to Enhance the Investment Process (2024)
AI in Investment Management: Ethics Case Study (2024); AI in Investment Management: Ethics Case Study Part II (2024)
Creating Value from Big Data in the Investment Management Process: A Workflow Analysis (2025)
Synthetic Data in Investment Management (2025)
Explainable AI in Finance: Addressing the Needs of Diverse Stakeholders (2025)
Automation Ahead: Content Series (2025)
[2] See for example Tierens, I., 2025, AI Can Pass the CFA® Exam, But It Cannot Replace Analysts
[3] An interactive version of this data is available on our RPC Labs GitHub repository: