On-demand webinar: Rethinking fund data sourcing in the age of AI

AI and fund data – are you asking the right questions?

Artificial intelligence adoption is accelerating across investment and wealth management. Firms are already using it for reporting, fund research and comparison, and increasingly for higher order tasks like risk management and regulatory horizon scanning. Agentic AI is now moving into end to end operational automation.

Growth like this raises a harder question. In a recent FE fundinfo industry survey, 64% of respondents said their AI is only as good as the data foundation it runs on. Without a trusted, stable source of fund data, AI can compound the very risks it was meant to solve, from non-compliance to inconsistent client outcomes.

This on-demand webinar looks at what's driving AI adoption in fund data workflows, the governance questions you should be asking internally, and the questions worth putting to any data supplier before you build AI on top of their feed.

Join our product experts Kirsty Joss and Karolina Wojdyla, for a practical session covering:

• How distributors are already using AI across fund research, documentation and commentary generation
• Why data lineage and explainability are now central to AI governance
• What to ask a data provider about collection, validation and AI-ready delivery
• How FE fundinfo's data feeds are built for AI-driven workflows

Our expert speaker:

Kirsty Joss - Head of Data Distribution Solutions

Karolina Wojdyla - Product Manager, Data Feeds

What you'll learn:

- Why 64% of firms surveyed say their AI is limited by the quality of their underlying data
- What governance and explainability questions to raise internally before scaling an AI workflow
- What to ask a data supplier about lineage, validation and AI-ready delivery, including context layers and MCP
- How FE fundinfo supports AI-ready fund data across 107,000+ active funds and 70+ jurisdictions

Who should watch

• Data and operations teams building AI-driven workflows
• Distribution teams and platforms sourcing fund data for AI use cases
• Risk, compliance and governance teams assessing AI oversight