Sponsored By: Monte Carlo | Building the Foundation for Trusted AI in Regulated Industries

The enterprises with the most to gain from AI are often the slowest to deploy it, and in regulated industries, that caution is rational — the risk is real. Data quality failures don't just break pipelines in financial services — they break compliance, erode model trust, and end careers. The bar for "production-ready" AI is fundamentally different when your data touches trades, audits, or PII. In this session, Barr Moses, CEO of Monte Carlo, joins Lenny Rosenfeld, VP of Data Science & Software Engineering at Nasdaq, for a conversation on what it takes to get trusted AI into production in financial services. They'll cover AI observability, data lineage, and governance frameworks built for regulators — sharing the failures they've seen, the patterns that work, and what they'd do differently.