Financial institutions are moving AI from experimentation into decisions with real consequences, and that shift raises a harder question than which model to use: whether an institution's data, its governance, and its infrastructure are ready for AI that acts rather than advises. Much of the answer sits in the data itself: what an agent is allowed to reach, where that is enforced, and whether it still holds once the data has been copied somewhere for a model.
Join leaders to discuss how that trust gets built in an industry defined by regulation, legacy systems, and low tolerance for error. Expect an honest look at what's working, what isn't, and where the industry still has hard problems left to solve.
