AI-Driven Compliance: Building Scalable, Ethical, and Explainable Data Architectures for Regulated

About the Session

As AI adoption accelerates in regulated sectors like finance, healthcare, and government, enterprises face a dual challenge: building scalable data architectures while ensuring compliance, explainability, and ethical AI use. This session presents a composable framework that integrates AI-driven automation with strong data governance, real-time monitoring, and explainable decision-making. Drawing from real-world implementations in financial regulatory systems, the talk explores: Architecting scalable, resilient data pipelines for compliance and auditability Integrating explainable AI (XAI) modules to support transparency in decision-making Operationalizing data ethics and regulatory frameworks like GDPR, DORA, and the AI Act Balancing innovation with risk in AI adoption across global enterprises Attendees will leave with a strategic blueprint to drive ROI while future-proofing their data infrastructure against the shifting regulatory landscape.

Speaker

Bharat Chaturvedi

Driving Responsible AI Adoption in Regulated Sectors through Data Leadership