Sneh

AI is getting more autonomous, and that's both exciting and challenging. What happens when AI systems start making decisions on their own? Who's accountable when things go wrong? And how so we manage the risks without slowing down innovation? If you've been wondering about these questions, this session is for you.

As someone working in AI agents and product development, I've been diving deep into AI governance frameworks to understand what's actually required. In this session, we'll explore the key concepts from AI governance - what makes AI different from traditional software, the risk-based approaches organizations are using, and what's happening in the regulatory landscape with frameworks like the NIST AI RMF and the EU AI Act. 

This session is for anyone curious about AI governance, and seeking to understand how to build AI systems responsibly - as it explores how organizations can manage risk, accountability, and oversight in increasingly autonomous and agent-driven AI systems.

Biography:

Sneh Lata, SMIEEE, AIGP

Sneh Lata is a certified AI Governance Professional (IAPP AIGP) and IEEE Senior Member specializing in AI governance, responsible AI development, and cloud innovations. She holds certifications in AI governance from the University of Oxford, NIST AI Risk Management Framework, and ISO/IEC 42001, along with technical credentials in Oracle Cloud Generative AI, Google Cloud AI Applications, and IBM AI Agents.

Currently serving as Director of Products at RChilli Inc., Sneh combines her Certified Scrum Product Owner (CSPO) background with deep AI governance knowledge to bridge the gap between technical implementation and regulatory requirements. She holds a degree from Delhi University, has completed executive education at UC Berkeley, and actively contributes to the AI governance community through IEEE.

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