Mrunal Gangrade

Mrunal Gangrade

VP, Data Engineering JPMorgan Chase
Mrunal Gangrade

Mrunal Gangrade is a Vice President at JPMorgan Chase and a recognized leader in artificial intelligence, machine learning, and cybersecurity. With deep expertise in responsible and explainable AI, she builds intelligent systems that enhance digital trust, strengthen identity and access management, and improve decision-making in high-stakes financial and healthcare environments.

An award-winning technologist, Mrunal has been honored with the Women in Tech Global Award and the Best Research Paper Award at ICDPN. She is an IEEE-published author whose work includes “Fortifying Financial Transaction Security Using Artificial Intelligence and Blockchain Technology.” She also serves as a peer reviewer for international journals and conferences and frequently mentors innovators as a hackathon judge.

Mrunal is known for her clear, practical, and ethical perspective on the future of AI. Her speaking topics include explainable AI, AI governance, cybersecurity, digital trust, and human-centered automation. She engages audiences by translating complex technologies into accessible insights, inspiring leaders to adopt AI responsibly and with confidence.

Day One

12:00 PM Operationalizing AI in CX: Practical steps, risks and guardrails

Moving AI from prototype to production is where the promise of better CX meets reality. In regulated industries especially,u that journey is littered with hard constraints. In this session, Mrunal Gangrade, VP at JPMorgan Chase, will walk us through what it takes to deploy and govern AI in customer-facing environments where data privacy and cybersecurity aren’t afterthoughts but non-negotiables. Drawing on two decades of engineering experience in financial services and hands-on work moving systems to cloud and into production, we will focus on real operational challenges such as training, choosing build vs buy, spotting data drift, and putting transparency and ethics at the centre of AI deployments.

You’ll hear practical guidance on starting small, proving value, and scaling safely, including how to identify what to automate, how to embed explainability into your models, and why continuous monitoring is essential to prevent models from silently degrading.

Attendees will learn:

  • How to move from development to operationalization in a regulated environment.
  • Practical guardrails for safe AI, including explainability, continuous monitoring for data drift, and integrating ethics and security into governance.
  • How to make build vs buy decisions and prepare teams (training, tools, cross-functional governance) so AI delivers real, sustainable CX improvements.