Mrunal Gangrade Discusses Accountability in AI at TechX Florida 2025

We had the honor to host our esteemed speaker Mrunal Gangrade, Vice President of Software Engineering at JPMorgan Chase & CO, to deliver a session that cut straight to the biggest challenge in advanced AI adoption: Accountability in Regulated Industries.

Mrunal argued that the high accuracy of Black-Box Models (like deep neural nets) comes with unmeasured legal risk and, thus, great caution in approaching those insights.

The use of opaque "black-box" AI models in regulated sectors like finance and healthcare creates a serious Accountability Gap, as organizations are legally mandated to explain critical decisions but cannot interpret the model's logic. Failure to provide transparency violates major regulatory mandates like the GDPR, leading to massive fines and legal exposure. Therefore, implementing Explainable AI (XAI) is the necessary strategic solution to manage this uncontrolled business risk and ensure compliance.

✅ Transparency Tools: Using frameworks like SHAP and LIME to generate clear explanations for any model with additional help from Counterfactual Explanations ("Change X to get the approval").

✅ Strategic Advantage: Embedding XAI into Model Risk Management (MRM) ensures that high-performing AI might as well be legal, responsible, and sustainable.

✨ TLDR; Explainability is not just an optional compliance; it is the foundation for a trustworthy and profitable AI augmenting tool.

Sounds cool right? Stay tuned as we share with you more insights into AI applications in enterprise directly from our speakers at TechX Florida 2025:)