Deploying Privacy-Preserving Generative AI from Edge to Enterprise

Santosh Kumar, Technical Leader – AI at HCLTech USA, presents "Deploying Privacy-Preserving Generative AI from Edge to Enterprise." Timestamps: 00:05 Intro: The Challenge of Responsible GenAI Deployment 01:41 4 Critical Deployment Challenges (Latency, Leakage, Silos, Sensitivity) 03:22 The Privacy-Preserving Architecture Overview 04:58 Pillars: Federated Learning + Differential Privacy 06:28 Real-World Healthcare AI Example (HIPAA Compliance & Trust) 08:00 XAI & Compliance: Explanability for Audits (GDPR, ISO) 09:52 Future Outlook: Multimodal & Self-Regulating AI The rapid evolution of Generative AI is reshaping industries, yet real-world deployment demands more than just powerful models—it requires trust, scalability, and domain alignment. This talk explores how to architect and operationalize trustworthy generative AI systems across enterprise and healthcare environments, from cloud to edge. Drawing on extensive AI leadership experience, the session unpacks practical frameworks for deploying transformer-based models, federated learning architectures, and privacy-preserving GenAI applications that align with regulatory and ethical imperatives. Attendees will gain insights into designing secure, explainable AI systems that address real-world challenges such as electronic health record summarization, predictive diagnostics, claims optimization, and enterprise document intelligence. The talk also highlights strategies for achieving model robustness, transparency, and policy compliance—key pillars for responsible AI adoption. Whether scaling GenAI in production or exploring edge-AI opportunities, this session provides a blueprint for building AI that is not only powerful but also purposeful. This video is an official session recording from the Applied AI Summit 2025, hosted by John Snow Labs. Connect with us: Our website: https://www.johnsnowlabs.com/ LinkedIn:   / johnsnowlabs   Facebook:   / johnsnowlabsinc   X: https://x.com/JohnSnowLabs #PrivacyPreservingAI #FederatedLearning #MedicalAI #GenerativeAI #DifferentialPrivacy #SecureAI #EnterpriseAI #ResponsibleAI #HIPPA #EdgeAI #DataSecurity