Damodhara Reddy Palavali is a technology professional with over 15 years of experience in software engineering, cloud computing, and enterprise application development across the automotive, banking, and healthcare sectors. He has successfully led digital transformation initiatives involving full-stack development, cloud modernization, microservices architecture, and serverless solutions using AWS technologies. Throughout his career, Damodhara has contributed to large-scale enterprise projects for organizations including American Honda Motors and JPMorgan Chase, delivering scalable, secure, and high-performance software solutions. His expertise spans Spring Boot, React, AWS Lambda, API Gateway, cloud-native architectures, and real-time monitoring platforms. With more than a decade of experience in U.S. Medicaid systems, he is currently focused on applying Artificial Intelligence, Machine Learning, and cybersecurity to improve healthcare operations through intelligent automation, fraud detection, and process optimization. He is pursuing a Post Graduate Program in Generative AI and Machine Learning from the Illinois Institute of Technology to further strengthen his expertise in emerging AI technologies. An AWS Certified Developer and active technical author on DZone, Damodhara is passionate about innovation, knowledge sharing, and building next-generation enterprise solutions that create measurable business impact.  

AI-Driven Identity Security: Securing Digital Trust in the Era of Autonomous AI Agents Artificial Intelligence is rapidly changing the way organizations build and operate applications across healthcare, finance, government, and enterprise systems. As AI agents become capable of making decisions, interacting with applications, and performing tasks autonomously, traditional identity and access management (IAM) approaches are no longer enough. Organizations must rethink how identities—both human and machine—are authenticated, authorized, and continuously monitored. This presentation explores how AI-driven identity security can help organizations build a Zero Trust security model for the next generation of intelligent applications. It discusses the shift from static authentication methods to adaptive, risk-based access decisions using artificial intelligence, behavioral analytics, and continuous trust evaluation. The session will also examine practical approaches to securing AI agents, APIs, cloud-native microservices, and distributed applications while maintaining compliance and operational efficiency. Drawing on real-world experiences from healthcare modernization, financial services, and government digital identity initiatives, the presentation will cover practical implementation strategies, including secure authentication, role-based and attribute-based access control, automated certificate lifecycle management, JSON Web Key Set (JWKS) rotation, federated identity integration, and AI-assisted threat detection. It will also demonstrate how predictive analytics can help detect unusual behavior early, reduce security risks, and improve cyber resilience. The session concludes by discussing the future of AI-native identity platforms, where security decisions are made continuously based on context, behavior, and risk rather than a single login event. As organizations increasingly adopt autonomous AI systems, identity security will play a critical role in building trustworthy and resilient digital ecosystems. Attendees will gain practical insights, implementation strategies, and real-world lessons that can help them design secure, scalable, and AI-ready identity solutions for modern enterprise environments.