Mandanna Appanderanda Nanaiah

Bio:
Mandanna Appanderanda’s key interests in Responsible AI center on building ethical, transparent, and accountable AI systems at scale. He focuses on governance frameworks that align with global regulations, while promoting fairness, bias mitigation, and explainability across AI models. Passionate about human-centered design, he advocates for AI that supports inclusive decision-making and safeguards human oversight. His work also explores autonomous and multi-agent AI systems, aiming to manage their complexity responsibly. At Infosys, he drives practical enterprise-wide adoption of Responsible AI, helping organizations operationalize trust and ethics through scalable tools, processes, and collaboration.

Abstract:
Scaling Responsible AI across an organization requires a balanced integration of policies, processes, and tools. Without this triad, AI adoption remains fragmented, inconsistent, and potentially risky. Policies provide the guiding principles and governance standards; processes operationalize these policies through repeatable actions and accountability structures; and tools enable automation, monitoring, and enforcement at scale. This conversation explores how Infosys successfully adopted a holistic Responsible AI framework to support its rapid expansion into Machine Learning, Generative AI, and Agentic AI applications. By embedding ethical principles into policy, establishing clear governance workflows, and deploying purpose-built tools for model evaluation, bias detection, and compliance tracking, Infosys has been able to integrate Responsible AI practices consistently across projects & programs. The organization’s approach also includes cross-functional collaboration between data scientists, legal teams, and business stakeholders to ensure that AI systems are not only technically robust but socially accountable. As AI continues to evolve into more autonomous and generative forms, Infosys’s example highlights that Responsible AI must scale as intentionally as AI itself—built into the core fabric of strategy, not bolted on as a compliance afterthought. The session offers practical insights for organizations aiming to achieve trustworthy, enterprise-wide AI adoption.