Abhradeep Chatterjee

From AI Pilots to Production Intelligence: Building Trustworthy and Resilient Enterprise Systems

Abstract:

Artificial intelligence has rapidly evolved from experimentation to enterprise adoption. Yet, many organizations continue to struggle with transforming successful AI pilots into scalable, sustainable business outcomes. While proof-of-concepts often demonstrate technical feasibility, production deployment introduces challenges related to governance, trust, integration, security, operational resilience, and measurable value realization.

This keynote explores how enterprises can move beyond isolated AI initiatives toward production intelligence, where AI capabilities are embedded into operational workflows and decision-making processes. The session will discuss the role of predictive analytics, observability, intelligent automation, human-in-the-loop governance, and continuous learning in enabling scalable and resilient enterprise operations.

Particular emphasis will be placed on trustworthy AI. As intelligent systems increasingly influence operational decisions, organizations must ensure that AI-driven actions remain explainable, auditable, policy-governed, and risk-aware. Practical approaches for responsible AI adoption, including confidence-based decisioning, approval workflows, operational safeguards, rollback mechanisms, and outcome-driven performance measurement, will be presented.

Drawing upon large-scale enterprise transformation experiences, this keynote will provide a pragmatic roadmap for operationalizing AI at scale. The central message is that the future of applied intelligence will be defined not only by increasingly capable models, but by the ability to deploy AI responsibly, reliably, and in alignment with business objectives.

Brief Profile:

Abhradeep Chatterjee is an Associate Director at NTT DATA, USA, with over 15 years of experience in enterprise AI transformation, operational intelligence, intelligent automation, AIOps, cloud operations, and resilient enterprise systems. His work focuses on helping organizations transition from reactive operations and isolated AI initiatives to governed, predictive, and production-scale AI capabilities.

He is an IEEE Senior Member, MIET, researcher, invited speaker, international judge, technical program committee member, and reviewer for leading journals and conferences in artificial intelligence and applied computing. His research and professional contributions span AI-driven operations, autonomous remediation, enterprise reliability, digital transformation, and trustworthy AI-enabled decision support systems.