Sharmistha Chatterjee
Data/AI Thought Leader
2X google Developer Expert-Cloud & AI/ML
Session at World AI Summit 2026
Sharmistha Chatterjee is a confirmed speaker at World AI Summit 2026, 14-15 October 2026, Sheraton Grand Bangalore Hotel at Brigade Gateway, Bengaluru, India. Session title, time and hall will be published on this page once the agenda is final.
About Sharmistha Chatterjee
Sharmistha Chatterjee is a Data and AI thought leader with more than 20 years of experience across data science, machine learning, cloud technologies and enterprise AI. She has worked across Fortune 500 organisations and technology environments, with a focus on taking AI solutions from research and experimentation to scalable production systems.
She has held senior leadership roles in data and AI, including Vice President, Data & AI/ML Shared Capabilities, Digital Workplace at American Express, where she has been responsible for data strategy, analytics capabilities, data governance and the evolution of AI/ML platforms for the Digital Workplace. Before American Express, she was Senior Vice President at Commonwealth Bank of Australia, leading Advanced Analytics and ML Operations.
A 2X Google Developer Expert in Cloud and AI/ML, Chatterjee is also an international speaker, mentor and author. Her areas of expertise include Generative AI, machine learning, cloud AI, data strategy, AI platforms, data governance and responsible AI. She has been recognised by Analytics India Magazine among its 40 Under 40 Data Scientists and has also been recognised by Google among its technology trailblazers.
Chatterjee is also a co-author of Platform and Model Design for Responsible AI, which explores approaches to building resilient, private, fair and transparent machine learning systems. Her work reflects a strong focus on connecting technical innovation with responsible and practical enterprise AI adoption.
About Her Work in AI
Chatterjee's work sits at the intersection of AI research, enterprise implementation and responsible technology. She has consistently focused on bridging the gap between AI theory and real-world deployment, while highlighting the importance of governance, human oversight and scalable technology foundations as organisations adopt AI.