Sudatta Kar explains why AI-native products require intelligence to be architectural from day one, with resilient data loops, governance, and system design built in.
About Sudatta Kar
Dr. Sudatta Kar is Vice President and Head of Engineering at Capgemini Engineering in India, bringing over 30 years of engineering leadership and digital transformation expertise across global organizations including TCS, Hughes, Flextronics, Aricent, Altran, and now Capgemini Engineering. A champion of software-defined architectures, physical AI, and enterprise-scale intelligent systems, she bridges rigorous research with industrial execution to drive native engineering innovation. Sudatta holds a bachelor's in physics with Honors from Utkal University, a master's in computer application from NIT Rourkela, and an Executive MBA and PhD from IIT Delhi. A recognized thought leader, keynote speaker, researcher, and author, she serves on the NASSCOM ER&D Council and the BITS Pilani WILP Academic Strategy Advisory Board. Her work has been published across IEEE, Wiley, Springer, and leading industry platforms. She has been recognized among the Top 100 Women in Technology Leaders to Watch by Chief-In-Tech and is a passionate advocate for responsible AI, inclusion, sustainability, and continuous learning.
What motivated you to join the AI Builders Global Conference?
I am thrilled to be part of the AI Builders Global Conference 2026. What motivated me to join this community is its sharp focus on building and execution in the real world. As AI moves from experimentation to enterprise-scale impact, this conference brings together the architects, engineering leaders, and builders who are actually doing the heavy lifting; designing, deploying, and scaling robust intelligent systems in the real world. The opportunity to exchange ideas, learn from peers, and contribute to conversations shaping the future of intelligent engineering is immensely energizing.
What shaped your journey through technology and AI?
My journey spans over three decades in technology leadership, beginning with a foundation in Physics and Computer Applications, followed by an MBA and PhD from IIT Delhi. Over the years, I've had the privilege of leading large-scale engineering organizations across global companies including TCS, Hughes Software Systems, Flextronics, Aricent, Altran, and now as Vice President and Head of Engineering at Capgemini Engineering India. What inspired my evolution toward AI and software-defined systems was witnessing the fundamental shift in how products interact with the physical and digital worlds. We moved from static, code-bound systems to dynamic platforms capable of sensing, learning, and adapting. Seeing the transformative potential of integrating agentic frameworks, software-defined architectures, and edge intelligence into core engineering convinced me that the future of engineering lies in embedding intelligence at the foundational layer.
Why is AI inside important to you?
For a long time, AI was treated as a layer added in the product development lifecycle. "AI Inside" represents a critical paradigm shift: designing products where intelligence is native, architectural, and systemic from day one. Whether we are talking about enterprise software, physical AI, edge devices, or software-defined platforms, building native intelligence requires rethinking system resilience, data loops, governance, and architectural efficiency. Mastering "AI Inside" is what distinguishes resilient, scalable products from fragile demonstrations.
Who should attend the AI Builders Global Conference?
I strongly advise engineering leaders, systems architects, AI product managers, and software engineers who are tasked with delivering real-world AI solutions to attend. If your goal is to go beyond models and understand the practical engineering blueprints, architectural patterns, and governance frameworks required for resilient AI-native products, this conference is built for you. It offers actionable insights from practitioners who are navigating the exact complexities you face in production.