Swami Chandrasekaran is a technology executive with over 25 years of experience in enterprise-scale digital, AI, and cloud transformation. As Partner/Principal and Global Head of AI & Data Labs at KPMG, he leads and executes the firm’s AI strategy across Tax, Audit, Advisory, and other functions, serving 200,000 knowledge professionals worldwide. He directs and oversees various R&D efforts and initiatives covering AI architecture, advanced knowledge assistants, AI Agents, domain-tuned Small Language Models (SLMs), synthetic data, enterprise discovery and search, and hardware-optimized solutions, while also chairing KPMG's AI Technology Review Board to ensure trusted and scalable AI adoption. He further serves as Principal Investigator at the NIST AI Safety Institute Consortium, influencing global AI safety standards.
During his KPMG tenure, Swami transformed the organization's technical capabilities by establishing the Solution Architecture discipline and the Global Cloud Center of Excellence. His leadership produced award-winning innovations and products, including the Medicaid systems integration platform and an AI-enabled Intelligent Agents system that generated $100M in savings while modernizing customer service. He also directed the creation of solutions in multi-cloud FinOps, continuous compliance monitoring, continuous risk prediction, contact center modernization, and modern data platforms, working with clients in Consumer Retail, Healthcare, Global Financial Institutions, and Global Pharmaceuticals.
Before joining KPMG, at IBM he was appointed as an IBM Distinguished Engineer for his contributions toward building IBM Watson and as IBM Master Inventor for his innovations and patents. He led the development of over 100 AI solutions, helped establish IBM’s first AI Solutions Lab, and directly contributed to over $1B in revenue growth by pioneering enterprise-grade AI systems.
Swami holds more than 30 patents, has received multiple accolades—including the 2024 Consulting Magazine Technology Leadership Award—and has authored several books and articles on applied AI, SOA, and enterprise automation and integration. He earned a Master’s degree in Electrical Engineering from the University of Texas at Arlington and is committed to mentoring future STEM leaders, teaching AI programming to students, and partnering with non-profits on AI initiatives. In his personal time, he pursues creative interests in music mixing and gaming.
