Too much of what gets published on AI governance either stays theoretical or gets diluted into marketing language by the time it reaches practitioners. My research work aims to close that gap.
Co-authored with Prof. Arpan Kumar Kar of IIT Delhi and published at BIGS 2025, this paper examines how organizations can move from experimental Agentic AI deployments toward governed, Retrieval Augmented Generation grounded systems that hold up under enterprise scrutiny. It addresses the governance gaps that surface once AI systems move from pilot to production, and proposes a practical framework rather than a purely academic one.
Read the paper on AIS eLibrary
Ongoing research exploring how organizations build enterprise intelligence capability that combines human expertise with AI driven decision support, rather than treating the two as separate tracks. This work informs the design of the Enterprise AI Adoption Advisor platform.
Frameworks for embedding governance and risk controls into AI systems from the start, particularly for regulated sectors such as banking, healthcare and the public sector, where governance cannot be bolted on after deployment.
Engagement through the IIT Delhi AI Leadership Program, frameworks developed through Wharton AI for Business, and continued conference publication work focused on enterprise AI transformation and responsible adoption.
I am always glad to connect with academic partners and practitioners working on responsible AI and enterprise intelligence.
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