Abhishek Goud Suragani
Abhishek Goud Suragani
Software Engineer, Independent Researcher
When AI Agents Touch Your Master Data: Governing Enterprise Data Integrity in the Age of Autonomous Systems
Enterprises are deploying AI agents faster than their data governance frameworks can keep up. Across industries — from financial services to manufacturing to healthcare — autonomous AI systems are now reading, reasoning over, and writing back to the same master data repositories that power procurement decisions, customer records, and supply chain operations. The problem is that the governance models protecting that data were built for a world where humans were always in the loop. That world no longer exists. In this keynote, Abhishek Suragani draws on research and hands-on enterprise experience to examine what happens to master data integrity when autonomous agents enter the picture — and what organizations need to do about it right now. From adversarial data poisoning and lineage forgery to unauthorized schema mutations that silently corrupt downstream AI decisions, the attack surface on enterprise master data has expanded in ways that traditional MDM platforms were never designed to handle. This session introduces a practical governance framework for the agent era — one that combines policy-enforced access control, machine learning-driven anomaly detection, and cryptographic data provenance to protect master data at the speed and scale that autonomous systems demand. Drawing on empirical evaluation across 2.4 million enterprise records and three major AI orchestration frameworks, the talk presents concrete detection rates, latency benchmarks, and architectural patterns that data and technology leaders can apply in their own environments. The session closes with a forward-looking perspective on what intelligent, self-defending master data governance looks like — and why getting this right is not just a technical problem, but a strategic imperative for any enterprise serious about trustworthy AI.