AI adoption across Indian enterprises is accelerating, often across business units, data science teams, and third-party SaaS platforms. LLM-powered tools, autonomous agents, runtime MCP connections, and fine-tuned models are expanding the AI footprint beyond what traditional asset inventories were designed to capture.

The result: an AI attack surface that no spreadsheet, CMDB, or cloud dashboard can fully see.

As regulatory expectations sharpen, from CERT-IN advisories to automated decision-making obligations under the DPDP Act and heightened AI/ML oversight in banking, this visibility gap is no longer theoretical.

This session explores why conventional asset management cannot discover modern AI components, what a complete five-domain AI attack surface inventory looks like, and why visibility must precede testing, monitoring, and compliance.

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