CISO 100 celebration: Keeping up with external threats, internal expectations
Virtual
8 Oct 2026
The trust gap: Why brittle data foundations are the silent killer of agentic AI - London
London
4 Nov 2026
The Trust Gap: Why Brittle Data Foundations are the Silent Killer of Agentic AI - Amsterdam
Amsterdam
19 Nov 2026
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AI-powered data management
Surging data volumes are overwhelming traditional manual governance models. Transitioning to AI agents establishes "controlled autonomy," where automated virtual workers continuously monitor, classify, and remediate data within human-defined boundaries. This augments data stewards to focus on strategic outcomes while highlighting critical needs for system auditability and explainability.
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Building the semantic data layer for agentic AI
Agentic AI requires semantically explicit, machine-interpretable data to reason and act responsibly. Building a unified semantic layer provides critical business context, drastically boosting model accuracy while eliminating contextual blindness. Open frameworks like the Model Context Protocol (MCP) operationalise this metadata, translating rich organisational context directly for autonomous systems.