Turning AI from Theory into Trust, Scale and SOC Impact

Introducing Agentic Mesh & The First Productivity-Based AI for the SOC 

AI has long promised to transform security operations. Yet many SOC teams are still working through important questions: How should AI be applied? Where does it create real value? And how can it be scaled in a way that maintains trust, transparency, and control? 

Join Simon Hunt, Chief Product and Innovation Officer at Securonix, for a thought-leadership session exploring how the industry’s understanding of AI in the SOC is evolving. Rather than focusing on full autonomy, this discussion explores how thoughtfully designed, human-guided AI augmentation can provide a more sustainable path to achieving meaningful operational impact.

This session explores how a governed, agentic approach brings together coordinated AI agents, unified security data, and human-in-the-loop oversight across the full SOC lifecycle. Instead of measuring success by how much AI is deployed, leading teams are beginning to focus on outcome-driven productivity: where AI meaningfully reduces friction, returns time to analysts, and improves decision quality. 

Attendees will gain perspective on: 

• Why trust, governance, and measurement are central to scaling AI responsibly in the SOC 

• How AI augmentation can support analysts without removing human judgment or control 

• Where AI can return valuable time across detection, investigation, response, and reporting workflows 

• How productivity and measurable outcomes not AI volume are emerging as more meaningful indicators of value 

• What it takes to operationalize AI safely in regulated, real-world environments 

This session is not a product deep dive. It is a practical, forward-looking discussion on how security leaders can rethink AI adoption, align it to operational outcomes, and build SOC capabilities that are both innovative and accountable.