Why AI Features Don’t Equal Better Vulnerability Management

AI is becoming table stakes in vulnerability and exposure management, at least in vendor messaging. Autonomous agents, instant prioritization, and self-healing security sound compelling. But many security teams are left asking a simpler question. Does this actually reduce risk, or does it just add complexity and false confidence? 

In this candid conversation, Chris Ray, Field CTO at GigaOm, and Will Gorman, CTO and leader of AI initiatives at Nucleus Security, challenge the assumption that more AI automatically leads to better outcomes. 

They break down where AI genuinely improves vulnerability and exposure management, and where it often falls short. The discussion focuses on practical use cases like prioritization, triage, and workflow automation, and calls out common failure modes such as amplifying bad data, obscuring ownership, or masking weak execution. 

Drawing on real enterprise experience, the conversation moves beyond feature claims to focus on what works at scale across teams, tools, and operational realities. 

You will walk away with: 

• A practical way to evaluate AI claims in vulnerability and exposure management and spot hype early 

• Clear guidance on where AI improves prioritization and workflows, and where traditional or hybrid approaches still make sense 

• A realistic picture of what strong execution looks like in AI-enabled vulnerability management, including ownership and accountability 

This webinar is for security leaders who want fewer promises, more proof, and measurable risk reduction instead of buzzwords.