The AI cybersecurity buyer's guide.
Everything a company needs to know before engaging an AI cybersecurity expert — written for executives, IT leaders, and operators, not analysts.
The AI-era threat surface
Generative AI in the enterprise, autonomous agents, model and prompt risk, data exfiltration via AI tools, AI-augmented social engineering, and supply-chain compromise. The attack surface is expanding faster than internal teams can keep up.
Expert specialties to know
AI governance & policy, model and prompt security, zero trust architecture, incident response & forensics, cloud and identity security, MDR / SOC operations, and AI-aware vendor risk.
How to vet a cybersecurity expert
Look for current hands-on AI threat work, prior incident-response history, references from comparable companies, and a clear scope of engagement. Frameworks and certifications matter less than demonstrated outcomes.
Engagement models
Discrete assessments, fractional CISO / advisor roles, ongoing MDR, project-based architecture work, and incident response retainers. Match the model to the risk and tempo, not the other way around.
Why private intake matters
Your risk surface is sensitive. Sharing it across public forms or marketplaces invites the exact attention you don't want. A private NDA-gated intake is the baseline.