JavaScript Required

Jumpseat Aerospace News requires JavaScript to function. Please enable JavaScript in your browser settings to continue.

AI Security Needs Shared Language

June 15, 2026

1 min read

Key Takeaways

AI systems introduce new risks like data poisoning and model drift.
Traditional security methods are insufficient for AI threats.
Certifications like AAISM can help create a shared language for AI security.
Understanding statistics and data is crucial for AI security professionals.

Silver membership required Upgrade to Silver to access Key Takeaways.

Upgrade

Strategic Implications

The need for a shared language in AI security may indicate a growing recognition of the unique risks associated with AI systems. This could suggest a shift towards more comprehensive and specialized training for cybersecurity professionals, which may lead to improved security outcomes and better governance of AI systems.

Silver membership required Upgrade to Silver to access Strategic Implications.

Upgrade

What Happened

Cybersecurity Professionals Must Adapt To Secure AI Systems

As AI adoption scales, cybersecurity professionals must adapt to secure these systems. Traditional security methods are no longer sufficient, and new risks like data poisoning and model drift have emerged. To address these challenges, certifications like ISACA’s AAISM and frameworks such as NIST AI RMF and ISO/IEC 42001 can provide a shared language and structure for security, engineering, and business professionals. This was first reported by Infosecurity Magazine.

Source

Companies Mentioned