THE 7 QUESTIONS EVERY FEDERAL CISO SHOULD BE ASKING ABOUT AI RISK

If you're a federal CISO in 2026, you're managing a security environment that looks fundamentally different from what it did three years ago. AI systems are being deployed across your agency — some with your knowledge, some without. And the frameworks you've relied on for decades weren't designed to govern them.

FISMA, NIST RMF, FedRAMP — these are essential. But they don't answer the questions that AI systems raise. Questions about algorithmic bias. About training data provenance. About what happens when an AI system makes a consequential decision that no human reviewed.

"Your security posture is only as strong as your weakest AI system. And right now, most federal CISOs don't know where all their AI systems are."

The 7 Questions

1. Do you have a complete inventory of AI systems in use across your agency?

OMB AI policy requires federal agencies to maintain an AI use case inventory. But beyond compliance, this is a fundamental security question. You cannot govern what you cannot see. Shadow AI — AI tools adopted by individual teams without IT or security review — is one of the fastest-growing attack surfaces in the federal environment.

2. Have you assessed the security controls of your AI vendors?

AI vendors introduce a new category of third-party risk. Traditional vendor assessments focus on data handling, access controls, and incident response. AI vendor assessments must also address model security, training data integrity, adversarial robustness, and the vendor's own AI governance practices.

3. What is your policy for AI-generated content in official communications?

Federal agencies are using AI to draft reports, summarize documents, and generate communications. Without a clear acceptable use policy, you're creating liability — and potentially, a security gap. AI-generated content can contain hallucinated facts, embedded biases, and in some cases, sensitive information from training data.

4. How are you managing AI-specific insider threat risks?

AI systems create new insider threat vectors. An employee with access to a generative AI tool can exfiltrate sensitive information through prompt engineering in ways that traditional DLP tools won't catch. Your insider threat program needs to account for AI-enabled data extraction.

5. Have you integrated AI risk into your existing RMF process?

NIST has published AI RMF guidance specifically designed to complement the existing Risk Management Framework. If your agency is running AI systems through a standard RMF authorization process without AI-specific controls, you have a gap. NIST SP 800-218A and the AI RMF Playbook provide the bridge.

6. What is your incident response plan for an AI system failure?

AI system failures don't look like traditional security incidents. They can manifest as biased outputs, degraded performance, adversarial manipulation, or unexpected behavior at scale. Your incident response plan needs AI-specific playbooks — including who has authority to shut down an AI system and under what conditions.

7. Are you prepared to brief your leadership on AI risk in plain language?

Agency leadership, IG offices, and congressional oversight committees are asking about AI risk. If you can't explain your AI risk posture in plain language — without jargon, without hedging — you're not ready. The CISO's role in AI governance is increasingly a communication role, not just a technical one.

What To Do Next

These seven questions are a starting point, not a checklist. Each one opens into a deeper set of governance, policy, and technical requirements that take time and expertise to address. The organizations that are getting ahead of AI risk are the ones that started the conversation early — before an incident forced their hand.

• →Conduct an AI use case inventory — know what's deployed and by whom
• →Integrate AI-specific controls into your existing RMF authorization process
• →Develop an AI acceptable use policy that covers generative AI tools
• →Assess your top 5 AI vendors against AI-specific security criteria
• →Build AI incident response playbooks into your existing IR program