AI is changing how cyber-attacks are launched—and how they’re stopped. Yet many organizations are trying to defend against AI-driven threats with a traditional cybersecurity strategy, which will not stand the test of time in this rapidly changing landscape.
The AI security skills gap is the mismatch between the AI-enabled threats and tools your organization faces and the ability of your cybersecurity workforce to secure AI systems and use AI effectively and safely in defense. Closing this gap requires more than a generic cybersecurity strategy. It demands targeted AI security training, role-based learning paths, and a vendor-neutral AI security certification such as CompTIA SecAI+ (launching in February 2026).
What is the AI security skills gap?
The AI security skills gap is a specific part of the larger cybersecurity talent shortage. It focuses on skills related to AI in cybersecurity, including securing AI models, data, prompts, APIs, and pipelines; and detecting, investigating, and responding to AI-driven threats.
Governing AI in line with policy, ethics, and regulations. In other words, it’s the gap between the AI risk for companies and the current capabilities of their security, IT, and risk teams.
Unlike a general shortage of computer security qualifications or cybersecurity professionals, the AI security skills gap is about what cybersecurity staff know, not just how many cybersecurity staff you have.
Why is this gap different from past cybersecurity skills gaps?
As AI spreads into every part of the business, this new layer of risk touches many cybersecurity job roles and therefore requires updated IT training courses. Boards and regulators are already asking: “Who owns AI risk here, and how do you prove they’re qualified?”
Where AI security skills are missing in organizations
The AI security skills gap is not limited to one team. It cuts across:
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Risk and governance
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Security operations (SOC)
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Security engineering and architecture
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Third-party providers
Risk, governance, and AI policy
CISOs and risk leaders are often responsible for AI governance but may not have the skills to translate AI risk into board-friendly language and AI governance and compliance reporting. This can lead to gaps in security compliance certification coverage for AI use cases.
SOC, incident response, and AI-enabled tools
Security operations centers are rapidly adopting AI-driven threat detection and response, and AI-assisted threat hunting in SIEM/XDR tools. Yet many SOC analysts have limited AI security upskilling. They may struggle to identify AI-generated phishing or automated campaigns.
This is where training plans for SOC and AI security become essential. Without them, your SOC risks relying on tools they don’t fully understand.
Building an AI-ready security workforce
Closing the AI security skills gap doesn’t mean replacing your current cybersecurity certification roadmap. It means extending it with AI-specific skills and credentials that align with the roles you already have.
Organizations should define role-based AI security learning paths that clearly map AI responsibilities to existing cybersecurity job roles. Training and certifications can help build skills for roles such as those listed below.
CISOs and security leaders
Develop skills in AI risk strategy, governance, compliance, and board-level reporting. This can include executive-level training with SecAI+ for a strategic, end-to-end view of AI in cybersecurity.
SOC analysts and incident responders
Build skills to defend against AI in day-to-day operations and validate AI-defense skills with SecAI+.
Security engineers and architects
Build deep expertise in securing AI systems and integrating them into your existing stack to ensure that it secures AI architectures that align with current controls.
Risk, compliance, and governance teams
Ensure a strong understanding of AI oversight and accountability. SecAI+ can be used as the competency baseline for consistent, organization-wide AI security knowledge.
Together, these AI-focused learning paths build on traditional cybersecurity certifications (Security+, CySA+, PenTest+) to create a complete cybersecurity roadmap that fully incorporates AI.
Why vendor-neutral AI security certification matters
Many technology providers now offer AI workshops and proprietary training. Those can be valuable, but they address only the tools and platforms of a single vendor. A vendor-neutral AI security certification like SecAI+ ensures your team develops transferable, foundational AI-security skills that apply across technologies, environments, and vendors—and fits cleanly into your broader cybersecurity certification journey.
Product-specific AI content typically:
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Focuses on one platform or security product.
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Assumes AI modeling or architecture choices are already fixed.
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Doesn’t provide a big picture view of enterprise AI security across tools.
For leaders building a cybersecurity roadmap, that’s a problem. They need to know if they can compare AI security skills across teams using different tools.
CompTIA SecAI+ is a vendor‑neutral AI security certification that:
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Covers AI-security concepts and AI security best practices across platforms.
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Reflects real-world tasks and cybersecurity job types that involve AI.
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Validates that professionals can secure AI systems and use AI for cyber defense.
SecAI+ doesn’t replace foundational certifications like CompTIA Security+ or CompTIA CySA+. It extends them, in-depth, into the AI era.
How CompTIA SecAI+ helps close the AI security skills gap
CompTIA SecAI+ helps companies address the AI security skills gap directly, enabling them to build an AI-ready security workforce. Standardize AI-security‑ expectations across teams and partners to strengthen AI governance and compliance by supporting a defensible cybersecurity certification roadmap for AI initiatives.
In short, SecAI+ extends your cybersecurity certifications path into the AI era—without locking you into a single vendor.
FAQ: Common questions about the AI security skills gap
What is the AI security skills gap in organizations?
The AI security skills gap is the difference between the AI-related threats and technologies an organization faces, and its security team’s ability to secure AI systems and use AI in cybersecurity safely. It’s about specific, AI-focused skills—not just the number of security staff.
Which AI-security skills do security teams need now?
Key skills include:
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AI risk assessment and governance.
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Securing AI models, data, prompts, and APIs.
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Detecting AI-generated phishing and automated attacks.
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Investigating incidents involving LLMs and GenAI.
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Overseeing AI-enabled SOC tools responsibly.
How is AI security training different from traditional cybersecurity training?
Traditional cybersecurity training certification programs focus on networks, endpoints, and applications. AI security training adds skills to:
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Defend against AI-driven threats like adversarial attacks, automated malware, and malicious use of generative AI.
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Secure AI systems using advanced controls and protections to safeguard data, models, and infrastructure.
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Integrate AI securely into DevSecOps pipelines and enterprise security strategies.
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Use AI responsibly.
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Align with emerging AI governance regulations.
A vendor-neutral AI security certification like SecAI+ ensures professionals understand AI security best practices and can apply them across tools and environments.
CompTIA SecAI+ launches in February 2026. Reach out to an Enterprise expert to learn more!