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aisecurity.llc

Survey Findings

What the primary research layer shows across all four survey instruments and the flash baseline.

Per-persona narrative

Recruiters & Hiring Managers

Staffing roles ahead of the programs

With an average maturity of 1.8/5, hiring managers are building requisitions before building programs. The hardest skills to source — prompt injection testing, agent security, secure AI SDLC — are precisely the capabilities that require program infrastructure to apply.

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CISOs & Security Leaders

Ownership fragmentation at the leadership layer

32% of security leaders report no clear AI security owner — the highest rate across all personas. Budget fragmentation mirrors this: 23% report no dedicated AI security budget, while 36% rely on informal allocations from the general security envelope.

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AI Security Engineers & Practitioners

Observed risk confirms the theoretical hierarchy

Practitioners have operationally encountered what hiring managers are trying to staff against: 49% have observed sensitive data leakage in prompts or outputs, 44% have seen insecure RAG retrieval, and 43% report poor authorization around retrieved data. These are not theoretical risks.

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Adjacent Security Engineers

A latent pipeline waiting for pathways

53% report active or near-term transition interest into AI security. But 30% cite no clear ownership structure as the reason they haven't moved yet. The workforce is willing; the organizational scaffolding is missing.

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Methodology and interpretation guidance

  • Minimum defensible sample threshold: 30 responses per persona bucket. Recommended credible baseline: 50.
  • All findings are aggregate directional signals from self-reported responses — not independent audits of individual organizations.
  • Psychometric and survey outputs reflect role-language and self-reported indicators, not individual capability diagnoses.
  • Sponsor support does not influence methodology, scoring, or editorial conclusions.
  • Cross-persona comparisons use a 12-question shared core present in all four full survey instruments.
  • Results are intended for triangulation with ATS corpus data, arXiv research signals, and GitHub tooling activity — not as standalone primary evidence.
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All findings are aggregate directional signals from self-reported responses. Not independent audit evidence. Survey data triangulates with ATS corpus, arXiv research signals, and GitHub tooling activity — it is one layer of a multi-signal validation approach.