AI
August 18, 2025

Security Strategies Lag Behind AI Deployment

AI Adoption Far Outstrips Security Strategy Development

Organizations are embracing artificial intelligence at a rapid clip—with nearly 80% already running AI projects in production. Yet fewer than one in ten have established a security program designed specifically for AI. This discrepancy leaves most enterprises exposed to threats they are ill-equipped to detect or mitigate.

Survey Insights: Gaps in Risk Assessment and Governance

The ADVSEC AI Security Benchmark Report, drawing on input from 102 senior security leaders across North America and Europe, reveals a pronounced readiness gap. Respondents express deep concern about model manipulation, sensitive data leakage, adversarial attacks and the misuse of machine identities. Despite this, only 28% have conducted a thorough security assessment focused on AI workloads, and a mere 6% have deployed AI-native protection measures spanning both IT and AI environments. In most organizations, responsibility for AI security remains tied to traditional IT or security teams—only 10% have formed a dedicated AI security unit.

An ADVSEC employee observes: “In many cases, the foundational elements for measuring AI risks simply aren’t in place. Without tailored assessments and controls, organizations are flying blind.”

Emerging Threats from Non-Human Identities

Autonomous agents, machine accounts and other non-human identities are proliferating alongside AI initiatives. These entities leverage cryptographic credentials to access data and services, often beyond the visibility and control of existing security tools. This evolution undermines zero-trust frameworks and exposes gaps in identity governance and key management practices.

Budgets and Priorities Shift Toward AI Protection

Acknowledging these vulnerabilities, the majority of organizations intend to boost their AI security investments over the next 12–24 months. Eighty-five percent plan incremental increases, with one in four expecting substantial budget uplifts. Top priorities include:

  • Securing training datasets and inference pipelines
  • Strengthening visibility and controls around non-human identities
  • Deploying automated incident response capabilities tuned to AI-driven environments
Conclusion

The chasm between AI deployment and security preparedness introduces material business risk. Enterprises must accelerate the development of AI-specific security frameworks, establish dedicated governance models, and embed continuous monitoring across AI workflows. From ADVSEC’s perspective, now is the critical window to align security strategy with the pace of innovation before threat actors exploit these emerging gaps.

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