AI Security Lags Dangerously Behind Adoption Rates, New Report Reveals

Enterprise artificial intelligence deployment is rapidly outpacing security measures, creating significant vulnerabilities across organizations, according to SandboxAQ's 2025 AI Security Benchmark Report. While 79% of organizations are using AI in production environments, only 6% have implemented comprehensive AI-native security protections.

The gap between AI adoption and cybersecurity infrastructure implementation presents an unprecedented risk to enterprise systems, with non-human identities (NHIs) emerging as a critical vulnerability. These autonomous AI agents, APIs, and machine accounts often operate without proper oversight or controls, threatening established Zero Trust security frameworks.

Current State of AI Security

The benchmark report highlights alarming statistics about organizational readiness for AI security:

• Only 10% of organizations have dedicated AI security teams
• Just 28% have completed AI-specific security risk assessments
• 85% plan to increase investments in AI security infrastructure and resources in the next 12-24 months

"This isn't just a solution gap, it's a conceptual one," explains Marc Manzano, General Manager of the Cybersecurity Group at SandboxAQ. "AI is radically changing the cybersecurity paradigm at an unprecedented speed."

The Growing NHI Challenge

A companion report from Entro Security reveals the escalating scale of non-human identity management challenges:

• NHI-to-human ratios grew 56% in one year, from 92:1 to 144:1
• 44% year-over-year growth in total NHIs
• 8.7% of NHIs are overprivileged and idle
• One in 20 AWS machine identities have full-admin privileges

Security experts express particular concern about the longevity of these digital identities. "7.5% of NHIs live 5-10 years, with some exceeding a decade. These identities often outlive their intended function and their human owners," notes the report.

Practical Implications for Organizations

Organizations must develop comprehensive AI security strategies and frameworks to address these emerging threats. Security leaders recommend several key actions to address the AI security gap:

1. Implement AI-specific threat modeling that includes inference APIs, training pipelines, and LLM agents
2. Establish comprehensive NHI governance and monitoring systems
3. Conduct dedicated AI security assessments beyond traditional vulnerability scanning
4. Prepare for quantum-resilient security measures

"Protecting NHIs starts with applying the same controls used for human users," advises Shane Barney, CISO at Keeper Security. "This includes managing access through least privilege, automating credential rotation, and auditing usage regularly."

The findings underscore the urgent need for organizations to bridge the gap between AI adoption and security measures. As AI deployment continues to accelerate, the security industry must develop new frameworks and tools specifically designed for AI-driven infrastructure protection. For more information on emerging AI security threats, visit the NIST Artificial Intelligence Risk Management Framework.