Snyk just proved your AI security team is blind to 67% of your attack surface. And it's getting worse.

Your security team knows which AI models are approved.

They have no idea what's invoking them, what data they can reach, or what they're doing with that access.

Snyk analyzed 3,000 enterprise accounts. The result: organizations can identify only one-third of their actual AI footprint. The other two-thirds — agent frameworks, MCP servers, vector databases, retrieval systems — sit entirely outside the inventory.

This isn't a static problem. It's accelerating.

Full-stack agentic adoption doubled in six months. Among adopters, 50% now run the complete execution architecture. They went from experimenting to full production in the time it took most security teams to finish their last risk assessment.

And half of model-deploying organizations can't even trace the data that trained their models. No code-level link between production models and the datasets behind them. That's an audit and compliance problem sitting in plain sight.

The model market is fragmenting too. OpenAI's enterprise share dropped from 44% to 35%. Anthropic rose from 4% to 11%. HuggingFace is taking real share. More vendors means more attack surface means more blind spots.

Seventy-five percent of the AI supply chain comes from outside the organization. You're running a porous environment you can't see.

Audit your AI surface inventory today. If your security team can only list models, you're governing one-third of the problem. The rest is already in production.

SOURCE: https://snyk.io/news/snyk-2026-state-of-agentic-ai-adoption-volume-ii/
VERIFIED: Snyk press release (Aug 3, 2026), Morningstar/Business Wire (Aug 3, 2026), Futurum Group analysis (Aug 3, 2026)
SIGNAL: Agentic AI adoption is outpacing security governance by a factor of three. Every new AI workload expands an attack surface your CISO can't see.