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ai security
Your enterprise AI footprint is about three times bigger than your model list
Snyk's analysis of over 3,000 enterprise environments and 1.39 million code repositories reveals that organizations are deploying AI systems using agentic architectures that combine multiple models, agents, and external tools rather than relying on standalone models. Nearly 47 percent of organizations using AI have adopted agentic architectures built on AI agents, model context protocol (MCP) servers, or both. The study indicates that enterprises' actual AI footprint is significantly larger than the number of models they track.
Why it matters: Security and engineering leaders need visibility into their full AI deployment surface across agents, tools, and integrations, not just model inventories, to properly assess risk and compliance exposure in agentic AI architectures.
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ai security
Your enterprise AI footprint is about three times bigger than your model list
No summary had been written when this copy was frozen.
- First seen by Cybersecurity Tracker
Source attribution
Correction
Correction recorded as of .
ai security
Your enterprise AI footprint is about three times bigger than your model list
A Snyk report analyzing 3,044 enterprise environments and 1.39 million code repositories found that nearly 47% of organizations using artificial intelligence have adopted agentic architectures, combining AI agents, model context protocol servers, or both. The study indicates enterprises are shifting from standalone models to integrated AI systems, expanding their AI footprint significantly.
Why it matters: Security practitioners in enterprises using AI should assess the broader attack surface introduced by agentic architectures and interconnected AI components.
- Source published
- First seen by Cybersecurity Tracker