AI adoption is a security survival metric

AI is increasingly shifting from an experimental, externally consumed service to core infrastructure that organizations customize, integrate, or build themselves, according to Sysdig’s 2026 cloud-native security data. The analysis found substantial growth in AI and machine-learning packages, including sixfold growth in ML packages, 14-fold growth in OpenAI packages, and 40-fold growth in Anthropic packages, indicating deeper operational adoption. Although usage is expanding, consolidation into internally managed model infrastructure may reduce exposure by replacing numerous AI tools and APIs with fewer, more manageable resources; public exposure remained at 1.5% for AI and ML packages, while only 0.05% of resources were publicly exposed. B2C industries such as media, transportation, and retail are leading adoption because AI directly affects customer experience and revenue, while B2B organizations commonly apply it to productivity, analytics, automation, and support. EMEA also leads regional adoption, potentially aided by clearer EU regulation, data sovereignty needs, and compliance requirements. In cybersecurity, AI is becoming essential for both attackers and defenders, with malicious actors using it for autonomous ransomware, rapid account takeovers, and exploiting vulnerabilities, while security teams use ML, large language models, and agentic systems for detection, remediation, automated response, and investigations.

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