Bottom line: Most enterprises run AI inference in production without adapting their security and governance structures accordingly – a growing risk for critical systems.
The F5 State of Application Strategy Report 2026 documents that 78 % of enterprises are already deploying AI inference in production. At the same time, a dangerous gap is evident: infrastructure, security and governance are not designed for this scale.
The F5 report documents a finding with immediate implications for CTOs: 78 % of surveyed enterprises are already running AI inference in production environments. This signals that AI models are no longer an experimental domain but now support central business processes.
The problem lies in the asymmetry between adoption and preparedness. While AI models run in production, the underlying infrastructure, security controls and governance processes are often not calibrated for this deployment scale. This exposes these systems to attack surfaces and uncontrolled dependencies – with direct impact on availability, data integrity and compliance.
For CTOs, this means concretely: the previous separation between AI development and productive infrastructure must be dismantled. Models must be versioned, tested and monitored just like conventional software. At the same time, new monitoring approaches are needed for AI-specific risks such as model drift, poisoning or unauthorized access to training and inference data.
Source: itwelt.at · Published 7 July 2026
Lumi AI News — AI-assisted curation pursuant to Article 50 EU AI Act. Paraphrase and classification by Lumi News Pipeline v1.7.3.