Gartner® Innovation Insight: AI Application Security
AI-enabled applications and agents introduce new risks that traditional application security tools weren’t built to address. Gartner explains why AI application security is emerging - and what capabilities organizations should evaluate.
By 2028, at least 50% of organizations that operate public-facing AI-enabled applications will use AI application security capabilities to protect them.
Anchor: what-you-ll-learn
What You'll Learn In this report, Gartner explores:
Why generative AI applications introduce new risks such as prompt injection and excessive agency
How AI application security combines security testing and runtime defense
The importance of discovery and inventory in identifying rogue or unauthorized AI applications
Why evaluating AI security tools is challenging due to nondeterministic behavior and noise
Key criteria for assessing runtime detection accuracy and remediation capabilities
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Anchor: our-perspective
Our Perspective Protect every AI agent you build and run. AI security must operate across development and production. A modern AI defense model includes continuous testing, centralized discovery, and runtime enforcement - enabling security teams and engineers to innovate safely without slowing down deployment.
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Source: Gartner, Innovation Insight for AI Application Security, Dionisio Zumerle, Jeremy D’Hoinne, Meghan Hollis, 8 January 2026.GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates and is used herein with permission. All rights reserved. Gartner does not endorse any vendor, product or service depicted in its research publications and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research.
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