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As enterprises continue their race to deploy AI agents at scale, Gartner's latest research makes clear that runtime security for AI applications has become a board-level priority, not an optional layer. NeuralTrust has been named a Sample Vendor in the Hype Cycle for Data Security Technologies, 2026, in the AI Runtime Defense category.
The Report
Published on 23 June 2026, the Hype Cycle for Data Security Technologies, 2026 (ID G00846824) by Gartner analyst Andrew Bales maps the maturity and trajectory of the technologies enterprises need to protect their data in an AI-first world.
This year's edition reflects a significant shift: AI-specific security controls, from AI Security Posture Management to AI Runtime Defense to AI TRiSM, now occupy a central place in the Hype Cycle, reflecting the urgency with which organizations are being pushed to govern and secure their AI deployments.
The report identifies AI Runtime Defense as a High benefit technology, with market penetration currently at 5% to 20% of the target audience, a signal that adoption is accelerating and that first-mover enterprises are already building runtime protection into their AI application architecture.
What AI Runtime Defense Means
Gartner defines AI Runtime Defense as technology that "implements intent-based policy enforcement and anomaly detection for AI applications and models." It covers content inspection for AI application abuse and attacks (including prompt injection) and extends to detecting intent or content anomalies such as toxicity, hallucination, data leakage, and performance drift.
Critically, the report frames this as an evolving category. As Gartner puts it, AI runtime defense tools are evolving to protect AI agents, not just LLM chatbots. The transformation of AI applications into autonomous agents reinforces the need for runtime protection and anomaly detection, adding low-latency and low false-positive requirements that only purpose-built platforms can meet.
The drivers Gartner highlights are precisely the forces shaping every enterprise AI security conversation today:
- Cybersecurity teams now have a better understanding of the impact and requirements for AI runtime defense. As more projects approach production, AI and application teams collaborate to integrate AI runtime controls.
- As enterprise-grown AI agent projects proliferate, AI runtime defense is more often a mandatory requirement.
- Upcoming regulations, including the EU AI Act and several U.S. laws, and existing enterprise policies potentially mandate the adoption of application security practices, including preventative controls and monitoring to support risk mitigation for high-risk AI systems.
Where NeuralTrust Fits
On page 29 of the report, Gartner identifies NeuralTrust among the Sample Vendors for AI Runtime Defense, the category purpose-built to address the security challenges that emerge once AI systems move from experimentation into production.
This recognition reflects what NeuralTrust was built to do: provide enterprises with the runtime protection, observability, and behavioral governance they need to deploy AI agents at scale without sacrificing control. Our platform delivers real-time inspection of AI inputs and outputs, behavioral anomaly detection, policy enforcement at the gateway layer, and the tamper-evident audit trails that regulatory frameworks increasingly require.
The Gartner framing: evaluating providers for their "ability to serve multiple AI security use cases, in addition to specialized LLM input and output monitoring" speaks directly to the architecture we have built. NeuralTrust covers the full security lifecycle: from pre-deployment red teaming with TrustTest, to gateway-layer policy enforcement with TrustGate, to behavioral runtime detection with TrustGuard, to continuous posture monitoring and observability with TrustLens.
What This Means for Security and AI Leaders
The Hype Cycle's placement of AI Runtime Defense signals that the market is moving fast, and that the window for establishing a mature runtime security posture before regulatory and incident pressure arrives is narrowing.
Gartner's user recommendations for this category are a useful action plan for any CISO or AI security lead evaluating their current posture:
- Mandate integration with AI security testing technology to evaluate the benefits of AI runtime defense before AI application or agent deployments.
- Evaluate discovery and security posture features included in AI application security bundles offered by vendors.
- Request benchmarks, test data, and test results to evaluate the provider's commitment to quality and identify how much due diligence work will be necessary to estimate false-positive and false-negative rates.
- Develop checklists and test plans to continuously evaluate the ability of security controls to identify new attacks.
For enterprises already operating AI agents in production (and for those planning deployments in 2026) the message from this Hype Cycle is the same one we have been delivering since day one: runtime control is not something you bolt on after deployment. It needs to be part of the architecture from the start.
NeuralTrust is ready to help you build it. Get in touch with our AI Security experts.
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