By 2030, guardian agent technologies will account for at least 10 to 15% of agentic AI markets, according to Gartner.
Guardian agents are AI-based technologies designed to support trustworthy and secure interactions with AI. They function as both AI assistants, supporting users with tasks like content review, monitoring and analysis, and as evolving semi-autonomous or fully autonomous agents, capable of formulating and executing action plans as well as redirecting or blocking actions to align with predefined agent goals.
Guardrails Are Needed as Agentic AI Usage Continues to Grow
According to a Gartner May 19, 2025 webinar poll of 147 CIOs and IT function leaders, 24% of respondents had already deployed a few AI agents (less than a dozen) and another 4% had deployed over a dozen.
The same poll question found that 50% of respondents said they were researching and experimenting with the technology, while another 17% of respondents said that they had not done so, but planned to deploy the technology by the end of 2026 at the latest. Automated trust, risk and security controls are needed to keep these agents aligned and safe, accelerating the need for and rise of Guardian Agents.
“Agentic AI will lead to unwanted outcomes if it is not controlled with the right guardrails,” said Avivah Litan, VP Distinguished Analyst at Gartner. “Guardian agents leverage a broad spectrum of agentic AI capabilities and AI-based, deterministic evaluations to oversee and manage the full range of agent capabilities, balancing runtime decision making with risk management.”
Risks Increase as Agent Power Increases and Spreads
Fifty-two percent of 125 respondents from the same webinar poll identified that their AI agents are or will primarily focus on use cases related to internal administration functions such as IT, HR, and accounting, while 23% are focused on external customer facing functions.
As use cases for AI agents continue to grow, there are several threat categories impacting them, including input manipulation and data poisoning, where agents rely on manipulated or misinterpreted data. Examples include:
- Credential hijacking and abuse leading to unauthorized control and data theft.
- Agents interacting with fake or criminal websites and sources that can result in poisoned actions.
- Agent deviation and unintended behavior due to internal flaws or external triggers that can cause reputational damage and operational disruption.
“The rapid acceleration and increasing agency of AI agents necessitates a shift beyond traditional human oversight,” said Litan. “As enterprises move towards complex multi-agent systems that communicate at breakneck speed, humans cannot keep up with the potential for errors and malicious activities. This escalating threat landscape underscores the urgent need for guardian agents, which provide automated oversight, control, and security for AI applications and agents.”
CIOs and security and AI leaders should focus on three primary usage types of guardian agents to contribute towards safeguarding and protecting AI interactions:
- Reviewers: Identifying and reviewing AI-generated output and content for accuracy and acceptable use.
- Monitors: Observing and tracking AI and agentic actions for human- or AI-based follow-up
- Protectors: Adjusting or blocking AI and agentic actions and permissions using automated actions during operations.
Guardian agents will manage interactions and anomalies no matter the usage type. This is a key pillar of their integration, since Gartner predicts that 70% of AI apps will use multi-agent systems by 2028.
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