How to Build Your First GRC Agent: A Red Teamer's Guide

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The term “agentic” is increasingly prevalent in discussions around governance, risk, and compliance (GRC), yet many vendors struggle to articulate how this approach fundamentally alters traditional practices.

The Shift to Agentic Systems

Drawn from years of offensive security experience, including red and purple team operations, the author highlights recurring vulnerabilities in GRC frameworks that persist across organizations. The shift toward agentic systems represents a critical evolution in how compliance and risk management are executed, moving away from static, schedule-driven processes to dynamic, context-aware workflows. This transformation is not speculative but rooted in the realities of modern infrastructure, where cloud environments, identity systems, and continuous integration/continuous deployment (CI/CD) pipelines operate in real time.

Agentic Systems: Key Differences

Agentic systems differ from conventional automation in three key aspects. First, they operate with autonomy, initiating actions based on predefined conditions rather than relying on manual triggers. Second, they maintain contextual awareness, analyzing the current state of an organization’s security posture instead of relying on outdated snapshots. Third, they execute multi-step workflows, enabling analysis, decision-making, and remediation without requiring human intervention for each stage.

Autonomy in Action

These capabilities align with the evolving nature of digital ecosystems, where systems like cloud infrastructure, identity management, and AI-driven processes are inherently fluid and non-deterministic.

Contextual Awareness

The integration of artificial intelligence into GRC is not a replacement for human judgment but a tool to enhance it. While machines excel at handling repetitive, high-volume tasks against established baselines, critical decisions about policies, thresholds, and risk assessments must remain in human hands.

Multi-Step Workflows

This approach mirrors existing AI applications in cybersecurity, such as anomaly detection and alert prioritization, where machines augment analyst capabilities rather than supplant them. The goal is to free practitioners from mundane tasks, allowing them to focus on strategic, judgment-based work.

Building an Agentic GRC System

Building an agentic GRC system involves three core steps. First, defining a trigger that initiates the agent’s workflow, whether based on time intervals or specific events. Second, specifying the task in natural language, akin to directing a junior analyst. For example, an agent could monitor multifactor authentication (MFA) policies for compliance with ISO 27001:2022 control A.8.5, automatically identifying deviations and initiating remediation. Third, deploying the agent with a comprehensive audit trail to ensure transparency and accountability.

Reshaping Traditional Roles

The transition to agentic GRC reshapes traditional roles and processes. Analysts shift from data collection to oversight, while compliance moves from periodic assessments to continuous monitoring. This shift introduces new challenges, particularly around trust in automated decisions. Observability is critical, with execution logs capturing every step of an agent’s workflow—trigger events, data sources, evaluation criteria, decisions, and actions taken.

Ensuring Accountability

These logs enable post-hoc verification, ensuring accountability without relying on opaque algorithms. Security professionals may rightly question the reliability of automated systems, but agentic GRC is designed to be defensible. Agents operate with least privilege, limiting their access to read-only data and restricted write permissions for GRC-specific actions.

Human Oversight

High-impact decisions, such as risk closure or control validation, require human approval, ensuring that automation supports rather than replaces human oversight. Implementation strategies emphasize starting with low-judgment, high-toil tasks, such as identifying evidence gaps or automating report analysis.

Future of GRC Tools

The author stresses that the goal is not to automate every process but to align tooling with the dynamic nature of modern systems. The evolution of GRC tools must keep pace with the environments they govern. Agentic systems represent a step toward this alignment, enabling organizations to address compliance and risk management in real time.

By prioritizing transparency, accountability, and human oversight, these systems offer a practical path forward for enterprises navigating increasingly complex digital landscapes.