🤖 AI Agents as the next GRC Frontier

Let's be honest - GRC has a perception problem. People see it as the "checkbox team" or the folks who just get you that SOC 2 report. But here's what's interesting: after chatting with Shruti Gupta on our latest episode, it's clear this perception is about to get flipped on its head.

Why This Episode Matters

Shruti isn't just another GRC leader - she's been in the trenches at Microsoft Identity, Brex, Instacart, and Airbnb. When someone who's built security programs at these companies says GRC is "one of the hardest parts of cybersecurity," you better pay attention. 🎯

Understanding GRC's Complex Reality

The conversation with Shruti revealed how GRC professionals navigate an intricate landscape that few truly understand. Unlike other security domains that can focus deeply on specific technical areas, GRC requires both breadth and depth across multiple domains:

• Infrastructure teams need guidance on cloud security controls.

• Data teams require frameworks for handling sensitive information.

• Development teams seek input on secure SDLC processes.

Each interaction demands not just technical knowledge, but the ability to translate complex requirements into actionable guidance.

This multifaceted nature of GRC work creates unique challenges that can't be solved through traditional automation alone. It requires a deep understanding of how different parts of an organization interact and how security controls affect business operations.

The Evolution of GRC Tooling

The current state of GRC tooling reveals an interesting paradox in our industry. While other security verticals have developed sophisticated tools that provide actionable insights and automated remediation, GRC tools have largely remained in an earlier stage of evolution.

Shruti explained how most GRC tools essentially function as structured databases. They're good at storing information and maintaining relationships between data points, but they fall short when it comes to:

• Automated decision-making

• Context-aware assessments

• Dynamic policy updates

• Intelligent evidence validation

• Cross-framework mapping

This limitation means GRC professionals spend significant time on manual tasks that could be automated, preventing them from focusing on strategic initiatives that could drive real security improvements.

The Agentic Revolution

The introduction of AI agents in GRC represents a fundamental shift in how we approach compliance and risk management. Here's how these technologies are transforming key GRC processes:

Common Controls Framework Automation

Traditional CCF development and maintenance has been a resource-intensive process requiring constant attention and expertise. AI agents can now:

• Analyze multiple regulatory frameworks simultaneously

• Identify common requirements across frameworks

• Generate mapped controls that satisfy multiple requirements

• Maintain framework currency as regulations change

• Adapt controls to organization-specific contexts

This automation doesn't just save time - it enables a level of framework maintenance and alignment that wasn't practically achievable through manual efforts.

Dynamic Decision Making

AI agents are bringing a new level of sophistication to GRC decision-making processes. They can:

• Understand and apply organizational context to control assessments

• Adapt evidence requirements based on system criticality

• Generate risk-appropriate control recommendations

• Provide consistent evaluation criteria across assessments

• Learn from historical decisions to improve future recommendations

This capability bridges the gap between rigid rule-based automation and the nuanced decision-making traditionally reserved for experienced GRC professionals.

End-to-End Workflow Automation

Perhaps most impressively, AI agents can now manage complex GRC workflows from start to finish:

• Navigate company documentation and knowledge bases

• Create detailed execution plans for assessments

• Interact with various tools and systems

• Maintain consistency across processes

• Learn and adapt to company-specific requirements

• Generate comprehensive reports and findings

This level of automation doesn't eliminate the need for human oversight - instead, it elevates GRC professionals to focus on strategic decision-making and program improvement.

The Human Element in an AI World

The introduction of AI in GRC raises natural questions about the future of the profession. However, the reality is more nuanced than simple replacement narratives suggest. AI is transforming the role of GRC professionals by:

• Eliminating routine, repetitive tasks

• Enabling more strategic focus

• Improving the quality and consistency of assessments

• Allowing for more meaningful stakeholder engagement

• Creating opportunities for program innovation

This transformation allows GRC professionals to focus on what they do best: understanding business context, managing relationships, and making strategic risk decisions.

Want More? We've Got You Covered 🎧

Full episode available on:

• Spotify

• YouTube

Keep The Conversation Going

Think we're onto something? Here's what you can do:

1. Share your own hot takes in the comments 🔥

2. Got spicy questions about AI in GRC? Share your ideas for an upcoming podcast

3. Hit that subscribe button - your inbox needs more trailblazing GRC

Connect with Shruti

Want to keep up with what's next in AI-powered GRC? Follow Shruti on LinkedIn and check out her company, Zania.

Found this valuable? Share it with that colleague who's still doing everything in Excel. They need to see this. 📊 ➡️ 🤖