How to integrate AI into a GRC strategy

COMMENTARY: A Fortune 500 financial services firm discovers their AI-enhanced governance, risk, and compliance (GRC) platform has been quietly sending sensitive control documentation to an external LLM for over six months.

The platform's "intelligent compliance assistant"—marketed as a game-changer for audit efficiency—had processed everything from penetration test results to incident response playbooks through third-party APIs.

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The discovery comes only when the company fails a routine SOC 2 audit requirement for data localization. It triggers a compliance nightmare, transforming their “clean” compliance posture into a material weakness requiring disclosure along with the prospect of notifying every client whose security questionnaires and audit evidence had been exposed to unapproved third-party processing.

While it’s a hypothetical scenario, it reflects a very real risk. As organizations rush to integrate AI into their GRC operations, many inadvertently create the very vulnerabilities their compliance programs are meant to prevent.

Traditional GRC approaches simply weren't designed for this reality. The static playbooks and annual assessments that worked in a pre-AI world are dangerously inadequate when facing systems that can evolve their behavior in real-time. Organizations need a new paradigm: One that harnesses AI's power for compliance while maintaining strict governance over the AI itself.

The AI evolution in GRC

I find myself saying “Compliance is Complex” repeatedly these days. And it's true. The myriad of rules and interpretations are the most bizarre form of recently invented theocracy. Traditional GRC platforms and the Advisory Services industry have long relied on simple playbooks, workflow automation and templated policies that “simplify” processes at the cost of efficiency and innovation. And to top it off, much of the work is done offshore.

Today's AI capabilities offer something far more sophisticated: Intelligent validation, predictive risk analysis, and contextual insights that transform compliance from a checkbox exercise into a strategic advantage.

Consider evidence validation. Where legacy systems simply collect and store documentation, AI-powered validation engines analyze evidence quality in real-time, identify gaps, and predict potential audit findings before they occur. This shifts the paradigm from reactive compliance to proactive assurance—critical as regulations like the Digital Operational Resilience Act (DORA) and Cybersecurity Maturity Model Certification (CMMC) 2.0 demand continuous resilience rather than point-in-time compliance.

Already, intelligent mapping capabilities can automatically identify common controls across frameworks, reducing redundant work and ensuring comprehensive coverage. When a single organization must comply with SOC 2, ISO 27001, GDPR, and the EU AI Act simultaneously, this intelligence becomes invaluable.

A security-first AI architecture

Not all AI implementations are created equal. Many platforms rely on external LLMs via API calls, inadvertently exposing sensitive data to third-party systems. This approach creates critical vulnerabilities such as data exposure risks, audit trail gaps and model training concerns.

Organizations should adopt AI implementations that prioritize Secure-by-Design principles. Self-hosted AI models running within controlled environments can eliminate data exposure risks while maintaining full audit trails. Zero-trust architectures ensure that even internal AI systems operate with minimal privileges, accessing only the specific data required for each task.

The concept of "TrustOps"—operationalizing trust-building across all organizational activities—offers a framework for thinking about AI integration in GRC. When properly implemented, AI doesn't just automate compliance tasks: It actively builds stakeholder confidence through transparent, verifiable operations.

For GRC leaders beginning this journey, here are six practical steps:

Successfully integrating AI in GRC isn't just about efficiency—it's about building a more intelligent, adaptive, and trustworthy compliance posture that demonstrates genuine operational resilience. As regulations evolve and AI capabilities advance, mastering this balance has become essential.

Justin Beals, founder and CEO, Strike Graph

SC Media Perspectives columns are written by a trusted community of SC Media cybersecurity subject matter experts. Each contribution has a goal of bringing a unique voice to important cybersecurity topics. Content strives to be of the highest quality, objective and non-commercial.