DEV Community: David O’Neal

The Future of GRC: AI, Automation, and the Engineering Mindset

David O’Neal — Tue, 02 Sep 2025 17:09:52 +0000

By David O’Neal
Published on Medium

GRC Is No Longer Just a Checkbox
For decades, Governance, Risk, and Compliance (GRC) sat in the background — necessary, but often seen as overhead. Companies built frameworks to satisfy auditors, pass inspections, and keep regulators at bay. It worked, but it was reactive.

That world is gone.

The sheer speed of digital transformation, coupled with rising cyber threats, complex supply chains, and global ESG obligations, has forced GRC into a new role. It’s not just about keeping businesses out of trouble anymore. It’s about enabling them to move faster, withstand shocks, and build trust in a volatile world.

The forces driving this shift? Artificial intelligence, automation, and a new discipline called GRC engineering.

Macro Trends Reshaping GRC Between now and 2030, five big trends will define how organizations approach GRC:

Predictive Compliance — Instead of reacting after a failure, AI models forecast where controls might break down before they do.
RegTech Becomes Core — Regulatory technology isn’t a bolt-on anymore; it’s woven into every modern GRC platform.
Composable Architecture — Modular, API-driven systems let companies snap together GRC capabilities — AI, ESG, audit, compliance — like building blocks.
Continuous Monitoring — Always-on compliance, powered by real-time data and autonomous systems.
AI Governance & Ethics — Managing risk now includes governing AI itself: bias, explainability, traceability.
“85% of enterprises plan to fully embed AI into GRC systems by 2026.” — Chandrasekaran (2024)

The message is clear: compliance is no longer a once-a-year exercise. It’s continuous, predictive, and deeply embedded in business operations.

Technology Is Rewriting the GRC Playbook Generative AI: The New GRC Co-Pilot Generative AI is changing how compliance teams work. Instead of poring over endless regulations or drafting policy updates by hand, GRC leaders now have an intelligent assistant:

Drafts audit reports and remediation plans automatically
Summarizes and interprets new regulations (GDPR, CSRD, HIPAA) in plain language
Generates reusable internal control templates
Runs “what-if” simulations to show how a new law or policy could affect operations
In other words, GenAI isn’t just saving time — it’s making compliance more proactive and forward-looking.

Predictive Risk & Continuous Controls
Traditional risk management looks backwards. Predictive risk management looks ahead.

Bayesian networks model how risks cascade across supply chains, finance, and compliance.
Continuous controls monitoring (CCM) agents pull in real-time feeds from IoT sensors and cloud platforms, detecting issues and fixing them on the fly.
Dynamic heatmaps are generated from KPIs, audit logs, and external threat data — giving leaders a live view of organizational risk.
This turns compliance from a periodic snapshot into a 24/7 radar system.

GRC-as-Code: Compliance Built In, Not Bolted On
Perhaps the most radical shift is the rise of GRC-as-Code. Inspired by DevOps, it embeds compliance into the development lifecycle itself.

Compliance-as-Code tools (OPA, Rego, Sentinel) enforce rules automatically during deployments.
Version-controlled policies ensure every change is logged and traceable.
Automated testing validates compliance the same way unit tests validate code.
Infrastructure-as-Code (IaC) integrates security and compliance rules directly into cloud environments.
The result: compliance becomes invisible, continuous, and inseparable from how software is built and run.

New Roles Are Emerging As GRC becomes more technical, new hybrid roles are appearing — part compliance, part engineering, part data science.

GRC Engineer — Codifies compliance into code, builds automation scripts, and deploys controls alongside infrastructure.
GRC Architect — Designs scalable, modular platforms that integrate risk, audit, ESG, and compliance into one ecosystem.
Risk Data Scientist — Uses ML, anomaly detection, and advanced modeling to predict risks and generate real-time alerts.
These roles reflect a new reality: the future of GRC will be built by people who understand both regulation and technology.

Designing GRC for Scale Forward-thinking organizations are re-architecting GRC to keep up with complexity. Key design principles include:

composable Services — Separate microservices for regulation tracking, policy engines, and audit logs.
API-first Integration — Seamlessly connecting GRC to ERP, CRM, ticketing, and security systems.
Federated Governance — A central policy brain with local enforcement through lightweight agents.
Real-Time Data Flows — Event-driven monitoring pipelines (Kafka, Kinesis) powering instant risk detection.
This isn’t GRC as a back-office function. It’s GRC as enterprise architecture.

RegTech and AI Governance Take Center Stage RegTech — AI-powered tools that automate compliance — is no longer optional. It’s becoming the engine of modern GRC.

Real-time fraud and anti–money laundering detection
Automated monitoring of regulatory changes worldwide
Continuous transaction monitoring to ensure privacy law compliance
But there’s a twist: organizations must also govern the AI itself. Bias, transparency, and explainability are now part of compliance. Regulators, investors, and customers all expect accountability in how AI systems make decisions.

The future of GRC isn’t just about human compliance — it’s about machine compliance too.

How to Get Started Transformation can feel daunting, but progress is achievable when it starts small and scales fast. Practical steps include:

Pilot AI-driven controls — Start with low-risk areas like audit automation and policy parsing.
Embed GRC into DevSecOps — Make compliance checks part of every deployment pipeline.
Leverage ESG and AI governance — Turn transparency and ethics into a market differentiator.
Adopt federated platforms — Balance central oversight with local flexibility.
Automate third-party risk — Continuously monitor vendors for ESG, security, and compliance.
These aren’t moonshots — they’re achievable with today’s tools.

Looking Ahead
By 2030, GRC will look nothing like it does today. Compliance won’t be managed through binders, spreadsheets, or quarterly reviews. It will be run by AI, executed in code, and monitored in real time.

Companies that embrace this shift will be the ones that thrive. They’ll be faster, more resilient, and more trusted than their peers.

The message is clear: GRC is no longer just about defense.
It’s a strategic weapon.

Continuous Compliance with AWS Config + Security Hub

David O’Neal — Sat, 23 Aug 2025 22:00:18 +0000

Manual control checks don’t scale. AWS gives you Config and Security Hub to monitor controls continuously.

Why These Two

AWS Config tracks configuration state and rule compliance.
Security Hub aggregates findings across standards (CIS, PCI, etc.).

Minimal Viable Setup

Enable Config in every account; pick the rules that map to your framework.
Aggregate to a delegated admin account.
Enable Security Hub with the standard(s) you care about.
Route notifications for High/CRITICAL findings.

What to Capture for Audits

Screenshots of compliant/non‑compliant resources
Security Hub findings summary
Remediation tickets referencing rule IDs

Resources & Evidence

AWS Governance Lab (Config + Security Hub) → https://doneal78.github.io/grc_portfolio/labs/aws-account-governance/?utm_source=devto&utm_medium=article&utm_campaign=aws-lab
Portfolio → https://doneal78.github.io/grc_portfolio/?utm_source=devto&utm_medium=article&utm_campaign=portfolio

Identity Reviews that Don’t Hurt: A Practical Playbook

David O’Neal — Sat, 23 Aug 2025 21:58:39 +0000

Access reviews fail when they’re manual, slow, and unactionable. Here’s a playbook for evidence‑first identity reviews that teams don’t hate.

Principles

Least privilege is a direction, not a one‑time event.
Evidence beats opinion: show what a role can do, not just what it’s called.
Make offboarding boring: standardize the “goodbye.”

Steps

Centralize identities (AWS IAM Identity Center) and require MFA.
Role clarity: short role catalog with purpose, owner, and allowed actions.
Review cadence: quarterly for admins, semi‑annual for contributor roles.
Automate inputs: export principals, last‑used metrics, and effective permissions.
Tighten: remove unused roles, break up “kitchen sink” policies, add alerts for admin elevation.

Evidence to Keep

Role catalog (Markdown/CSV)
Last‑used permissions report
Tickets confirming removals & approvals

Result

Faster reviews, fewer exceptions, simpler audits.

Resources & Evidence

Case Study: AWS Account Governance → https://doneal78.github.io/grc_portfolio/projects/aws-account-governance/?utm_source=devto&utm_medium=article&utm_campaign=aws-governance
Lab: Identity Center & MFA → https://doneal78.github.io/grc_portfolio/labs/aws-account-governance/?utm_source=devto&utm_medium=article&utm_campaign=aws-lab

AWS Account Governance: Guardrails that Prove Themselves

David O’Neal — Sat, 23 Aug 2025 21:36:26 +0000

Governance succeeds when it’s provable. In AWS, that means designing guardrails that prevent risky changes, surface evidence continuously, and map to a control framework the business recognizes.

The Problem

Fast growth in AWS often leads to:

Siloed accounts with inconsistent controls
Over‑privileged IAM roles
Compliance that depends on screenshots and goodwill

The Approach

Organize accounts by function or environment under AWS Organizations.
Apply Service Control Policies (SCPs) to hard‑deny obvious anti‑patterns (public S3 ACLs, unapproved regions, root key usage).
Centralize identity with AWS IAM Identity Center (least‑privilege roles, SSO, MFA).
Continuously evaluate with AWS Config + Security Hub (CIS/NIST rules).
Prove it with artifacts: dashboards, role definitions, SCP docs, and alert samples.

Design Notes

Start with a deny‑list SCP set that blocks the worst foot‑guns.
Add budget alerts per account—governance includes cost control.
Evidence lives forever: store screenshots/CLI outputs alongside SOPs in version control.

Outcomes You Can Expect

Reduced blast radius: even if an IAM policy grows too broad, SCPs catch dangerous calls.
Audit‑ready posture: Config and Security Hub give date‑stamped findings.
Developer trust: roles are known, access is fast, and reviewers stop playing whack‑a‑mole.

Resources & Evidence

Case Study: AWS Account Governance → https://doneal78.github.io/grc_portfolio/projects/aws-account-governance/?utm_source=devto&utm_medium=article&utm_campaign=aws-governance
Hands‑on AWS Governance Lab → https://doneal78.github.io/grc_portfolio/labs/aws-account-governance/?utm_source=devto&utm_medium=article&utm_campaign=aws-lab
Portfolio → https://doneal78.github.io/grc_portfolio/?utm_source=devto&utm_medium=article&utm_campaign=portfolio