Many governance, risk, and compliance (GRC) professionals think of automation as a north star in the journey to GRC maturity. For good reason: when you’re running yourself ragged between evidence collection, policy updates, and vendor assessments, automated GRC processes can feel like a lifeline. 

But what if the most mature GRC programs are playing a different game altogether? 

Survey data from our State of Enterprise GRC Maturity research reveals telling patterns about how the most mature GRC programs use automation and AI, how AI expectations compare to reality, and how leadership buy-in ties to AI adoption.
‍
As you pursue full GRC maturity, don’t stop at automation. Take a cue from level 5 GRC teams — the most mature — and use technology the way they do.

Automation is Important, but Don’t Stop There.

In our survey of over 550 GRC professionals, those who rate their organization at GRC maturity levels 1 through 4 consistently report a “lack of automation” as a top-three barrier to achieving full GRC maturity. 

Other findings back up this perception: the rate of GRC process automation is highly correlated with an organization’s GRC maturity. In fact, at level 5 GRC maturity, 100% of programs report using automation. The most common use cases for automation in Level 5 GRC maturity programs are:

• Risk management (67%)
• GRC workflow management (63%)
• Control monitoring and testing (61%)

But automation isn’t the only way the most mature GRC teams use technology to their advantage. A whopping 68% of level 5 teams are also using artificial intelligence in GRC, and 8% more plan to implement AI within the next year. 

{{ banner-image }}

Expectation vs Reality of AI Use Cases for GRC

When asked about areas of opportunity for AI, respondents from individual contributors to executives report “workflow optimization” as a top-three way that AI could significantly improve their GRC program. But are fully mature GRC teams as focused on this use case? Not exactly.

While 47% of level 5 maturity GRC programs report using AI for workflow optimization, our research found that other use cases are even more common. Mature teams aren’t just looking for speed — they’re aiming for smarter strategic expansion.

The most popular processes that level 5 GRC maturity programs currently use AI for are: 

• Gap remediation (55%)
• Recommending relevant controls for a given framework (54%)
• Document review and summarization (50%)
• Recommending how to expand your program based on your evidence (50%)

Instead of using AI to help humans work faster, mature GRC programs are using it to do things better. AI helps them make connections between evidence, frameworks, and actions that would otherwise require deep manual analysis.

Leaders Like GRC Programs that Use AI

One pattern is crystal clear. When survey respondents use AI in their GRC program, for any use case, they are more likely to report that their leadership views GRC in a positive light. 

Now, our data shows correlation, not causation. Does this connection exist because GRC programs that use AI earn the respect of leadership? Or is it that GRC programs gain access to AI when leadership is already on board? The relationship surely goes both ways. Leadership buy-in leads to investment in AI, and AI-powered results demonstrate the value of GRC to leadership.

And remember that excitement around AI for workflow optimization? GRC teams — at any maturity level — that use AI for workflow optimization experience the most significant improvement in positive leadership perception. Compared to total survey responses, leaders at organizations using AI for GRC workflow optimization are:

• 9% more likely to see GRC as a competitive advantage
• 8% more likely to see GRC as a risk reduction tool
• 11% more likely to see GRC as a business enabler

When leaders see the business value of GRC, the metric for success shifts from compliance to business contribution. That’s where AI really starts to matter, not only for what it automates, but for how it helps GRC operate with the same outcome-driven mindset as the rest of the business.

Automation and AI Go Hand in Hand with GRC Maturity

If you’re pursuing automation as part of your GRC maturity journey, you’re on the right path, but think bigger than just offloading manual processes to a machine. While automating labor-intensive parts of the job can give you breathing room for a while, it’s not enough to shift your program from a reactive posture to a proactive one — the ultimate goal of GRC maturity.

Research shows that the majority of level 5 maturity GRC programs have adopted AI to turn data into action. And they aren’t just dipping their toe in the AI pool, but using it across multiple use cases to unlock deeper insights, real-time observability, and context-aware scalability. 

Earlier-stage GRC programs should set themselves up for success with AI by adopting a data-first approach — because the future of GRC is clearly AI-driven, and AI is only as good as the data it’s built on. Building a foundation of AI-ready GRC data ensures that when you adopt AI, you’ll be ready to maximize its value.

You can find many more insights and takeaways about GRC maturity in our State of Enterprise GRC Maturity Report. Download your copy now.

‍