Building the Future: Our Vision for AI-Powered GRC

GRC has always been a data-intensive discipline, but the scale and complexity of modern regulatory environments have been pushing traditional approaches to their breaking point. Organizations are drowning in frameworks, struggling to keep pace with regulatory changes, and spending countless hours on manual processes that scale poorly. 

In other words, it’s a landscape ripe for transformation — one where AI has the potential to fundamentally reshape how risk and compliance work gets done. 

In GRC, AI tools offer the ability to identify control gaps, provide predictive insights, and process and analyze regulatory requirements at unprecedented speed. They can recognize patterns and surface hidden correlations that traditional monitoring would miss entirely, and they can make accuracy and efficiency more accessible across the entire organization. 

Yet adoption in the industry has been slow, with only 18% of organizations currently using GenAI tools for compliance, according to the 2025 State of CCM Report. 

That’s why we’ve positioned ourselves at the forefront of AI innovation in GRC. We recognized early that bridging this adoption gap will require more than just implementing new technology; it demands a thoughtful, practitioner-focused approach that addresses the real barriers holding organizations back. 

What Sets RegScale’s AI Apart

Our approach to AI — RegML — is grounded in solving real problems that GRC teams face every day: the bottlenecks, the manual work, and the knowledge gaps. Rather than layering technology on top of existing processes, we’ve embedded AI into the heart of the platform to create meaningful outcomes for our users. Here’s what that looks like in detail. 

Accelerating regulatory adoption. When a new framework drops or an existing one changes, the clock starts ticking. Our AI leverages existing policy documents, past security plans, and other institutional knowledge to rapidly tailor and implement those new requirements. This capability also ensures quick adaptation when existing frameworks change, so what used to take months can happen in weeks. 

Streamlining onboarding and framework adoption. We’ve developed AI-driven tools that use a custom intake questionnaire to automatically restructure and map responses into a new System Security Plan (SSP). These tools accelerate onboarding into the platform and significantly speed up adoption of new frameworks. 

Performing AI-powered audits. Our AI audit capabilities identify gaps and vulnerabilities within a system security plan before the expense of a human audit. This catches gaps early, saving significant time, energy, and cost by addressing weaknesses early in the process. 

Making complexity understandable. Compliance language can be highly dense, technical, and often alienating. Our AI translates it into clear, accessible explanations that work for the entire organization, not just the specialists. That democratization of knowledge helps make critical insights usable across the company. 

Guiding best practices and implementation. By analyzing control requirements and organizational context, AI surfaces best practices and outlines a clear path forward for control implementation. This provides practical, actionable guidance that accelerates audit readiness. 

Building an AI Foundation

The success of any AI initiative depends on the strength of its leadership. Under the direction of Dr. Monica Ihli, RegScale’s Senior Manager of AI Engineering, we’ve built an AI program that balances vision with the practical realities of GRC work — and that models how AI can be responsibly and effectively applied in this industry. 

Building a foundation of research and innovation. Our team has established a rigorous research and development program designed to improve inferencing outcomes and generate data-driven insights that guide implementation decisions. As a subject matter expert in AI and compliance, Dr. Ihli has spearheaded the development of novel algorithms that leverage generative AI to address some of the most frustrating challenges in preparing for audits and delivering immediate value to GRC professionals. 

Cultivating a world-class team. We’ve cultivated an R&D team that combines deep academic expertise with applied knowledge of GRC in practice. This balance between technical rigor and a pragmatic understanding of the day-to-day challenges faced by practitioners has created a culture that produces innovation while remaining grounded in the operational realities of the industry. 

The bottom line? RegScale’s AI program is not an experiment on the sidelines but rather a core driver of our growth, resilience, and leadership in GRC. 

AI: The Ever-Evolving Endeavor 

If there’s one constant in the AI landscape, it’s change. Capabilities are progressing rapidly, and today’s breakthroughs will be tomorrow’s old news. 

To stay ahead of the curve, we’re focused on ensuring that every advancement we create is grounded in trust and practical value. Several priorities define our path forward. 

First, we’re committed to innovating the way professionals engage with AI agents. By designing intuitive, responsible interfaces, we aim to establish best practices for the industry. Our goal is to make interactions with AI seamless, empowering, and aligned with how GRC professionals actually work. 

We’re also committed to building trust, credibility, and transparency. We know that giving AI agents access to systems can feel daunting, which is why we’ve made sure that the foundational models we’ve deployed are from trusted sources, tuned to specific organizational needs, capable of operating in closed environments, and unable to act without explicit approval. These protections make it possible to shift the conversation from fear to value, highlighting how AI can remove tedious tasks while leaving control firmly in human hands. 

Next, we’re investing in solid architectural foundations that are extensible, interoperable, and future-ready. Strong architectural engineering is the backbone that will allow innovation to flourish. By embracing emergent best practices such as Model Context Protocol (MCP), we are ensuring that our platform can seamlessly integrate AI capabilities, scale responsibly, and adapt to the rapidly evolving needs of GRC professionals.  

Beyond that, we plan to continue setting new benchmarks for efficiency and accuracy across the industry by growing several key capabilities in our platform. 

• AI auditing: Allowing organizations to identify risks and compliance gaps faster and at lower cost. 
• AI policy drafting: Giving practitioners draft content that’s aligned to regulatory expectations and ready for expert review.  
• AI control mapping: Solving persistent challenges in one of the most frustrating and resource-intensive aspects of compliance. 
• AI regulatory change scanning: Partnering with organizations that provide regulatory horizon scanning and change management — and transforming unstructured regulatory information into structured, usable intelligence — in order to help organizations prepare for change before it arrives. 
• AI for the financial sector: Strengthening our platform’s capabilities for the financial services industry, a sector where regulatory complexity is high and the potential for AI-driven impact is enormous. 

All in all, our vision is to lead not only through technology but also through trust, foresight, and a relentless focus on solving the problems that matter most to GRC professionals. 

Future Vision: Where the GRC Industry Is Headed 

By 2030, GRC will look very different than it does today. We’re already seeing major shifts today — shifts being driven by increasing capabilities in AI and automation as well as growing expectations from regulators, stakeholders, and customers. 

1. GRC will move from reactive to proactive. Today’s GRC programs often identify risks after they have emerged. By 2030, AI will help shift us towards predictive models that forecast risks before they materialize — moving the whole industry from backward-looking documentation to forward-looking prevention. 
2. Compliance programs will adapt more quickly and flexibly. The regulatory landscape is not getting simpler. (If anything, it’s continuing to grow in complexity.) However, AI will allow us to finally catch up with the rate of regulatory change by making it possible to ingest, interpret, and operationalize new requirements in days rather than months.  
3. Industry standards for AI will emerge. Just as industries once had to create and align on best practices for, say, quality management or financial auditing, we’re going to see a rise in accepted standards for how AI is designed, deployed, and governed in GRC. Organizations that can lead the conversation on AI best practices will help shape the future of the industry. 

The most effective GRC teams in 2030 will be those that combine deep professional judgment with AI-driven augmentation. They’ll balance the precision and scale that AI provides with the contextual understanding, ethical reasoning, and strategic oversight that only humans can deliver. Machines will handle the repetitive work and surface the insights, while professionals will make the critical decisions, navigate nuance, and maintain accountability. 

This is the future we’re working toward: One where GRC professionals are freed from manual tasks and empowered to focus on strategic risk management, stakeholder engagement, and the high-value work that truly drives business outcomes. We’re excited to see this vision become a reality.