AI Is Changing Risk Monitoring. Here’s What It Actually Does (and Doesn’t Do).

Recent advancements in machine learning are revolutionizing all kinds of industries, and risk management is no exception. However, despite the advances in AI tools, this technology is not a replacement for human skills. Simply turning over all of your risk monitoring processes to AI systems might even create more risks in the long run.

So how do you know when to use AI compliance tools for risk monitoring and when to let human experts take over? In this guide, we’ll break down the biggest strengths and weaknesses of generative AI when it comes to governance, risk and compliance (GRC). Explore how to make the most of responsible AI usage without unintentionally creating more risk exposure.

The Benefits of AI for Risk Monitoring

Responsible use of artificial intelligence can take the tedium and guesswork out of many GRC functions. These are only a few of the many tasks that generative AI can support and sometimes outperform human risk managers.

Identifying and Flagging Risks

One of the best uses for AI risk management tools is tracking potential risk factors. AI can flag potential risks for relevant team members to review and rank the risks by priority. 

These features can take some of the pain out of compliance workflows, especially if your organization uses many diverse data sources of varying levels of reliability. Many AI-augmented GRC platforms are purpose-built and trained to monitor specific risk categories, such as third-party risks and relationships.

Automating Regulatory Tracking and Policy Updates

If your organization is impacted by multiple regulatory frameworks or laws that are constantly changing, compliance automation can reduce repetitive work. AI compliance tools are capable of tracking regulatory updates, alerting relevant team members and even updating affected internal policies automatically. This kind of automation can be especially valuable for organizations managing regulatory compliance obligations across multiple departments or jurisdictions.

You’ll still want to make sure any policy updates are reviewed promptly by a human expert in case of any errors. However, that’s generally a quicker and easier process than manually tracking all regulation changes and updating policies by hand. As the broader regulatory environment continues to evolve, AI-assisted monitoring can help teams stay informed without relying entirely on manual processes.

Maintaining Audit Readiness

AI governance, risk and compliance tools can be a game-changer when it comes to audit management and preparation. Instead of scrambling to gather evidence and generate reports during an audit, you can rely on AI-assisted software to constantly compile these records automatically as you go about your work, maintaining your compliance posture. The same features can also be a lifeline when you need to investigate unexpected adverse events, such as data breaches. Organizations working within complex governance frameworks may also benefit from centralized reporting and documentation features that simplify audit preparation.

Learn More About How AI Is Reshaping Risk Monitoring

• The Future of GRC: AI Enabled, Human Led
• Resilience in an Era of AI and Global Volatility: What Actually Needs to Change in GRC
• How AI Helps GRC Teams Respond to Regulatory Change Faster
• Artificial Intelligence and Cybersecurity: A Federal Perspective

The Limitations of AI in Risk Monitoring

Although AI compliance tools are promising in many respects, they can’t be expected to handle every type of task with equal competence. Human expertise will always be essential to risk monitoring.  You and your team need to understand the limitations and risks posed by AI in order to use the technology responsibly.

Judging Acceptable vs. Unacceptable Risk

While AI tools are often excellent at identifying and tracking risks, they’re much less capable when it comes to understanding exactly how much risk your organization needs to tolerate to accomplish its goals. AI models tend to operate within rigid parameters and binary frameworks and rely on strict rubrics to sort potential risks. It takes a human mind to introduce nuance when needed.

Drawing Reliable Conclusions from Data

One of the most well-documented AI risks is the technology’s tendency to leap to conclusions based on little evidence, or even generate inaccurate information when there isn’t enough available to draw a clear conclusion. Humans are better at evaluating the reliability of murky data, vague conclusions and contradictory evidence than machines. To function properly, your organization needs the ability to acknowledge the messiness of real data governance. This is particularly important when teams are handling sensitive information tied to data privacy and compliance reporting requirements.

Ensuring Appropriate Data Protection

Another potential risk associated with the use of some of the most popular AI tools, such as ChatGPT, is how little users know about what happens to the data they feed to the platform. Many general-purpose AI platforms provide limited visibility into how information is processed or stored, which is why it’s important to find a GRC-specific tool that your team can use safely. Organizations evaluating different AI products should also consider how vendors address security controls, retention policies and access management.

Learn More About the Risks of Using AI for GRC

• Beyond Cybersecurity: What Leaders Overlook About AI Risk
• AI in GRC: How to Separate Practical Value From Vanity Features
• Why Data Privacy Is Breaking Down in the Age of AI
• Your Employees Are Your Biggest Privacy Risk. Here’s Why.

The Best Practices for Getting the Most Out of AI With Minimal Downsides

Knowing what AI is best and worst at gives you a head start on using it effectively in risk management. Here’s our best advice for GRC teams looking to incorporate AI tools that add efficiency, not risk:

• Create organizational policies around AI use: Reports suggest that more than one in five workers across various industries are already using generative AI professionally, with or without their employers’ guidance, which can lead to security risks. Instead of outright banning these tools, your best bet is to craft policies to guide your team toward responsible AI use and away from potentially risky platforms. Clear internal standards can also help organizations maintain consistent regulatory compliance practices as AI adoption expands.
• Ensure human reviewers are always involved: One of the simplest way to curb risks associated with AI is to assign a human expert to review any tasks or reports generated by machine learning before your team acts on the information. You can simplify this work by setting your tool to automatically submit its work to the appropriate team members for review.
• Use purpose-built GRC platforms: The best way to protect your organization from the risks of AI is to choose a platform that’s purpose-built for governance, risk and compliance teams. Platforms such as Onspring’s compliance software understand exactly what risk managers need from the technology and which safeguards need to be in place to prevent unnecessary risk. This can be especially helpful for organizations navigating a changing regulatory landscape while managing operational complexity.
• Evaluate before your commit: Before committing to an AI tool, teams should understand how it works in practice, including its governance, security and workflow capabilities. With Onspring, you can schedule a personalized demo so you know exactly what you’re signing up for.

Learn More About Responsible AI Use for Risk Monitoring

• 4 Best Practices for Managing Generative AI Risk
• Why Secure, Built-In AI Matters More Than Standalone AI Tools in Modern GRC
• What AI Should Handle and What Humans Should Not
• What Secure AI Really Looks Like in Compliance Management

Understand How AI Fits into Today’s GRC Landscape

AI capabilities aren’t the only new developments changing how governance, risk and compliance officers need to approach their work. Organizations should avoid focusing solely on AI while overlooking broader GRC modernization trends. Across the industry, GRC teams are shifting toward continuous monitoring, connected risk data and other improvements.

Download the 2026 GRC Report to see the top five trends reshaping GRC right now to learn more about which you should implement and which may require caution.