Artificial intelligence technology is having a profound impact on all industries, but not all tools are created equal, or equally useful. When it comes to AI in risk management, the last thing compliance officers and risk managers need is another tool that floods them with alerts and information without offering guidance on what to do with it or assistance getting that work done.
If you’re wondering how you can use AI systems to streamline processes and turn insights into action without overwhelming your governance, risk and compliance (GRC) team, this guide is here to help. Learn more about why information overload is a growing problem in risk management, how your existing processes might not be enough to combat it and what AI risk management tools can do to alleviate the pressure.
Key Takeaways
- AI impacts risk management but can lead to information overload without guidance.
- Compliance teams need AI tools that summarize and prioritize information, avoiding alerts that overwhelm them.
- Avoid ad-hoc solutions; they can waste human expertise and lead to critical information being missed.
- Use AI for data processing and analytics, but rely on human oversight for decision-making.
- Choose purpose-built GRC platforms to integrate AI effectively and safely, reducing risks.
Table of Contents
When Important Alerts Turn Into Information Overload
Keeping up with common GRC responsibilities, such as risk assessments, regulatory compliance and data governance, requires risk managers to stay informed in a constantly shifting landscape. And the solutions may not be self-evident. For instance, setting up alerts to let you know when regulatory requirements change seems like an easy solution until your inboxes are overflowing with information of varying importance.
It’s no wonder, then, that many compliance officers are turning to popular AI tools to summarize long reports, pull out key information and reduce their overall intellectual load. The downside here is that the most commonly used AI models have insufficient safeguards for data privacy, no built-in expertise on GRC topics and no connection to your existing governance frameworks. Because of these drawbacks, choosing the wrong AI technology can actually expose your organization to even more risks, including potential data breaches, regulatory noncompliance and reputational damage. Some organizations respond by forbidding any use of AI, but ignoring new trends in risk assessment only sets your team up to fall behind.
In fact, an analysis by Harmonic showed that in 2025, enterprises saw their employees using a startling 23 new, unknown generative AI tools on average. Given the proliferation of tools out there, GRC employees are likely to use AI with or without internal permission. So failing to provide guidelines only leaves you open to even greater risk.
Learn More About How AI Is Reshaping Risk Management
- Resilience in an Era of AI and Global Volatility: What Actually Needs to Change in GRC
- The Future of GRC: AI Enabled, Human Led
- Why Data Privacy Is Breaking Down in the Age of AI
Why Ad Hoc Solutions Don’t Work
The traditional ways of handling information overload are often simple. Unfortunately, they’re too often ineffective as well. In many organizations, one or two individuals shoulder the burden of tracking key information, determining which pieces of information need to be surfaced to the larger organization and which alerts are just noise to be ignored.
However, the manual approach is both error-prone and time-consuming. Valuable human expertise goes to waste as experienced team members lose significant time wading through irrelevant information. And the more overwhelmed these individuals are, the more likely they are to unknowingly let critical information fall through the gaps.
But even if you do have the staff, there’s another drawback to ad-hoc tracking. If your risk mitigation strategy relies on alerts from outside sources, you’re only ever reacting to changes in the compliance landscape, rather than working proactively to identify and prevent risks.
One-off AI usage has a tendency to cause more problems than it solves. The manual approach with its overreliance on human filtering is the other side of the same coin. Both of these strategies fail because they misunderstand the best uses of artificial intelligence vs. human intelligence.
When humans outsource critical functions like judgment, understanding context and tolerating risk to AI platforms, processes fail and new risks arise. Similarly, opportunities lapse and risks go unnoticed when people tackle rote problems better left to machines, such as sifting through and sorting piles of information.
So how do you make sure that AI-powered governance tools and human oversight are working in tandem rather than creating friction and risk? The answer is choosing the right tool for the job.
Learn More About the Hidden Risks of Using the Wrong AI Tools
- Beyond Cybersecurity: What Leaders Overlook About AI Risk
- AI in GRC: How to Separate Practical Value From Vanity Features
- What AI Should Handle and What Humans Should Not
How Centralized AI Risk Management Separates Signal from Noise
Wondering how to get the most out of your AI tools and human experts? Here are our recommended best practices for reducing information overload without introducing AI risks:
- Use AI when appropriate: AI tools are best suited for processing large amounts of information faster than a human ever could. That means you’ll want to assign it tasks like data analytics or fraud detection, but always ensure the results are reviewed by humans who understand the goal of the work and the errors to look out for.
- Know when to rely on human expertise: Treat human judgment as the valuable limited resource that it is by choosing the most impactful points in your workflow to deploy human attention. For example, AI can be great for summarizing large amounts of information and pulling out key insights, but it should be the responsibility of a human expert to determine the best way to act on that information, if at all.
- Choose a purpose-built GRC platform: If you and your team don’t have the time to vet multiple individual AI tools, you can save yourself a lot of hassle by avoiding any AI platform that isn’t specifically made for governance, risk and compliance teams. Only purpose-built GRC platforms are designed with compliance teams’ needs in mind throughout the AI lifecycle and with appropriate safeguards to prevent reputational risks and other types of potential damage.
Learn More About the Right Way to Use AI for GRC
- Why Secure, Built-In AI Matters More Than Standalone AI Tools in Modern GRC
- How AI Helps GRC Teams Respond to Regulatory Change Faster
- What Secure AI Really Looks Like in Compliance ManagementGet the Efficiency of AI Without the Risks
Constant alerts shouldn’t stop your team from acting on the information that matters most. Instead of wading through data points of varying importance and relevance hoping not to miss the updates they actually need, GRC professionals are turning to the immense data processing power of AI for help.
Unfortunately, some AI models can introduce nearly as many problems as they solve. Using the wrong platform can expose your organization to potential data breaches, reputational risks and even legal liability. That’s why the safest way to integrate AI into your GRC workflows is to use a platform purpose-built to meet the needs of risk managers and compliance officers.
With Onspring’s GRC software, you can safely use AI to streamline processes and boost efficiency by quickly reviewing and summarizing documents, detecting and removing duplicate data and automatically creating records like risk assessments and mitigation plans.
Find out for yourself how the right platform can transform your GRC efforts. Schedule your personalized demo today to see Onspring’s process automation, workflows, analysis, and reporting in action.
