GRC teams are under growing pressure as regulatory requirements expand and organizations expect continuous compliance. According to a PwC 2025 survey, 90% of executives report that the breadth of compliance responsibility has increased since 2022. And because organizations hardly love extra expenses, compliance teams are expected to handle the increased workload without additional headcount.
To ease the operational burden, most GRC teams are adopting AI. But there’s more to compliance than efficiency. Compliance work involves sensitive information and strict regulatory standards. Any misstep with AI can introduce new risks and non-compliance, so it’s vital to use the right tools.
Why Compliance Is a High-Risk Environment for AI
Regulatory compliance is a high-risk environment for AI because a wrong move can result in significant penalties and severe reputational damage. In a 2026 Deloitte report, 50% of organizations say regulatory compliance is a major AI risk concern. And the concern is for a good reason when compliance work is involved. Routine regulatory tasks involve multiple types of risk.
Sensitive Data
An AI model that operates without boundaries can process sensitive information in ways that violate data privacy or data protection requirements. It’s no surprise that 73% of businesses view data privacy and security as the most concerning AI risk. To stay compliant, you should control how models interact with data.
Regulated Information
If you can’t track your automated output back to the source, it can create gaps in audit trails. As the NIST AI Risk Management Framework recommends, your AI system must provide traceability, from data ingestion to output, for auditability. Every action the system takes must be auditable.
Practices That Must Withstand External Scrutiny
If your AI models don’t show how they reach a conclusion, your compliance team may be unable to explain some of the AI decisions to regulators. To maintain compliance, AI tools must have clear enough decision logic to help your team explain outcomes when needed.
Any technology you use in compliance must hold up under scrutiny. Without sufficient controls, you risk increasing exposure.
Where AI Adds Real Value in Compliance Management
AI adds value in compliance when it automates repetitive, high-effort work while preserving the controls and visibility that regulators expect.
Compliance requirements are changing too quickly for manual processes to keep up with. Nearly all (92%) of compliance professionals report their work has become more challenging, according to a 2025 Regology survey. To support your compliance team, you can use AI in the common areas where it has proven real value.
Automated Evidence Collection Across Systems
Manual evidence collection is a notorious time sink for compliance teams. It’s a real pain point that 18% of organizations say is their top audit challenge in a 2024 A-LIGN survey. Your team wastes a significant amount of time gathering screenshots, pulling PDFs across fragmented systems, downloading configs and compiling spreadsheets.
You can use AI to continuously capture and validate evidence across environments, while preserving the source context and timestamp to ensure:
- Comprehensive coverage so you won’t have gaps due to outdated data or technical restrictions
- Continuous audit-readiness, as auditors can see a complete, validated trail at any moment
- Strategic focus because your team will stop acting as evidence hunters and start performing advisory roles
Maintaining Accurate, Time-Stamped Audit Trails
Because every compliance activity must trace back to its source, a secure AI helps you maintain an accurate, time-stamped audit trail with minimal effort. Your compliance team will be able to explain outcomes during audits and regulatory reviews, which can otherwise be difficult when you rely on fragmented systems.
Supporting Real-Time Monitoring of Internal Controls
Traditional risk assessment is usually a point-in-time manual practice. A 2022 Dark Reading report shows that 88% of businesses rely on manual processes to view risks across their infrastructure. To prove compliance, teams must gather logs, verify evidence and score controls in a spreadsheet. This approach is prone to error and findings quickly get outdated, making it difficult to understand your real-time compliance posture.
With secure AI, you can monitor controls to automatically evaluate performance and get a live, dynamic view of your compliance efforts.
Strengthening Risk Management Through Early Issue Detection
It’s often the risk you don’t see that causes the most damage. In cybersecurity, for example, 74% of organizations have suffered incidents due to unknown and unmanaged assets, according to a 2025 Trend Micro research. Secure AI helps you identify gaps and anomalies earlier so you can reduce risk exposure before issues turn into audit findings or regulatory concerns.
Secure AI in Compliance Starts With Governance, Then Automation
Your AI won’t deliver value in compliance if it operates without governance. It should work under clear rules. While compliance standards and regulatory frameworks should guide your AI implementation, here are key governance principles to consider.
Controlled Access To Sensitive Information
If you are deploying a model that interacts with sensitive data or evaluates internal controls, you must carefully configure it to prevent unnecessary access.
In 2025, IBM reported that 97% of businesses that experienced AI-related data breaches lacked proper AI access controls. To avoid high operational and financial costs:
- Adopt role-based access control (RBAC), so both human and AI agents have only the minimum data access necessary for their specific functions
- Automatically scan and filter sensitive data from training datasets and outputs before they reach the model
- Encrypt data at rest and in transit across the entire AI lifecycle
- Use sensitivity labels and data loss prevention policies to restrict AI access
Defined Ownership and Human Oversight
Assign a member of your compliance department to oversee decision-making and monitor AI activities. You’ll need human oversight to manage risks AI will surface. If you don’t define ownership and accountability, your AI use may lead to blind spots and errors that regulators will flag.
Explainability for Compliance Decisions
How your AI model makes decisions should be transparent. Your team needs to understand how the AI reaches its conclusions so they can explain the outcome to regulators when they are required to prove compliance.
GRC-Native AI Tools Support Continuous Compliance Without New Risks
While you can develop models to support compliance, modern GRC tools like Onspring include native AI for compliance and risk management. Unlike general AI tools built for productivity alone, GRC-native automation platforms are regulatory-aware, and they:
- Understand requirements for compliance frameworks like ISO 27001 and SOC 2
- Automatically map your controls
- Continuously capture evidence
- Maintain audit-ready records
- Handle sensitive and regulatory data securely
Importantly, the right tool can analyze patterns across your data controls and regulatory changes to forecast compliance gaps before audits. With continuous controls monitoring, you’ll shift from reactive to proactive compliance management.
Risk Governance Comes First in Secure AI
Your role as a compliance professional is to protect your organization and ensure business processes comply with regulatory requirements. In your pursuit of continuous compliance, any AI solution you implement should reduce manual effort without introducing new risks. You need a secure system that reinforces governance while ensuring regulators can trust your process.
At Onspring, we offer an AI-native GRC solution so you no longer have to trade off speed, scale and accuracy. On our platform, you can organize audit evidence and actively monitor the effectiveness of your controls through real-time alerts. You can also map your controls against common security standards to prove ongoing compliance with confidence.
Download our ebook Make Continuous Compliance Part of Your GRC Best Practices today to learn how you can use GRC-native AI to securely ease compliance workloads.
