Compliance audits can be nerve-racking. If you’re a tech-forward firm, a generative AI tool might already be assisting your team members in summarizing policies or acting as an AI assistant during preparation. These tools work wonders in audits by processing natural language queries and drafting reports from scattered data points.
When it comes to governance, risk and compliance (GRC), however, AI technology has clear limits. For instance, sensitive financial data can be leaked or exposed to vulnerabilities during data export across the data lifecycle. That’s why it’s important to have a native AI tool.
Explore the difference between generic and native GRC AI tools and how the latter delivers superior governance, privacy, context and control.
Why Generic AI Tools Are Not Efficient for GRC
Firms across the world now leverage AI models and machine learning to expedite their daily operations. Marketing teams use them to generate campaign ideas that improve customer experience, and customer service reps leverage conversational AI to streamline repetitive customer interaction.
Undoubtedly, these AI-powered tools work great for many processes. They offer personalization, speed and intuitive interactions through natural language processing scalable AI assistance.
However, effective GRC demands deeper integration than a generic AI tool can provide. In most cases, these models lack specific context because they are trained on public data rather than a firm’s internal policies, data collection systems or audit history. As a result, they can overlook critical policies and audit records.
When you share third-party risk data through these generic tools, they send it to outside servers. Most of them operate outside your enterprise software ecosystem, so you have to transfer data from legacy systems and then back to the tool. This exposes your data to errors and vulnerabilities.
Many generic AI tools don’t come with built-in controls, so you can’t track their outputs or decisions back to sources. Their data analytics also can be generic. Yes, AI literacy can help you generate better results with these tools. But GRC requires a tool specifically designed to meet its demands.
GRC Native AI Tools vs Generic Tools: A Clear Comparison
GRC native AI tools embed artificial intelligence at the platform level. Their models consider the unique context of how you do business, so they generate more accurate, tailored responses than generic tools. This makes them a more reliable option for GRC operating under strict regulatory standards.
Here is a side-by-side GRC native AI and generic tool comparison.
Data Handling
Generic AI tools usually require data uploads to external or third-party clouds, as they operate outside of a company’s ecosystem. This makes financial records and sensitive customer data vulnerable to breaches that can lead to serious risks. In banking, for example, one misplaced export could trigger regulatory scrutiny and fines.
GRC native AI tools keep everything in-platform. They process everything in a secure, controlled environment using encrypted storage and role-based access controls. This keeps data confined to only authorized servers and eliminates the risk of vulnerabilities.
Efficient GRC AI-native applications go further by automating workflows end to end. Predictive modeling runs on live risk data and flags anomalies in real time.
Governance
With many generic tools, AI responses and records disappear post-generation, making it difficult to trace any changes in your records during audits. GRC native AI tools are designed to meet compliance requirements.
AI-native technology keeps detailed audit lots of changes to records. This means you can easily trace a predictive risk score back to its data sources and algorithms.
Your team can also set rules for AI behavior by defining the business context to make sure outputs align with your organizational policies.
Integration
When it comes to data integration or transfer, generic AI tools may require manual copy-paste from legacy systems to external servers. This disconnection often calls for data breaches and vulnerabilities.
GRC native AI unifies it all through an AI native architecture. These models come with direct APIs that connect to ERPs, CRMs or HR platforms and feed data into analytics without human touch. With an efficient GRC tool, you can even customize your integrations visually and add triggers for vendor risk alerts.
For example, Onspring, a GRC native AI tool, comes with native integrations that allow users to pull data from their systems into the platform to stay informed on changing compliance frameworks and regulations.
When it comes to cybersecurity, Onspring can be easily integrated with Bitsight, Black Kite and Security Scorecard. For file sharing, the platform is compatible with OneDrive and Google Drive. Not only that, but you will also get productivity integrations with Microsoft 365, Docusign and Slack.
These third-party integrations give you greater visibility into your systems, so you’re always in control of what’s getting in and going out.
Efficiency Gains
Generic tools promise quick wins, but they sometimes deliver inconsistent or inaccurate outputs. They require your team to continuously monitor them to make sure they’re generating relevant results. This keeps your staff constantly occupied, which may compromise your overall productivity and efficiency.
A GRC native AI tool works on its own and delivers results that you can track and trust. They need little to no human intervention, so your workforce can focus on more important things and boost overall productivity.
In fact, according to users, efficient GRC software like Onspring can deliver immediate ROI to enterprises. Many businesses have reported as much as a 70% increase in GRC efficiency, 40% reduction in time spent on coordination and 100% connectivity across the firm. Moreover, Onspring allows them to launch their first program in less than 30 days.
Why Onspring’s GRC Native AI Fits Your Team
Onspring stands out with the connected GRC suite. It offers risk, compliance, policy, audit and third-party risk management, all in one centralized system. As operations grow, this setup brings visibility and automation, adapting to evolving needs without added complexity.
Native AI frees teams to focus on high-value work that demands human judgment. It handles routine tasks, such as spotting duplicate incident reports and overlapping risks across departments, while keeping programs clean.
Onspring’s AI can even review a third-party SOC2 report. It automatically pulls key details, like exceptions, into fields, which saves data entry time and improves accuracy. This AI-native platform also works wonders for policy drafting with its context-aware sentence completion capabilities.
Here is a quick overview of Onspring’s GRC management features:
- Map Governance Frameworks: Align International Organization for Standardization (ISO), National Institute of Standards and Technology (NIST) or Cybersecurity Maturity Model Certification (CMMC) standards to controls with ease.
- Break Down Silos: Automate workflows, testing and attestations across teams for unified management.
- Assess Risks Proactively: Create risk registers that identify weaknesses, match your tolerance and automate assessments for smarter decisions.
- Manage Vendors Effectively: Tier suppliers, integrate cyber/financial ratings and control access to sensitive data to protect data privacy.
- Monitor Performance Live: Dashboards show key metrics, risk scores and audit status at a glance.
Onspring’s no-code flexibility empowers finance, healthcare and manufacturing professionals to implement GRC without any tech knowledge. Connect with the team to explore more about this GRC native AI platform.
Discover How GRC Native AI Tools Ensure Compliance
The complex standards of GRC call for native AI tools trained and designed for compliance. To learn more, download our ebook Blank Page to GRC Ready: How AI is Accelerating Documentation, Standardization and Compliance Review.
