DataGrail for AI Governance
Innovate with AI, without worrying about the data privacy risks
48% of CISOs claim AI security is now their biggest concern.
On top of keeping up with new data privacy laws, increasing third-party risk, ongoing cyberattacks, and rising consumer data privacy expectations, CISOs now have to figure out this new black box – AI.
52% of security professionals say they are finding it difficult to safeguard confidential and personal data used by AI. So while everyone scrambles to embrace generative AI to increase efficiency, CISOs are tasked with understanding the data risk impact, what it has access to, data sources, and data classification.
Discover traditional and generative AI
Continuously discover what traditional and Generative AI models are being used throughout your SaaS & third-party systems.
Stay up-to-date on new AI systems and models in your organization.
Quickly detect LLMs and GenAI with our integration network of 2,000+ enterprise apps, data platforms, and internal systems.
Orchestrate data requests across your AI systems
No matter where personal information lives across your AI systems, DataGrail will orchestrate deletion, access, and opt-out requests.
- Process data requests for your internal models via Internal Systems Integration (ISI) agent with Request Manager.
- Enable your privacy operations on top of any internal and third-party systems using AI.
Monitor AI risks in SaaS
Identify and manage the AI risk in your third-party vendors.
- Easily extend your Data Protection Impact Reports (DPIAs) or Privacy Impact Assessments (PIAs) in Risk Monitor to uncover risk in third-party SaaS.
- Utilize existing workflows to help understand the AI risks in the third-party SaaS you use.
- Be prepared for the changing AI regulatory landscape, including the EU’s AI act and California’s automated decision-making enforcements.
Wondering what to ask your vendors? Check out these questions you can use in your vendor assessments to quantify AI risks.
DataGrail’s responsible AI use principles
Know our why behind AI
Responsibly explore how AI can benefit our business and customers.
Respect all individuals
To the best of our ability, we will not use AI that could compromise an individual’s right to consent or to privacy.
Be real and transparent
We will be upfront with customers about when and how we use AI in our products and services.
Seek guidance from a diverse team
We will actively seek guidance from diverse peer groups and cross-functional leadership to ensure alignment on goals and no potential risk is missed.
The trusted leader in data privacy
FAQ
What is AI governance and why does it matter?
AI governance is the framework that helps organizations use AI responsibly. It sets clear rules for how data is collected, trained, and applied so decisions are fair, transparent, and compliant. Strong governance reduces risk, protects customers, and builds trust in the way your business uses AI.
How do companies ensure responsible AI use?
It starts with visibility and accountability. Companies that use AI responsibly put policies in place around data sourcing, model training, and decision-making. They run regular audits, test for bias, and make sure systems align with privacy laws. The goal isn’t to slow down innovation, it’s to use AI in a way that customers can trust.
What are the risks of not having AI governance in place?
Without governance, AI can introduce real risks: biased results, data misuse, regulatory penalties, and damage to brand reputation. Once trust is lost, it’s hard to win back. A governance framework helps organizations spot and manage these risks before they become costly problems.
How does AI governance support regulatory compliance (GDPR, CCPA, etc.)?
Privacy regulations require businesses to understand how personal data is used, and AI is no exception. Governance ensures AI models rely on compliant data sets, respect individuals’ rights, and maintain audit trails. This makes it easier to show compliance and build trust with regulators and customers alike.
What is the difference between AI ethics and AI governance?
AI ethics focuses on principles like fairness, accountability, and transparency. AI governance takes those principles and makes them actionable, turning high-level intentions into clear processes, tools, and policies that teams can follow every day.
What tools are available for managing AI governance?
Tools that support AI governance give organizations visibility into how data is used, monitor for risks like bias, and track compliance across regulations. The best solutions integrate with privacy platforms so businesses can manage data and AI governance together in one place.
How to choose a privacy solution that helps with AI governance?
Selecting the right privacy solution ensures AI is used responsibly while keeping your organization compliant. Key factors to consider include:
- Visibility into how personal data is collected, stored, and used by AI systems
- Automated tracking and documentation of data processing activities
- Tools to monitor for bias, ensure transparency, and support compliance with regulations
- Integration with existing systems and workflows for seamless governance
- Scalable support that can adapt as AI initiatives grow
