Artificial intelligence (AI) is rapidly changing the world as we know it.
The rise of generative AI technologies like OpenAI’s ChatGPT, Anthropic’s Claude, and Google’s Gemini is rapidly changing how brands provide value to their customers or evolving operational aspects of their business. Recently, Klarna, a Swedish Fintech company, announced that its AI assistant is handling the workload equivalent to 700 full-time staff members. From self-driving cars to facial recognition software and even retail, AI is already having a transformative impact on our lives.
And that’s why we just announced our solution, DataGrail for AI Governance.
With all of the benefits that AI brings, it also exposes additional risk vectors, a primary one being the risks associated with data privacy and handling of personal identifiable information. AI systems, both first and third party, can easily collect and process vast amounts of data simply by having it entered into a chat box. With many of these services available as web apps, as a Security or Privacy leader, it’s likely very difficult to detect the use of shadow AI, let alone the data that might be funneling into those services.
What is AI governance?
Enter AI governance: the process of managing the development and use of AI in a responsible, ethical, and privacy aware manner. It involves discovery of AI systems, both known and unknown, controls and policies around those AI services, and the ongoing monitoring of AI services. AI governance is all about reducing the data privacy risk businesses incur when opting to use these technologies or when employees use them without proper vetting.
How DataGrail can help with AI governance
At DataGrail, we believe that privacy is a human right and that privacy can and should be used as a key brand differentiator. DataGrail’s AI Governance solution can help organizations to manage their AI risk and instill confidence with their end customers. Our solution helps with:
- Discovering shadow AI systems: DataGrail can help organizations discover AI systems that are being used without their knowledge or approval. Shadow AI systems can pose a significant data privacy risk as Personal Identifiable Information (PII) data may be flowing to these systems without knowledge and proper controls. DataGrail’s system detection has been proven to identify and surface both known and unknown AI services to our customers, allowing organizations to take the appropriate actions against those systems.
- Managing data subject requests against AI systems and services: DataGrail can help organizations manage data subject requests against AI systems and services. This includes providing data subjects with access to their data, correcting inaccurate data, and deleting data.
- Completing risk assessments against GenAI services: DataGrail’s risk monitor product can help organizations conduct risk assessments such as Privacy Impact Assessments (PIAs) or Data Protection Impact Assessments (DPIAs) against AI systems and services. This can help organizations to identify and mitigate AI risks related to data privacy.
In response to customer demand, we also created a Responsible AI Use Principles & Policies Playbook, providing a framework for businesses to develop their own customized AI principles and policy based on their brand values.
Here at DataGrail, we believe in getting user feedback and actioning on it quickly. We ship improvements to our platform on a daily basis and believe that iterating quickly with small improvements is the best way to ensure we’re building the right things for our customers as well as stay ahead of where the market is moving.
For many businesses, the AI journey is just getting started and we’re honored to help serve as a guide for how to govern and manage AI data privacy risks. Reach out at eric [dot] brinkman [at] datagrail [dot] io if you’d like to discuss further!