Gen is expanding AI privacy checkers with AI Data Checker, a beta tool designed to show consumers how AI apps and agents interact with their personal information. Users can enter an email address or username to identify connected AI services as well as other accounts that may contain shared personal data. The tool then surfaces information about what each service collects, whether data may be used to train or improve AI models, how long information may be retained and which privacy controls are available.
For Gen, the tool extends its cybersecurity portfolio into emerging concerns surrounding agentic AI and personal data. Providing privacy information in one centralized interface can make complex policies more accessible as consumers give AI services greater access to their digital lives. AI Data Checker also strengthens Gen’s broader Agent Trust Hub, creating opportunities to connect privacy visibility with its existing agent protection, VPN and security products.
Image Credit: Gen Digital Inc.
Why This Trend Is Growing
- AI Data Transparency
- Centralized visibility into how AI tools collect, retain and train on personal data creates room for privacy dashboards that simplify complex policy language for everyday users.
- Agentic AI Trust
- As autonomous AI agents gain access to accounts and workflows, trust infrastructure can evolve around permission monitoring, data-use verification and consumer-facing security signals.
- Privacy-aware Cybersecurity
- The convergence of privacy management and cybersecurity expands product ecosystems that combine threat protection, identity controls and AI-specific data oversight.
Industries Being Reshaped
- Cybersecurity
- Security providers can differentiate by embedding AI data exposure insights into existing protection suites for consumers and enterprises.
- Privacy Technology
- Demand for clearer data rights and consent management supports new platforms that translate AI service policies into accessible, actionable privacy intelligence.
- Consumer Software
- Apps that handle personal information face growing pressure to offer transparent AI data practices, creating competitive value through built-in privacy controls and user education.
