Data Privacy in the AI-Powered Workplace
As AI becomes central to HR workflows, data privacy is more important than ever. Here's how we approach enterprise-grade security and compliance.
February 14, 2025 · 6 min read · Priya Nair, Security Engineer
HR data is among the most sensitive information in any organization — it includes salaries, performance ratings, medical accommodations, disciplinary records, and personal contact details. Introducing AI into these workflows raises the stakes on data governance considerably.
The Core Privacy Risks
There are three categories of risk that HR and security teams need to evaluate when adopting AI tools: data exposure (who can see what), data retention (how long is it stored and where), and model training (is your data being used to train third-party models?).
- Data exposure: Role-based access controls and field-level encryption
- Data retention: Clear policies on purge schedules and audit logs
- Model training: Contractual guarantees that your data is never used for training
- Cross-border transfers: Compliance with GDPR, PDPA, and local data residency laws
Our Approach to Security
We built our platform with a security-first architecture from day one. All data is encrypted at rest and in transit. We undergo annual SOC 2 Type II audits, and we offer data residency options for customers in the EU, Singapore, and Australia.
We never use customer data to train our models. Your employee data belongs to you — always.
Questions to Ask Any AI Vendor
Before signing a contract with an AI HR vendor, ask these questions: Where is data stored? Who has access to it within the vendor's organization? How is access logged and audited? What happens to data if you leave? Can you delete all data on request?
A reputable vendor will answer all of these questions clearly and in writing. If they can't, treat that as a red flag.