AI in HR is booming, but is your HR data secure?

Quick Takeaways:

• AI in HR unlocks huge potential, but only if data privacy and security are taken seriously
  
  
• 63% of HR pros cite data protection as their #1 concern when adopting AI tools
  
  
• Responsible AI means internal infrastructure, transparent decision logic, and regular bias audits
  
  
• You don’t need to have a law degree to navigate the red flags, just choose tools built with privacy by design and clear governance in mind

AI Privacy & Security HR Stats

Talentech’s HR AI was built to meet these expectations and exceed them.

How to Stay Compliant When Using AI in HR

You don’t need to be a lawyer to stay on the right side of data regulations. But you do need to know the basics.

1. Protect the Data

The EU’s GDPR legislation and the incoming AI Act put HR teams on the hook for how AI collects, stores, and uses data.

That means:

• Only collecting the data you need
• Encrypting it properly
• Keeping it for a set period (and not forever)
• Making sure employees know their rights

Tip: Choose tools that build data protection into the design (aka “privacy by design”). If you’re duct-taping AI features onto a creaky old HR system, it’s time to upgrade.

1. Protect the Data

The EU’s GDPR legislation and the incoming AI Act put HR teams on the hook for how AI collects, stores, and uses data.

That means:

• Only collecting the data you need
• Encrypting it properly
• Keeping it for a set period (and not forever)
• Making sure employees know their rights

Tip: Choose tools that build data protection into the design (aka “privacy by design”). If you’re duct-taping AI features onto a creaky old HR system, it’s time to upgrade.

2. Get Employee Consent

You can’t just flip the AI switch and hope nobody notices. Consent matters.

Let employees know:

• What data is being collected
• How AI is being used (e.g. screening, scoring, monitoring)
• How they can opt out or ask questions

If you’re not sure where to start, think about how you’d want to be treated, and go from there.

3. Ditch the Black Boxes

Some AI tools are built like fortresses; no one knows how decisions are made, not even the vendor.

That’s a risk.

HR needs explainable AI, tools that can tell you how and why a decision was made. If you can’t trace the output, you can’t trust it.

According to Talentech’s CPO Malin Gustafsson, “Our approach is human first, AI supported. That means transparency isn’t a feature, it’s a foundation.

What to Look For in AI-Driven HR Tools

Choosing the right AI tool isn’t about chasing shiny features. It’s about protecting your people, your data, and your credibility. With new tools flooding the market, it's easy to get overwhelmed by sleek visuals and flashy dashboards. But underneath it all, what matters most is how a tool handles risk, bias, transparency, and control. 

Here’s what to demand from vendors and some red flags that should send you running:

1. Internal Infrastructure and No Third-Party Dependencies

AI that handles HR data should be built with the same care you’d expect from any secure enterprise system. If your provider is relying on external platforms like ChatGPT to process candidate or employee information, that’s a major risk. You need to know exactly where your data is going, who can access it, and whether it's being used to train other people’s tools.

❓ Ask your vendor: how their AI infrastructure is built. Is it developed and hosted in-house? Do they use any third-party APIs or open platforms for AI processing? Who owns the data? 

Malin Gustafsson, Talentech’s Chief Product Officer, explains: “We built our infrastructure internally to avoid third-party dependencies and retain full control over data use and compliance”.

That’s not just a preference, it’s a requirement for HR-grade tools.

🚩 Red flag: If a vendor can’t give you a straight answer about where your data is being processed or stored, or defaults to vague claims like “it’s anonymised” or “secure by default”, it’s time to walk away.

2. Continuous Bias Monitoring (Not Just a One-Time Audit)

Bias isn’t a bug you fix once; it’s a risk you manage constantly. As models evolve and new data is introduced, AI outputs can shift subtly in ways that impact fairness and compliance. If a tool promises “bias-free” decision-making without ongoing testing, it’s marketing spin.

❓ Ask your vendor how often they test for bias, and how they do it. Do they run simulations with deliberately skewed data? Are their models monitored for changes in performance across age, gender, ethnicity, or disability? 

Talentech, for example, runs weekly audits and includes stress testing using adversarial prompts to catch blind spots before they affect real people.

🚩 Red flag: If a vendor says their model passed a fairness test last year and hasn’t reviewed it since, or if they only test for bias after client complaints, they’re not taking the security of your data seriously enough.

3. Transparent Logic and Explainable AI

HR decisions carry weight. Whether it’s choosing who gets hired, who’s flagged for promotion, or who’s considered a flight risk, you need to understand how those decisions are made and be able to explain them if and when challenged. That means using AI tools built on explainable logic, not black-box algorithms.

❓ Ask your vendor whether their AI provides traceability. Can they show the factors used in a decision? Is it clear how different inputs influenced the outcome? Do users get insight into why a recommendation was made, or is it just a score with no explanation?

🚩 Red flag: If a vendor says the model is “too complex to explain,” or treats explainability like a future feature instead of a core requirement, they’re exposing you to compliance and reputational risk.

4. Customisation, Control, and Clear Governance

Every organisation has different policies, priorities, and risk tolerances. Your AI tools should reflect that. Off-the-shelf models that can’t be tuned or monitored are potential mine fields, especially if you can't control what data they use, how they operate, or when they intervene.

❓ Ask your vendor what kind of controls you have. Can you adjust thresholds for recommendations or decisions? Can you disable features or run audits internally? Is there a governance framework in place that HR can actually use, without needing a data science degree?

🚩 Red flag: If the vendor takes a "set it and forget it" approach or insists that all configuration needs to go through their tech team, you're not in control, and that's a problem.

The takeaway

AI in HR isn’t optional anymore. But trust, privacy, and ethics aren’t optional either.

The good news? You don’t need to compromise.

By choosing tools that are transparent, secure, and built with compliance in mind, you can put AI to work without losing sleep.

Remember: AI should amplify your HR team, not undermine it. Keep the focus on people, protect their data like it’s your own, and partner with vendors who take that responsibility as seriously as you do.

Ready to bring secure, compliant AI into your HR stack? We can help!

Talentech gives you more than just smart features. Our all-in-one HR platform combines practical, purpose-built AI with the security and flexibility your team needs to thrive. From recruitment to onboarding, policy to planning, everything works together so you can focus on people, not patchwork systems.

If you’re ready for AI that’s built for HR (not just bolted on), let’s talk!

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