How HR Can Overcome AI Data Privacy & Compliance Concerns.

A Practical Roadmap for HR's Safe AI Adoption

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Happy Tuesday,

Today is more of a practical one, because a lot of HR leaders I speak with worry about using generative AI because they're concerned about data privacy and compliance—and understandably so!
After all, we’re handling sensitive employee data, like personal details, pay, and performance records, means we must tread carefully.

But don't let this stop you from exploring AI!

What I've tried to do here is to summarize my best tips and the common things I've helped or seen companies and organisations do when it comes to data privacy and compliance. Following these steps also aligns closely with the EU AI Act requirements—a big bonus if you're operating within the EU!

So here's a practical, step-by-step guide to help overcome these common concerns in an easy and non-technical way!

Listen to the article - powered by ElevenLabs - try it for free here.

Step 1: Understand the data you're handling

Start by clearly identifying the types of data your HR team handles:

• Personal information (names, addresses, etc.)

• Performance reviews and feedback

• Payroll and compensation details

• Recruitment and candidate data

Knowing exactly what data you have will clarify what needs protection.

One of the HR teams I supported began their AI exploration with a thorough data audit. We created a simple spreadsheet categorizing all HR data by sensitivity level (high, medium, low).

This approach provided immediate clarity on which data could safely be used with AI tools and identified exactly where stricter controls were necessary.

Step 2: Set clear boundaries

Decide explicitly what data can and cannot be entered into generative AI tools:

• Never input identifiable personal data directly.

• Only use anonymized or aggregated data.

• Set guidelines about who on your team is authorized to use AI and under what conditions.

At a large European car manufacturer I supported, we created a simple but effective "green/yellow/red" system for data usage with AI.

Green data, such as generic job descriptions or public training content, was openly accessible. Yellow data, including anonymized engagement survey results, required managerial approval before use. Red data, like individual performance evaluations or detailed payroll information, was explicitly off-limits.

This clear, color-coded system quickly became an intuitive guide for employees across the organisation.

Step 3: Choose AI tools with built-in compliance

Not all AI tools are created equal. Look specifically for those that:

• Clearly state compliance with GDPR and local data privacy laws.

• Offer data encryption and secure storage options.

• Provide clear explanations of how your data is managed and protected.

It's considered best practice to select AI tools with clear compliance documentation. One organisation I worked with partnered with an external vendor specializing in compliance evaluations, in addition to my assistance.

Together, we reviewed multiple AI providers and ultimately chose one offering comprehensive compliance reports, customizable data retention periods, and transparent data processing agreements.

This external vetting process provided additional reassurance. Today, several organisations offer similar compliance review services to independently verify AI vendors, simplifying the selection process for HR teams.

Step 4: Establish nterinal guidelines and training

Make sure your HR team feels comfortable and confident with AI:

• Create simple, straightforward guidelines on AI usage.

• Train your team regularly on data privacy basics and AI-specific practices.

• Encourage open dialogue about any concerns or uncertainties.

One organisation, which participated in one of my open training sessions, developed a practical 30-minute "AI Safety for HR" training program featuring real-life scenarios.

After completing the training, 85% of their HR team reported increased confidence in using AI tools responsibly. Additionally, they implemented monthly "AI office hours," providing team members dedicated time to ask questions and receive support on specific AI use cases.

Step 5: Partner with IT and legal

Collaborate early and often:

• Engage your legal and IT departments to review tools and practices.

• Develop simple checklists or approval processes together.

• Keep open lines of communication to quickly address any issues that arise.

At my own organisation, we've established a joint cross-functional "AI governance team" that includes representatives from HR, IT, and Legal departments. This group meets bi-weekly to proactively address AI-related concerns and opportunities.

Together, we've streamlined the approval process by creating a concise, one-page document that simplifies new AI use case evaluations, cutting the decision-making timeline from weeks down to just 48 hours.

Step 6: Regularly review and update practices

Compliance isn't a "set and forget" task:

• Schedule regular reviews (e.g., quarterly) to check your practices against current laws.

• Adjust your policies and training as new regulations emerge or your business evolves.

At one organisation, a dedicated cross-functional AI governance team regularly reviews AI practices, particularly when expanding operations into new regions. Recently, this team proactively assessed local data privacy laws, quickly identifying and implementing three critical adjustments to their AI processes.

This collaborative approach allowed the organisation to smoothly avoid potential compliance issues, showcasing the benefits of having a structured, cross-functional team in place.

Step 7: Document your processes

Keep a clear record of:

• How and why you use AI.

• Measures you've taken to ensure compliance.

• Training provided to your HR team.

Clear documentation not only helps with compliance but also builds trust internally.

Establishing an "AI use registry" is becoming a best practice and aligns closely with upcoming requirements under the EU AI Act. This registry documents all HR AI applications, clearly outlining their purpose, data involved, and the specific measures taken to manage risks.

Although I've yet to see this fully play out in practice, this structured approach is exactly how organisations should aim to manage and document their AI use, ensuring compliance and facilitating smoother audits and reviews.

These are certainly not all the steps you could take, but they're practical measures and inspiring examples that hopefully reduce the "oh, this isn't safe" hurdle. By staying informed and keeping the dialogue open, you'll navigate these challenges more confidently and safely integrate AI into your HR processes!