Five AI Skills Every HR Professional Should Be Building

A practical guide to using AI confidently, responsibly, and strategically at work.

By Leilani Decena, SHRM-SCP | Founder, AI x HR Studios

Think about your last workday.

How much time did you spend responding to emails, preparing reports, answering routine questions, or tracking down information?

Now think about the conversations you didn't have time for. The manager who needed coaching. The employee experience you wanted to improve. The workforce problem you wished you could investigate.

Here's what I've been wondering:

If AI helps us spend less time managing HR processes, could it give us more time to actually shape the workplace?

That's the conversation I think we need to be having.

Because while everyone seems to be talking about what artificial intelligence can do, I'm interested in what it could make possible for the people doing the work.

And for HR professionals, I believe the opportunity goes well beyond learning how to write a better prompt.

HR Isn't Just Adopting AI. We're Helping Shape What Comes Next.

My career has taken me from television journalism and communications to human resources, learning and development, and now AI education and consulting.

At first glance, those fields might seem worlds apart.

But they've taught me something important about people, information, and change.

In television, I learned how to ask better questions, separate facts from assumptions, work under pressure, and turn complicated information into stories people could understand.

In HR and learning and development, I saw how much time goes into managing processes, explaining policies, developing employees, supporting leaders, and helping people navigate change.

Those experiences influence how I approach AI today.

I don't begin by asking what the technology can do.

I begin by asking what people are trying to accomplish, what's getting in their way, and whether there's a better way to work.

And the more I explore AI, the more I see how relevant HR's existing capabilities are to this moment.

Think about it.

When organizations introduce new technology, someone needs to assess its impact on employees, communicate what's changing, establish expectations, develop training, address concerns, and evaluate results.

HR already knows how to do much of that work.

But there's a catch.

We can't confidently help others navigate AI if we're not developing our own understanding of it.

That doesn't mean every HR professional needs to become a programmer, data scientist, or AI engineer.

It means learning enough to recognize opportunities, ask informed questions, evaluate risks, and make thoughtful decisions.

Here are five skills I'd prioritize.

1. Learn to Communicate With AI, Not Just Prompt It

You've probably heard the term prompt engineering.

It can sound technical, but the foundation is something HR professionals already understand: clear communication.

Think about onboarding a new employee.

You wouldn't simply say, "Handle recruiting," and expect that person to understand your organization's policies, priorities, communication style, and expectations.

You'd explain the assignment, provide context, establish boundaries, and review the work.

Working with AI requires many of those same habits.

Let's say you're preparing an onboarding email.

You could type:

"Write an onboarding email."

You'll probably get something.

But will it reflect your organization's culture? Will it include accurate information? Will it sound welcoming rather than generic?

Here's a stronger approach:

Try this prompt:

"Help me draft a welcoming onboarding email for a new employee starting Monday. Use a warm, professional tone. Include placeholders for first-day instructions, the schedule, and HR contact information. Don't invent names, policies, benefits, or dates. Flag anything that needs my confirmation before sending."

Notice what's different.

You've explained the task, audience, tone, expectations, and boundaries.

You're not simply asking AI to produce something. You're giving it a clearer assignment.

And just as you would review work prepared by a colleague, you still need to review what AI produces.

The skill to build: Give AI clear instructions, provide appropriate context, establish guardrails, and evaluate the results.

2. Learn to Recognize Opportunities for Better Workflows

HR professionals are constantly managing processes.

Recruitment. Onboarding. Employee relations. Performance management. Learning and development. Compliance. Workforce planning.

We understand responsibilities, approvals, documentation, and accountability.

Those skills translate surprisingly well into designing AI-assisted workflows.

But I encourage people to resist the temptation to automate something simply because they can.

Start by understanding the work.

Imagine your HR department receives the same questions about training requirements every week.

Before purchasing a chatbot, ask a few questions.

Where are employees looking for information? Are the training requirements easy to understand? Are the documents current? Why are people having trouble finding answers?

Maybe the solution is a clearer employee resource page.

Maybe AI can help create a searchable guide using approved materials.

Or perhaps an AI-supported assistant could help employees find routine information while directing complicated or sensitive questions to HR.

The right solution depends on the problem.

Try this: Choose one repetitive HR task and write down the steps involved. Identify where delays occur, which steps require human judgment, and where AI might help.

Sometimes a well-written prompt will do the job. Sometimes you'll need a repeatable workflow. And sometimes AI isn't necessary at all.

The skill to build: Understand how work happens before deciding how technology should change it.

3. Build Confidence With Data and People Analytics

HR has access to information that can help organizations make better decisions.

Turnover. Retention. Absenteeism. Training participation. Employee engagement. Recruiting activity. Workforce demographics.

But collecting data and understanding what it means are two very different things.

That's one reason I've continued investing in my own People Analytics education.

I believe HR professionals need to become increasingly comfortable translating workforce information into insights that business leaders can understand and act on.

AI can help us explore that information.

Imagine you're reviewing an appropriately anonymized employee turnover dataset.

You could ask AI to help identify trends, compare periods, create a chart, or suggest questions worth investigating.

But suppose turnover appears higher in one department.

Does that mean the manager is the problem?

Not necessarily.

There could be scheduling challenges, compensation concerns, career development issues, seasonal changes, or problems with the data itself.

AI doesn't automatically understand your organization's circumstances.

That's where your knowledge and professional judgment matter.

Try this: Use a fictional HR dataset and ask AI to identify three trends, create a simple visualization, and suggest possible explanations.

Then challenge the results.

Are the calculations accurate? What assumptions did AI make? What information is missing? What would you need to know before presenting a recommendation?

The skill to build: Use AI to explore information while applying data literacy, business understanding, and critical thinking to the conclusions.

Because a dashboard may show you what's happening. Understanding why it's happening requires more investigation.

4. Learn to Evaluate AI, Not Just Use It

Here's something I emphasize when teaching AI:

Just because an answer sounds confident doesn't mean it's correct.

AI can produce beautifully written responses containing inaccurate information, unsupported claims, or fabricated references.

That's frustrating when you're brainstorming.

It's potentially much more serious when you're dealing with compensation, employment policies, employee relations, or regulatory compliance.

Imagine asking AI to summarize a workplace regulation.

The response looks professional. The explanation sounds reasonable. It even includes what appears to be a legal citation.

Would you use it without checking?

I hope not.

HR professionals need to know how to verify AI-generated information, recognize limitations, and identify situations requiring expert review.

We also need to understand what information can and cannot be shared with an AI system.

Employee medical information, personnel records, compensation details, confidential investigations, and other sensitive information require particular care.

And when AI is involved in employment decisions, we need to consider fairness, accessibility, privacy, applicable laws, and accountability.

AI doesn't automatically eliminate bias. Depending on how a system is developed, deployed, and monitored, it can introduce or reinforce unfair outcomes.

Try this: Ask an approved AI tool to summarize publicly available HR guidance.

Compare its response with the original government or regulatory source.

What did it get right? What did it overlook? Did it make assumptions? Could someone be misled if they accepted the answer without checking?

The skill to build: Develop a healthy habit of verification, risk awareness, and human oversight.

Responsible AI isn't about being afraid of technology.

It's about understanding the consequences of how we use it.

5. Learn How to Help People Adapt to AI

This may be the most important skill on the list.

An organization can invest in impressive technology and still struggle to see meaningful results.

Why?

Because people may not understand it, trust it, or know how to incorporate it into their everyday work.

Managers may have unrealistic expectations.

Employees may worry about accuracy, privacy, job security, or how their performance will be evaluated.

Others may enthusiastically experiment without understanding the risks.

And some people simply don't have the time or support to learn another technology.

These aren't just technical problems.

They're workplace challenges.

And they're exactly the kinds of challenges HR professionals are accustomed to navigating.

We know how to assess learning needs, develop training, communicate changes, coach managers, and establish expectations.

We also know that people are more likely to engage with change when they understand why it matters and have opportunities to participate.

That's why I believe employees should be part of conversations about AI implementation, not simply informed after decisions have been made.

The people doing the work often know where processes are frustrating, where mistakes happen, and what could be improved.

Their perspectives matter.

Try this: Ask five colleagues what they find most exciting, confusing, or concerning about using AI at work.

Listen carefully.

Their answers may reveal training needs, workflow opportunities, or concerns that leadership hasn't considered.

The skill to build: Connect AI adoption with communication, employee involvement, learning, trust, and thoughtful change management.

Technology can change a process.

People determine whether that change actually works.

Where Are You in Your AI Learning Journey?

One thing I've noticed when speaking to groups about AI is that people often arrive with very different levels of experience.

Some are opening ChatGPT or their favorite AI tool for the first time.

Others already use AI to draft communications, brainstorm ideas, or summarize information.

And some are ready to build repeatable workflows or lead AI initiatives across their teams.

There's no reason everyone should be learning exactly the same thing.

Here's how I'd think about the next step.

If You're Just Getting Started

Focus on understanding what generative AI can and cannot do.

Practice giving clear instructions, reviewing outputs, protecting confidential information, and recognizing when AI isn't appropriate.

You don't need to learn every feature.

Start with one low-risk task.

If You're Already Using AI

Move beyond isolated prompts.

Look for repetitive work that could benefit from a more consistent process.

Explore how to organize context, create reusable instructions, evaluate outputs, and establish human review checkpoints.

The goal is to move from occasional experimentation toward dependable, repeatable practices.

If You're Leading a Team

Think beyond your personal AI skills.

What does your team need to know? Which tools are approved? What policies or guidelines are necessary? How will you provide training and support?

And perhaps most importantly, how will you know whether AI is actually improving the work?

Start with one well-defined pilot, involve the people affected, establish meaningful measures, and learn from the results.

Whatever stage you're in, the objective isn't to collect AI tools.

It's to build capabilities you can apply with confidence.

How Should HR Professionals Choose AI Training?

There's no shortage of AI courses, webinars, certifications, and professional development opportunities.

I understand the appeal. I'm a lifelong learner myself.

My SHRM-SCP certification, SHRM AI+HI Specialty Credential, People Analytics education, and continued AI studies have helped me connect emerging technology with the knowledge and experience I've built throughout my career.

But I also believe that taking another course isn't automatically the same as building a useful skill.

Before enrolling, ask:

What will I be able to do differently when I finish?

Look for learning opportunities that help you apply AI to realistic situations, evaluate results, understand responsible use, and connect technology to business and people outcomes.

Organizations such as SHRM and IHRIM offer HR-focused professional development and resources. Learning platforms such as Coursera, edX, and LinkedIn Learning also provide AI education.

Compare the curriculum, instructor qualifications, practical exercises, cost, and credential requirements before committing.

And don't underestimate hands-on practice.

Some of the most useful learning happens when you experiment with a realistic problem, discover what doesn't work, improve your approach, and try again.

Formal education can provide structure.

Practical application helps turn that knowledge into capability.

You need both.

Your 10-Minute HR + AI Experiment

Want to put one of these skills into practice?

Here's a simple exercise you can try today.

You don't need confidential employee information or a complicated AI system.

Just an approved AI tool and a fictional HR scenario.

Step 1: Choose a familiar task.

Let's use onboarding.

Imagine you're preparing a first-week onboarding checklist for a new employee joining a fictional 50-person professional services firm.

Step 2: Give AI a clear assignment.

Try this:

"Act as an HR onboarding coordinator. Create a practical first-week onboarding checklist for a new employee joining a fictional 50-person professional services firm.

Organize the checklist by day. Include introductions, equipment setup, required administrative activities, role-specific learning, manager check-ins, and opportunities to ask questions.

Identify who should be responsible for each activity.

Don't invent company-specific policies or legal requirements. Mark anything that needs organizational confirmation. Use a welcoming, clear, professional tone."

Step 3: Review the result.

Does the checklist make sense?

Are responsibilities clear?

Did AI overlook something important?

Are there assumptions that need to be corrected?

What would you change based on your HR experience?

Step 4: Improve it.

Give AI feedback and ask for a revision.

Then compare the two versions.

Step 5: Decide whether it helped.

Did you save time?

Was the result useful?

What still required your expertise?

Would you use the process again?

Congratulations. You've just practiced prompting, workflow thinking, evaluation, and human oversight.

And perhaps you've discovered a better way to approach a familiar task.

That's a meaningful first step.

The Future of HR Needs Your Judgment, Not Just Your Prompts

I don't believe HR professionals need to become technology experts to remain valuable.

But I do believe we have a responsibility to understand how AI is changing work, how it affects people, and what organizations need from us next.

We already bring many of the skills this moment demands.

Communication. Critical thinking. Business understanding. Learning design. Ethical judgment. The ability to guide people through change.

AI gives us an opportunity to apply those strengths in new ways.

The question isn't simply whether we can learn to use AI.

It's what we'll choose to do with those capabilities once we have them.

Will we use AI only to complete administrative tasks faster?

Or will we use some of that newly available capacity to strengthen the work that makes HR valuable: developing people, supporting leaders, improving employee experiences, and helping organizations make better decisions?

I know which direction interests me.

Because the future of HR shouldn't be defined only by what we can automate.

It should also be defined by what we can make better for the people doing the work.

Let's Build Your AI Confidence and Capabilities

If you're an HR professional wondering where to begin, or an HR leader preparing

your team for an AI-enabled workplace, you don't have to navigate it alone.

At AI x HR Studios, I help HR professionals, business leaders, and teams move from AI curiosity to practical application.

My focus isn't simply teaching you what buttons to click.

It's helping you understand the possibilities, strengthen your judgment, improve workflows, and develop the confidence to use AI responsibly in the work you actually do.

Whether you're learning the basics or ready to move beyond prompting, we can start with one meaningful improvement.

Let's make AI less intimidating, more practical, and genuinely useful for the people and organizations we serve.

Explore AI training, customized team workshops, and workflow strategy services at AI x HR Studios.