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Every department in an organization is evolving rapidly, thanks to AI. But for HR leaders, this transformation comes with growing pains.
According to HRE’s “What’s Keeping HR Up At Night?” survey, many HR professionals face increased expectations while working with stagnant budgets. The result? Overburdened teams stuck managing routine tasks that offer little strategic value. If you’ve felt this strain, you’re not alone.
But what if there was a way to break free from this cycle?
The answer lies in AI. While I don’t believe AI can replace human judgment, I firmly believe in its ability to enhance decision-making, improve efficiency, and empower HR teams to focus on what matters most—people.
Like Kristy Sundjaja, Chief People Officer at Taboola, said on Chris Rainey’s podcast, “AI is just one technology that is disrupting work. This is the future… For the right person, this is an exciting time.”
HR should serve as an enabler, helping organizations adopt AI efficiently and strategically. That’s why I reached out to multiple business owners and HR professionals to uncover how real companies are using AI today.
The truth is, nobody—not even AI vendors—can predict exactly how AI will evolve in HR over the next two to three years. Everyone is experimenting. And if you don’t, you risk being left behind.
In this article, we’ll explore the most impactful AI use cases in HR, backed by real-world insights, and address the common fears that hold many teams back from embracing this technology.
16 AI Use Cases In Human Resources
Optimizing Job Descriptions
Biased job descriptions can unintentionally discourage qualified candidates from applying, even when they are a great fit for the role. To reduce bias and improve inclusivity, many companies now leverage AI-powered tools.
AI ensures that job descriptions use engaging and inclusive language, helping companies attract a diverse talent pool while avoiding biased wording. For instance, organizations using Ongig’s AI-powered Job Description platform have successfully eliminated bias in their job postings and increased applications by up to 8x.
👉 Watch this video to see how Ongig’s AI optimizes job descriptions for inclusivity and engagement.
Enabling Employee Self-Service
AI-powered employee self-service tools empower employees to handle routine HR tasks, freeing up valuable time for HR teams.
For example, imagine an employee who needs to confirm her health benefits before scheduling a doctor’s appointment. Instead of emailing HR and waiting hours for a response, she simply types her query into an AI-powered chatbot and receives an instant answer.
By handling common HR inquiries 24/7, AI enhances employee autonomy while allowing HR professionals to focus on strategic initiatives.
Automating Interview Scheduling
Coordinating interviews can be a logistical headache, often involving multiple rounds of back-and-forth emails. AI-powered scheduling tools eliminate this hassle by automatically syncing calendars between recruiters and candidates.
David Haskins, CEO of Wrongful Death Lawyer, shared how AI has streamlined their scheduling process:
“Coordinating interviews used to take days, but AI now syncs calendars quickly. We are booking interviews 40% faster, and top candidates are not leaving for faster-moving firms.”
By accelerating interview scheduling, AI helps companies secure top talent faster and stay ahead in competitive hiring markets.
Reviewing Your Recruiting Experience
AI isn’t just transforming hiring. It’s also helping HR teams evaluate and refine their entire recruiting process.
Kristy Sundjaja, Chief People Officer at Taboola, shared on the HR Leaders podcast how her team is already using AI to analyze their interview consistency and identify key attributes that lead to high-quality hires.
By leveraging AI-driven insights, your HR team can fine-tune their recruitment strategy, ensuring better hiring decisions and improving long-term employee success.
Scheduling Employee Work Hours
Managing employee work hours in industries like retail, healthcare, and call centers is a time-consuming challenge. HR teams must juggle multiple variables, from shift coverage and labor laws to unexpected absences and spikes in demand.
Josh Bersin, a leading HR industry analyst and founder of The Josh Bersin Company, shared on his podcast that he’s working with companies that use AI-powered scheduling tools to create efficient, demand-based shift plans. These AI systems analyze real-time workforce data, ensuring that schedules are optimized while accounting for business constraints and employee availability.
Automating Resume Scanning
For HR teams handling hundreds or even thousands of applications per job opening, manually reviewing every resume is inefficient.
AI automates resume screening, allowing recruiters to focus on engaging with top talent rather than sifting through piles of applications. Modern AI tools can scan resumes at scale, extract relevant keywords, and match them to job requirements, dramatically reducing manual workload.
Michael Nemeroff, CEO of RushOrderTees, shared how AI transformed his team’s hiring process:
“We integrated Workday’s AI-driven workforce management tool to handle hiring and scheduling. The biggest win was in recruitment—we cut down resume screening time by 40%, letting HR focus on interviewing quality candidates.”
By implementing AI for resume screening, your organization can improve hiring speed, candidate experience, and recruiter efficiency.
Workforce Analytics
If your HR team wants deeper insights into workforce performance, AI-powered analytics tools offer a powerful solution.
These tools analyze large volumes of HR data, including employee demographics, performance metrics, and engagement trends. AI can then generate visual dashboards and predictive insights, helping HR leaders make data-backed decisions.
With AI-driven workforce analytics, HR teams can quantify their impact, optimize talent strategies, and clearly demonstrate HR’s value to the C-suite.
Prompt Engineering
Prompt engineering is an emerging field focused on crafting precise instructions (prompts) for AI models to generate optimized, relevant outputs.
With many HR platforms already integrating AI-driven agents, it’s becoming clear that HR teams need a dedicated expert to fine-tune AI models for better decision-making. Proper prompt engineering ensures that AI delivers meaningful insights, helping HR teams make data-driven hiring, engagement, and workforce planning decisions.
Chris Rainey, host of the HR Leaders podcast, shared a conversation with Kristy Sundjaja, Chief People Officer at Taboola, where he mentioned a large organization that has already hired a dedicated prompt engineer for their HR team. This specialist fine-tunes various AI models to ensure accurate and actionable results.
If your HR team works with multiple AI tools across different platforms, hiring a prompt engineer could be a strategic move, ensuring that AI delivers the most relevant, data-driven insights for your business.
Forecast Hiring Needs
Instead of scrambling to hire when demand spikes, AI allows HR teams to predict staffing needs in advance.
By analyzing historical hiring trends, sales data, and support tickets, AI helps organizations anticipate workforce demand and plan accordingly.
Adam Young, CEO and Founder of Event Tickets Center, shared how AI helped his company prepare for a major event:
“For Beyoncé’s tour, AI predicted a 40% increase in customer inquiries, so we staffed up in advance—avoiding slow response times and costly last-minute hires.”
By using AI for workforce forecasting, you can reduce hiring bottlenecks, improve customer service, and optimize labor costs.
Employee Onboarding
While employee onboarding should be a human-driven experience, AI can enhance the process by automating administrative tasks and guiding new hires.
For example, AI-powered chatbots can walk employees through onboarding checklists, ensuring they complete key steps like paperwork submission, benefits enrollment, and IT setup. This allows HR professionals to focus on more meaningful, human-centric experiences such as mentorship programs or buddy systems.
By blending AI automation with personalized onboarding experiences, your organization can streamline the process while making new employees feel supported and engaged from day one.
Improving Payroll Accuracy
Payroll errors frustrate employees and can damage trust in an organization. Whether it’s miscalculated overtime or incorrect deductions, inaccuracies can lead to disputes and compliance risks. That’s why many companies are turning to AI to improve payroll accuracy.
Michael Nemeroff, CEO of Rush Order Tees, shared how AI transformed his company’s payroll process:
“We had issues with miscalculated overtime and missed break penalties, which led to employee frustration. AI now tracks work hours in real time, making payroll 100% accurate and flagging any potential compliance risks before they happen. Employees trust the system more, and payroll disputes have dropped significantly.”
By using AI-driven payroll systems, organizations can ensure accuracy, maintain compliance, and improve employee satisfaction.
Personalized Learning & Development
Continuous learning is a top priority for employees. In fact, 9 out of 10 workers say that learning opportunities are essential to their workplace experience. To create scalable, effective learning programs, HR leaders are turning to AI.
Albert Galarza, Global Vice President of Human Resources at TELUS International, highlights five key AI-driven learning use cases:
- Personalized training content: AI analyzes employees’ learning styles and preferences to create customized training materials.
- Simulated learning environments: AI generates immersive simulations to help employees practice complex tasks and gain confidence.
- Adaptive learning paths: AI adjusts training programs in real time, tailoring content based on an employee’s progress, strengths, and areas for improvement.
- Automated assessment & feedback: AI grades assessments instantly and provides real-time, personalized feedback to help employees improve.
- Predictive analytics for skills gaps: AI identifies skill shortages within an organization, allowing HR teams to design targeted learning programs.
Automated Performance Reviews
Traditional performance reviews often suffer from recency bias, inconsistent feedback, and a lack of real-time insights. AI is changing this by making performance management more data-driven and objective.
According to Albert Galarza, AI can enhance performance management in several ways:
- Objective, data-driven analysis: AI compiles 360-degree performance insights, reducing human bias.
- Consolidated information for evaluation: AI aggregates data from multiple sources, offering
Employee Benefits strategy
Organizations are increasingly using AI to optimize their benefits strategy. According to Mercer, 40% of companies now use AI for benefits administration.
One common use case is analyzing compensation and benefits data to ensure fairness and maintain competitive rewards policies. AI can also play a crucial role in mergers and acquisitions, where it helps HR teams process large volumes of HR materials quickly to align benefits programs.
By leveraging AI, organizations can streamline benefits management, ensure equitable compensation, and make data-driven decisions that enhance employee satisfaction.
Handling Candidate Enquiries
For companies that receive thousands of applications per job posting, handling candidate inquiries can become overwhelming. AI-powered chatbots solve this challenge by engaging with candidates, answering FAQs, and guiding them through the hiring process, all without human intervention.
A prime example is L’Oréal, which uses AI chatbots like Mya and Seedlink to communicate with applicants, provide real-time updates, and improve the candidate experience.
Employee Engagement Analysis
No organization wants to lose its top talent unexpectedly. That’s why employee engagement and retention remain top priorities for HR leaders.
AI helps detect early warning signs of disengagement and turnover risks by analyzing behavioral data such as:
- Absenteeism trends
- Changes in engagement levels
- Shifts in performance review ratings
IBM, for example, uses AI to predict employee turnover with 95% accuracy, allowing HR teams to proactively address retention risks before employees leave.
Best Practices for Implementing AI in Human Resources
If you’re ready to introduce AI into your HR workflows, the key to success isn’t just selecting an AI tool, model, or platform. It is implementing it strategically and thoughtfully. AI can enhance efficiency, improve decision-making, and free up HR teams, but without a clear plan, your adoption can fail.
Before moving forward, ask yourself: How will AI support your HR strategy? How are other departments already maximizing their skills with AI, and where can HR apply similar efficiencies?
Here are some best practices to ensure a successful AI implementation in HR.
Adopt an Agile Implementation Approach
You can’t roll out AI in HR the same way you deploy an ERP system. It’s not a one-size-fits-all solution. AI is constantly evolving, and HR teams are still discovering its full capabilities and limitations.
The best approach? Start small, test, learn, and refine.
- Form an internal AI task force before purchasing any solution. Identify the specific problem you want to solve and ensure there’s a clear use case before making a financial commitment.
- Avoid “shiny object syndrome”. Don’t invest in AI tools simply because they’re trending. If the problem you’re addressing isn’t substantial, adding another vendor to your tech stack may not be necessary.
- Be flexible. AI adoption should be an iterative process, continuously improving based on real-world application and feedback.
Keep Humans in the Loop
AI can identify patterns and flag biases, but it won’t tell you when bias is actively influencing decisions. That’s why human oversight is crucial in AI-driven HR processes.
HR professionals must continually ask:
- Is this data accurate?
- Are we adhering to privacy laws?
- How is the AI system making decisions?
- Where is the data coming from?
AI should enhance human decision-making, not replace it. Ensuring that ethical considerations and compliance safeguards are in place will prevent unintended consequences that could negatively impact employees.
Foster an AI-Ready Workplace Culture
To ensure that AI adoption is embraced rather than resisted, be transparent about:
- What AI will (and won’t) do
- How it affects employees’ roles
- The safeguards in place to prevent bias and errors
Governance is also critical. As one HR leader put it:
“You want to focus on a robust governance and compliance framework while ensuring human oversight is in place. Establishing clear ethical guidelines, regular audits, and compliance checks will help build trust. Active human intervention reinforces fairness, mitigates bias, and ensures AI decisions align with organizational values.”
By proactively addressing concerns, expectations, and ethical considerations, HR teams can foster a workplace culture that views AI as a tool for empowerment rather than replacement.
Choose the Right AI Vendor Partner
Selecting the right AI partner is just as important as choosing the right AI tool.
When evaluating vendors, look for:
- Compatibility with your existing HR tech stack: Ensure seamless integration with your current systems.
- Transparency: Vendors should provide clear explanations of how their AI makes decisions.
- Customization options: The ability to tailor AI models to your unique business needs.
- Ongoing support: AI is constantly evolving, so vendors should offer continuous updates.
A strategic vendor partnership ensures your AI solution remains scalable, compliant, and aligned with your long-term HR objectives.
Addressing Your Fears & Concerns With AI in HR
AI adoption in HR comes with both opportunities and uncertainties. Many HR leaders hesitate to integrate AI because they’re unsure of its impact on jobs, data privacy, and the overall employee experience.
But if you think of AI as an inevitable wave of change (and it is), then your role as an HR leader is to embrace it, address concerns proactively, and turn AI into a strategic advantage. Organizations that fail to adapt risk being left behind. The key is to use AI as a tool to enhance HR functions while maintaining human oversight and ethical safeguards.
Let’s explore the biggest concerns HR professionals have and how to mitigate risks while unlocking AI’s full potential.
Workforce Impact
A common misconception is that AI will replace HR professionals entirely. In reality, AI augments human expertise, not eliminates it.
Of course, it would be naive to ignore the fact that some roles will evolve or disappear, just as they have in every technological shift. However, AI is primarily designed to automate repetitive, time-consuming tasks like:
- Data entry & administrative tasks
- Resume screening & candidate shortlisting
- Interview scheduling
- Payroll processing
By offloading these routine tasks, AI frees up HR teams to focus on:
- Employee development & upskilling programs
- Diversity, equity, and inclusion (DEI) initiatives
- Strategic workforce planning
- Creating more personalized, human-centric experiences
There are also certain skills AI cannot replicate—like empathy, emotional intelligence, and critical thinking. If employees are worried about job security, HR leaders should proactively communicate how AI will support their roles and offer upskilling opportunities to help them stay relevant.
The goal isn’t to replace humans with AI, it’s to enhance human capabilities and build a more strategic, efficient HR function.
Data Privacy & Compliance
One of the biggest concerns for HR teams is how AI handles sensitive employee data.
To ensure AI solutions are secure and compliant, organizations must establish clear guardrails around:
- What type of data can be fed into AI models? (Personal, financial, intellectual property data?)
- Where is the data stored and who has access to it?
- How does the AI system process analyze, and retain this information?
Modern AI platforms are built with privacy-by-design principles and comply with major data regulations like General Data Protection Regulation (GDPR), Equal Employment Opportunity Commission (EEOC) guidelines, Local labor laws and corporate compliance policies
However, it’s not enough to assume compliance. HR teams must understand both the capabilities and limitations of AI-driven systems.
Before implementing AI, collaborate with legal, compliance, and IT teams to:
- Assess vendor security protocols
- Establish ethical guidelines for AI usage
- Regularly audit AI-driven decisions to prevent unintended bias or privacy risks
By taking a proactive approach to data governance, HR leaders can mitigate risks, protect employee information, and build trust in AI-driven processes.
Why I Wrote This:
Ongig’s platform supports AI in HR by helping recruiting teams to great better job descriptions fast. To learn more, request a demo of Text Analyzer.
