Introduction
Companies embracing AI achieve better decision-making, higher productivity, and increased profits. These benefits extend to the Human Resources (HR) function – provided you know how to fully leverage its potential.
As AI capabilities continuously expand and grow, there are several key benefits to using AI in HR. AI can facilitate data-driven decisions, reduce headcount and recruitment costs, and enhance the employee experience. Despite 80% of decision-makers believing that AI adoption is essential for maintaining company competitiveness, and 77% thinking that risk reduction could increase its adoption rate, challenges remain.
This article discusses AI’s role, impact, risks, and benefits in HR, offering best practices for applying AI across various aspects of the function.
A Brief History of AI’s Development in HR
AI first appeared in the HR domain in the late 1990s and early 2000s with the emergence of simple automation tools, such as resume screening through Applicant Tracking Systems (ATS) that matched keywords with job descriptions, and more efficient processing of large volumes of applicants.
Subsequently, basic AI chatbots quickly emerged, capable of managing candidate inquiries and scheduling interviews without human intervention. This was followed by the advent of predictive analytics, which utilized historical data to forecast outcomes (e.g., the likelihood of a candidate succeeding in a role). As AI evolved, it shifted from handling simple tasks to supporting strategic decisions like workforce planning.
Today, HR relies more heavily on data and machine learning to automate, improve, and streamline processes, such as predicting employee turnover, identifying high-risk teams, or analyzing survey results. AI is now applied across various HR areas, including recruitment, onboarding and offboarding, workforce planning, chatbots and virtual assistants, Learning & Development (L&D), analytics, talent management, AI coaching, and HR business partnerships. However, it’s crucial to remember that AI should be viewed as a co-pilot, not a replacement, as most HR tasks still require human judgment and empathy.
Five Types of AI Applications in Human Resources
Here are some examples of AI usage in HR, along with relevant HR AI tools that can help integrate AI technology into your organization:
- Content Generation
- AI assists HR teams in creating job descriptions, personalizing candidate emails, and drafting policies.
- It also supports the development of training materials and simulations, allowing you to generate welcome videos for new hires and run employer branding campaigns on social media.
- Examples: DeepSeek, ChatGPT, Jasper AI, Pictory
- Data Insights
- AI makes analyzing performance, compensation, and other data effortless.
- It creates clear dashboards and highlights patterns in large datasets, helping you identify trends like low team performance.
- Additionally, you can use machine learning to predict future HR needs.
- Examples: IBM Watson Analytics, MonkeyLearn
- Information Extraction and Summarization
- You can use AI to scan and summarize large documents, such as legal texts or company policies, helping employees quickly find key information.
- It can also extract insights relevant to business objectives, supporting better HR decisions.
- Examples: SummarizeBot, Tableau, and Einstein Analytics
- Automation and Optimization
- A significant application of AI in HR is automating administrative tasks like interviewing, onboarding, payroll, and performance reviews.
- You can also use it to send e-signature documents, answer employee questions via chatbots, and personalize routine information based on employee data.
- Examples: AI for Google Calendar, Calendly, Grammarly
- Productivity Enhancement
- AI can flag urgent tasks, manage shifting deadlines, sync calendars, assign tasks, and send reminders.
- It can also schedule meetings, take notes, summarize discussions, draft documents, assist with research, and recommend tasks based on past performance.
- Examples: Asana, Clockwise, Otter.ai, Perplexity
Nine Key Areas of AI Application in HR
Let’s explore the benefits of AI in HR through practical application cases of AI tools and the companies using them:
- AI Helps Save Time on Repetitive Tasks
- AI enables HR teams to outsource low-value, time-consuming administrative tasks such as resume screening, meeting scheduling, payroll processing, and compliance assurance.
- This enhances efficiency, frees up time for more strategic, value-added work, reduces the risk of human error, and improves overall accuracy.
- Practical Case:
- Ambassador Cruise Line uses Sage HR to automate its reporting, leave booking, and shift scheduling, allowing the HR team to focus on more valuable work.
- Mastercard partnered with Phenom to use AI for interview scheduling, increasing scheduling speed by 85%, with 88% of interviews scheduled within 24 hours of the request.
- AI Improves Recruitment Quality
- AI can enhance candidate matching, thereby improving recruitment quality.
- For instance, you can use ChatGPT to generate interview questions based on roles, and summarize resumes to expedite the screening process.
- You can also use AI tools like skill tests and pre-employment assessments to gain deeper insights into candidate abilities.
- Practical Case:
- Advanced tools like HireVue use AI in video interviews to assess facial expressions, body language, and tone, helping determine a candidate’s fit for the position.
- L’Oréal’s Mya AI chatbot interacts with candidates before they apply to see if they are a good fit and guides them through the process. This pre-screening saves recruiters time and helps improve the quality of applicants.
- AI Enhances Employee Experience
- AI-powered chatbots can answer employee queries and act as virtual assistants for new hires during onboarding.
- Meanwhile, AI generative technology (GenAI) in HR can analyze skills, performance data, and career goals to provide tailored learning and development recommendations.
- Additionally, AI-based coaching tools can simulate in-person coaching and offer real-time feedback.
- Practical Case:
- Leena is a virtual HR assistant that supports employees by automatically resolving common questions and streamlining workflows. This allows employees to get support faster and frees up the HR department for tasks requiring human interaction.
- Unilever uses AI-integrated platforms like Degreed to personalize learning paths based on employees’ roles, interests, and skill gaps.
- AI Boosts Employee Engagement
- AI tools can help draft clear, engaging company communications regarding new initiatives, policy updates, and reward programs, while Generative AI (GenAI) can customize employee communications to make your messages more inclusive and effective.
- These tools can also help you brainstorm ways to improve employee experience (e.g., by increasing participation).
- Practical Case:
- Jasper enhances employee engagement by writing personalized messages, newsletters, and learning materials, ensuring consistent and motivating communication.
- Canva’s Magic Write generates clear, engaging text for HR visual content (such as posters, slides, and event materials), making it easy to create professional and compelling content that captures employee attention and promotes engagement.
- AI Provides Data-Driven Decisions
- AI allows you to make evidence-based decisions by measuring key performance indicators like task completion rates and colleague feedback.
- This enables you to plan for the future by personalizing career development plans, identifying future leaders, and retraining and upskilling employees across the organization.
- Practical Case:
- RingCentral partnered with Findem to combine external and internal data to streamline the recruitment process, including candidate matching. Ultimately, its talent pool increased by 40%, and hiring quality improved by 22%.
- Platforms like Gloat and Eightfold AI can recommend internal job opportunities, training programs, and mentor pairings based on each employee’s current skills, experience, and career goals.
- AI’s Ability to Predict Workforce Trends
- 58% of HR leaders struggle to meet talent demands, and 40% of companies cannot fill critical positions.
- AI-driven predictions can forecast workforce trends and proactively adjust strategies.
- Additionally, you can use Generative AI (GenAI) to analyze large datasets from various sources to gain key insights (e.g., potential turnover risks and future skill gaps).
- Practical Case:
- Aura synchronizes workforce data and integrates external workforce trends, competitor hiring patterns, and economic factors into a single source of truth, facilitating the tracking of workforce trends and optimization of strategies.
- ChatGPT can be used to summarize trends from employee surveys, performance reviews, and exit interviews, identify common causes of employee turnover, and suggest improvements.
- AI Increases HR Productivity
- As AI takes on manual, repetitive administrative tasks, you can focus on more strategic tasks and increase HR productivity in key areas.
- For example, you can use AI tools to evaluate applicant responses and quickly draft job descriptions, offer letters, and policy updates, making the recruitment process more efficient.
- Practical Case:
- By using machine learning tools to analyze applicant interview responses and videos, Unilever streamlined its recruitment process, reducing hiring time by 75%.
- Grammarly helps HR teams work faster by improving the clarity, tone, and correctness of emails, policies, and internal documents. This reduces back-and-forth revisions and ensures professional, error-free communication.
- Copy.ai accelerates HR content creation by generating ready-to-use drafts for job postings, employee updates, onboarding guides, and more. This saves writing time and helps HR teams focus on higher-value tasks.
- AI Strengthens Diversity, Inclusion, Equity, and Employee Development (DEIB)
- AI in HR supports DEIB by analyzing data to identify biases in recruitment, promotion, and compensation, helping HR teams take action to address these gaps.
- Simultaneously, AI tools like chatbots promote inclusivity by providing real-time support for employees with disabilities, ensuring they have equal access to relevant information and assistance.
- Practical Case:
- Diversio uses Generative AI (GenAI) to process open-ended text feedback from employee surveys to detect subtle language implying exclusion or bias. It then correlates these patterns with outcomes such as lower engagement or slower promotion rates for certain groups.
- Textio scans text in real-time to flag non-inclusive language and suggest neutral alternatives. For instance, it highlights phrases that might deter minority groups from applying and provides alternatives to attract a broader, more diverse audience.
- AI Improves Policy and Regulatory Compliance
- Tools like predictive compliance analytics use AI to analyze historical data and compliance trends, while automated software streamlines compliance tasks.
- GenAI can also help you draft, create, and update policy documents and contractual compliance regulations based on company policies.
- Practical Case:
- Compliance.ai monitors compliance updates in real-time, generates accurate and updated policy drafts, and alerts HR departments to legal changes that may affect employee handbooks or contracts. This reduces the risk of manual research and non-compliance.
- ADP uses AI-driven compliance tools to keep HR teams informed of labor law changes, automate policy and document updates, and minimize legal risks. This helps businesses remain compliant, reduce manual work, and stay audit-ready.
Understanding AI Risks for Better Application
While there are many benefits to using AI in HR, there are also risks and challenges to be aware of:
- Algorithmic Bias: Biased algorithms can produce inaccurate insights, potentially leading to discrimination and inequality within the organization.
- Data Privacy and Ethical Concerns: AI systems might collect data without users’ knowledge, which is a privacy violation and raises ethical questions about consent.
- Limited Transparency of AI Decisions: Insufficient transparency around how AI models arrive at their results can erode trust in the information provided.
- Over-reliance on Automated Suggestions: Excessive reliance on AI is a growing concern, as it can lead to reduced human oversight and decision-making errors.
- Integration Complexity: Organizations with legacy systems not designed for AI integration can easily encounter problems with AI adoption and scalability.
- Lack of Internal AI Expertise: 81% of IT professionals believe they can use AI, but only 12% possess the necessary skills, indicating a 69% skill gap in this area.
- Resistance to Change: HR teams and employees may be reluctant to adopt AI, either due to a lack of interest or capability, or concerns that it will replace their jobs.
- High Upfront Costs or Unclear ROI: AI in HR requires significant upfront investment, and it can be difficult to justify these costs.
- Regulatory Uncertainty: Increasingly stringent regulations on AI technology might deter some organizations from developing formal AI roadmaps.
Eight Strategies for Applying AI in HR
Here are some best practices for applying AI in HR:
- Start with Small HR Needs
- Begin by testing AI in a specific HR area, such as recruitment or onboarding, before rolling it out across the entire company. Try several different tools to see what works and evaluate their impact.
- Starting small allows you to understand which tools fit your processes, address issues promptly, and gain internal support before expanding to other areas like learning, performance, or workforce planning.
- Choose Tools Integrated with Existing HR Software
- Select AI tools compatible with your existing systems (e.g., ATS, HRIS, or LMS). This not only avoids redundant work but also promotes smooth processes.
- Furthermore, integration reduces the time spent on manual data transfers and yields more reliable data insights from connected systems.
- Focus on Solving Pain Points
- Your company should adopt AI because it addresses genuine business needs, not just to follow trends.
- Whether it’s shortening hiring time, improving employee retention, or automating administrative tasks, start with clear objectives.
- This will help you select the right tools, justify their value, and gain buy-in from relevant stakeholders.
- Collaborate with IT and Data Teams to Ensure Smooth Implementation
- Involving your organization’s IT and data teams early on helps you set up AI tools correctly and securely.
- These teams can help ensure system compatibility, data integration, and compliance with regulatory requirements.
- If you lack internal expertise, consider hiring a reputable external partner to guide the process.
- Prioritize Transparency
- Ensure employees understand how AI will be used, what data will be collected, and how decisions will be made. This helps build trust and prevent resistance.
- Clear communication is especially important in areas where AI suggestions directly impact employees, such as performance evaluations or internal transfers.
- Maintain a “Human-in-the-Loop” Approach
- AI should assist the HR department, not replace it. When reviewing AI-driven outputs, especially those involving employee decisions, ensure relevant personnel are involved.
- Thorough human review is crucial for detecting errors, preventing bias, and ensuring the fairness and accuracy of final decisions.
- Regularly Audit AI Tools for Bias and Performance Issues
- Monitor tool performance and check results for any biases. Regular audits help you detect problems early, whether it’s a hiring algorithm unfairly screening out specific candidates or inaccurately predicting employee turnover.
- Evaluate the tool’s data, decision-making process, and whether the results are fair and reliable.
- Train HR Staff to Use and Interpret AI Outputs
- Train employees not only on how to operate new software but also on how to interpret data results and act upon them.
- They need to understand what the data reveals, the potential limitations of AI, and when human judgment is needed for decision-making.
- The better trained the team, the greater the value derived from AI investment.
Conclusion
The benefits of integrating AI tools and software in HR are evident. Technology is rapidly evolving, transforming the world of work and business, and failing to adopt AI will lead to falling behind. However, it’s important to be aware of the challenges AI presents and the broad, unregulated potential concerns with previously untested technologies.
If you are ready to apply AI to your organization’s HR function, start small and focus on solving real business problems. Be sure to thoroughly test your chosen AI tools before company-wide implementation, and monitor them regularly so you can minimize bias and make timely changes where needed.
