Using AI in HR: Workflows, Key Tools, Benefits, and Considerations

Key takeaways

Artificial intelligence (AI) is reshaping many human resource (HR) workflows.

• AI has many practical uses for HR, including during recruitment, onboarding, and employee development.

• The benefits of using AI in HR workflows include greater efficiency, improved candidate experiences, and stronger data-driven decision making.

• There are many different AI tools to consider when looking to address a specific HR need.

Explore how you can use AI to your advantage in different areas of HR. Afterward, learn how to apply AI to streamline activities in various functions of human resources with IBM's Generative AI for Human Resources (HR) Professionals Specialization.

How is AI being used in HR?

HR teams are using AI to address all phases of their work: recruiting, onboarding, professional development, and more. Let's review some of the HR areas that AI can be useful in:

1. Recruitment and onboarding

AI tools can help enhance the hiring process by analyzing job applications, scheduling candidate interviews, and profiling potential candidates to indicate who may be a good fit. For example, during recruitment, you might use AI to:

• Generate interview questions and job descriptions

• Identify candidates with relevant skill sets

• Rank potential hires based on their experiences

• Communicate with potential candidates via chatbot

• Screen potential candidates and invite them to apply

Once you’ve recruited and hired new employees, you can continue to use AI during the onboarding process. You can:

• Generate personalized new hire training materials and documents

• Automate the delivery of required information

• Provide continual onboarding support via chatbots

2. Performance management and review

Annual performance reviews can involve a cumbersome amount of information to pull together. AI uses data to provide objective insights into employee performance, which can in turn lead to a more fair evaluation process with personalized feedback.

AI systems collect data throughout the year, providing a more complete assessment, rather than relying on periodic assessments or actions directly prior to review. Not only does this real-time feedback system help employees stay on track and improve engagement, but it also bypasses human error, such as recency bias.

3. Talent management and employee development

According to McKinsey talent trends research, providing opportunities for employees to continually learn and develop is a key driver of business success [1]. To keep up with the demand for employee growth opportunities, many successful companies employ adaptive learning, which involves learning programs that match the needs and interests of individual employees.

AI enables the precise assessment of employees' skills, personalizes their growth opportunities with tailored learning paths and assignments, and identifies opportunities for employees to reskill or upskill within their current roles. It also identifies pathways for employees to move within the company, helping to retain talent as employees evolve and seek new responsibilities.

4. Payroll processing and financial tracking

AI enables the automation of payroll processing, thereby reducing the workload of HR professionals. These automated systems can reduce pay errors, consider regulations and compliance concerns, and provide transparent documentation of employee pay records and changes over time.

In addition, AI technologies can track organizational spending and budgeting, identifying areas of overspending or strain on the company. This helps leaders make informed decisions about where to invest resources, what initiatives are succeeding, and what areas could use improvement.

Using different types of AI in HR: Examples

As AI progresses, you may want to use different types of AI to address specific HR needs. For example:

• You might use generative AI to generate job descriptions and performance reviews.

• You might use deep learning algorithms to provide recommendations for employee and organizational success.

• You might use automation to detect fraud or process payroll.

17 AI tools you can use for human resources

We've compiled some of the top AI tools for use across HR.

Recruitment and talent acquisition

AI-powered recruiting tools help HR teams source, screen, and hire candidates more efficiently while reducing bias and improving candidate experience. These platforms can handle everything from initial outreach to interview scheduling and assessment, dramatically reducing time-to-hire.

HireVue

• What it does: Video interviewing platform with AI-powered candidate assessment and interview analysis

• Best for: Large enterprises handling high-volume hiring who want to streamline early-stage interviews

Eightfold AI

• What it does: Uses deep learning to match candidates with opportunities and predict career trajectories

• Best for: Companies focused on internal mobility and building diverse talent pipelines

Pymetrics

• What it does: Gamified assessments that measure cognitive and emotional traits to match candidates to roles

• Best for: Organizations prioritizing bias reduction and finding non-traditional candidates

Olivia by Paradox

• What it does: Conversational AI assistant that handles candidate screening, scheduling, and communication

• Best for: High-volume recruiters in retail, hospitality, or healthcare needing to automate repetitive tasks

Phenom

• What it does: Personalized career site experience with AI-driven job matching and CRM capabilities

• Best for: Mid to large companies wanting to improve candidate experience and recruiter efficiency

Learning and development

Certain AI tools can help organizations build a culture of continuous learning and ensure employees develop the skills needed for future roles. The AI tools below personalize employee learning experiences by recommending relevant content, identifying skill gaps, and creating adaptive learning paths.

Degreed

• What it does: Skills management platform that curates learning content and tracks skill development

• Best for: Organizations undergoing digital transformation or focusing on continuous upskilling

EdCast

• What it does: AI-powered knowledge cloud that delivers personalized learning pathways

• Best for: Enterprises seeking to democratize knowledge sharing across global teams

Cornerstone OnDemand

• What it does: Comprehensive LMS with AI recommendations for personalized training content

• Best for: Large organizations needing an all-in-one learning and talent management solution

Performance and engagement

AI enhances performance management by analyzing feedback patterns, predicting turnover risk, and providing managers with data-driven coaching recommendations. These platforms move beyond annual reviews to enable continuous feedback and real-time engagement monitoring.

Lattice

• What it does: Performance management platform with goals, feedback, and engagement survey tools

• Best for: Growing tech companies and startups wanting modern, continuous performance processes

Culture Amp

• What it does: Employee engagement and feedback platform with AI-powered insights and benchmarking

• Best for: Companies serious about measuring and improving employee experience and culture

15Five

• What it does: Continuous performance management with check-ins, OKRs, and manager effectiveness tools

• Best for: Small to mid-sized businesses adopting a coaching-based management approach

Workforce planning and analytics

Workforce analytics tools use AI to transform raw HR data into strategic insights about headcount planning, compensation equity, retention risks, and organizational effectiveness. These platforms enable HR managers to make evidence-based decisions and demonstrate business impact.

Workday

• What it does: Enterprise cloud platform for HR, finance, and planning with embedded AI/ML capabilities

• Best for: Large enterprises needing integrated financial and workforce management

SAP SuccessFactors

• What it does: Comprehensive HCM suite covering core HR, talent, and analytics with AI features

• Best for: Global enterprises, especially those already in the SAP ecosystem

Visier

• What it does: People analytics platform that transforms HR data into actionable workforce insights

• Best for: HR leaders seeking sophisticated analytics without needing data science expertise

Orgnostic

• What it does: HR analytics and reporting tool that connects multiple data sources for insights

• Best for: Small to mid-sized companies wanting affordable people analytics

Operations and employee support

AI-powered HR service delivery tools act as virtual assistants, answering common employee questions, automating routine processes, and routing complex issues to the right people. They free up HR teams from administrative tasks while providing employees with constant support.

Leena AI

• What it does: Virtual HR assistant that answers employee questions and automates HR tickets

• Best for: Companies looking to reduce HR workload and provide 24/7 employee support

ServiceNow HR Service Delivery

• What it does: Workflow automation platform that streamlines HR case management and employee requests

• Best for: Large enterprises wanting to create consumer-grade employee service experiences

Benefits of using AI in HR

There are many reasons to consider integrating AI tools into your HR workflows.

1. Save time

By incorporating AI into your HR processes, you can reduce the time spent on more repetitive or administrative tasks. AI can free HR coordinators and HR analysts, among other HR professionals, to focus on strategic initiatives.

2. Data-driven decision making

AI can analyze a significant amount of HR data from multiple sources, such as performance reviews, engagement surveys, compensation data, and turnover patterns, to surface insights that would take much longer to identify manually. This enables evidence-based decisions about numerous operational areas.

3. Improved employee experience

AI-powered chatbots provide instant responses to employee questions throughout the day and across time zones. AI can also create tailored learning pathways based on individual career goals, skill gaps, and learning preferences, making professional development more relevant and engaging.

4. Proactive problem identification

By continually analyzing employee-specific data, AI can identify patterns that predict turnover risk, burnout, skill gaps, or engagement issues before they become critical problems. This allows HR teams to intervene early, rather than reacting after valuable employees have already left.

5. Reduced unconscious bias

When properly designed and monitored, AI can help reduce human biases in hiring and promotion decisions by focusing on objective criteria like skills, experience, and performance data.

6. Scalability

AI tools enable HR teams to handle significantly larger workloads without increasing headcount and therefore budget. A small HR team can support thousands of employees with AI-powered service delivery or a high-volume recruiter can manage numerous candidates simultaneously with automated scheduling.

7. Enhanced employee development

AI-powered learning platforms can deliver personalized skill development tailored to employees' goals and current gaps. This creates a more agile workforce capable of pivoting where needed, while also increasing employee engagement .

Considerations of using AI in HR

At the same time, there are considerations to keep in mind as you explore the possibility of using AI.

1. Data privacy risks

The data that AI systems require can be sensitive in nature, which can in turn create privacy concerns and security risks. Data breaches could expose confidential information, and employees may feel uncomfortable with the level of surveillance and data collection required for AI systems to function effectively.

2. Discrimination

Despite aiming for objectivity, AI algorithms can perpetuate and even amplify existing biases present in historical training data. If past hiring decisions favored certain demographics, AI may replicate those patterns. What's more: Bias can be subtle and difficult to detect, requiring constant auditing and human oversight.

3. Lack of emotional intelligence

AI excels at pattern recognition and data processing but lacks the emotional intelligence so critical to HR success. For instance, it can't read between the lines in an interview, understand unique personal circumstances affecting performance, or provide genuine emotional support during difficult situations.

4. Over-reliance on technology

There's a risk that organizations become too dependent on AI recommendations without questioning underlying assumptions or data quality. AI systems can produce confident-sounding insights based on flawed data or inappropriate algorithms. HR professionals need to maintain critical thinking skills and domain expertise.

5. Data quality dependence

AI is only as good as the data it's trained on. Incomplete, outdated, or inaccurate HR data will produce unreliable insights and recommendations. Many organizations struggle with fragmented data across multiple systems, inconsistent data entry practices, and historical data that doesn't reflect current realities.

Will HR get replaced by AI?

AI is unlikely to replace HR. Instead, AI allows HR professionals to streamline operations and focus their energy on areas that benefit more from human insight and creativity. For example, while AI can automate payroll processes or provide spending recommendations, it lacks a human perspective. This hinders it from making nuanced decisions, such as how to build an effective team or resolve conflict between two employees—areas that are important when it comes to HR.

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