hero background image

Artificial intelligence in HR:
use cases, trends, platforms & challenges

June 24, 2025

Top use cases of AI in HR

Workforce planning

Staff shortage or overstaffing can negatively impact operational efficiency and disrupt key business workflows. HR teams use data analytics solutions with AI capabilities to prevent such outcomes by identifying potential skill gaps, predicting workforce supply and demand, and thus accurately planning hiring initiatives to meet future talent needs.

Candidate sourcing

Major HR-oriented online platforms, such as LinkedIn, feature ML-based recommendation systems that efficiently segment, rank, and suggest potential candidates for an open position based on their experience and skill set, making recruiting faster and cheaper. Headhunters can also leverage generative AI capabilities to quickly create comprehensive descriptions for their job postings.

Employee onboarding

HR departments can use AI agents and NLP-powered bots at various stages of the onboarding process to improve new employee engagement and recruiting experience. For instance, chatbots can provide new hires with credentials and answer their questions 24/7.

Employee well-being & benefits management

AI-powered solutions help companies monitor employee workload for effective shift scheduling and provide personalized benefits, like health insurance options or retirement plans. Such tools also enable HR specialists to analyze the turnover rate and optimize talent retention and churn prevention strategies accordingly. This results in a more pleasant work environment and superior employee satisfaction.

Career development

Companies can use AI-driven adaptive learning solutions to plan and execute tailored professional paths and training initiatives (including the use of personalized eLearning content, employee handbooks, and other resources) based on each employee’s current capabilities and skill gaps. This helps foster career progression and internal mobility and prioritize talent redeployment over layoffs.

Employee performance management

With the help of HR data analytics software powered by AI, HR teams can monitor workforce KPIs to assign roles and responsibilities based on actual performance, support underperformers with targeted coaching initiatives, and reward the best employees with bonuses. These tools can also help identify key performance drivers, such as specific training programs or incentive schemes.

HR budgeting

Thanks to the AI-based analysis of business outcomes and workforce performance data, organizations can assess the cost-effectiveness of their HR initiatives to prioritize the most beneficial ones. For example, HR managers can evaluate the results of mentoring and upskilling programs to decide whether to hire new specialists or retrain existing employees for new positions. They can also plan future salaries and bonuses to maximize talent retention while staying within budget constraints.

Empower your HR managers with AI

Turn to Itransition

Selected AI technologies applied in HR

HR departments can implement an ensemble of AI-related tools and technologies tailored to their organizations’ specific goals, requirements, and business scenarios.

Predictive analytics solutions rely on statistical and machine learning models to forecast future trends or business outcomes and provide recommendations on the best course of action.

Thanks to their high degree of autonomy and advanced problem-solving capabilities, AI agents can handle multi-step business processes with maximum accuracy and minimal human intervention.

Generative AI

GenAI-powered software uses natural language processing to understand user instructions or 'prompts' and quickly generate text, code, visuals, or other types of original content.

Example of use

Predicting employee churn based on engagement survey results

Example of use

Automating key recruiting tasks, from screening applications to scheduling interviews

Example of use

Creating job descriptions or training materials

Use of AI in HR

Scheme title: Most popular AI use cases in human resources
Data source: SHRM
*Question was select all that apply. Among those who indicated their organization uses Al to support HR-related activities

Most companies relying on AI for recruiting use it to generate job descriptions (65%), while organizations implementing this technology for learning and development apply it primarily to provide employees with personalized training opportunities (49%). When it comes to performance management, the most common AI use case is providing employees with more comprehensive performance feedback (57%).

SHRM

According to HR leaders surveyed, the highest priority GenAI use case is document generation (53%), followed by job description generation for recruiting (52%) and employee-facing chatbots (51%).

Gartner

Real-life examples of AI adoption in HR

-12,000

hours of data gathering and entry in one quarter

IBM adopted an AI-powered automation system called HiRo to help its HR staff perform a variety of time-consuming tasks. For instance, it can collect and analyze data to compile lists of employees eligible for promotion.

-50%

in response times to HR queries

A multinational bank partnered with Deloitte to complement its service desk agents with an AI-powered smart assistant. The chatbot can handle common HR help desk queries and even improve its capabilities by observing human interactions between employees.

-85%

time spent to process sick leave submissions

Covestro, one of the world's leading suppliers of polymers, opted for an AI-enhanced RPA solution by UiPath to automate its HR processes. The solution uses OCR and ML to extract data from sick leave documents and enter it into corporate systems.

Popular AI-powered tools & platforms for HR

Talenteer is an AI-based internal talent marketplace developed by Itransition to improve the transparency of open positions and facilitate employee redeployment while minimizing staff turnover and external over-hiring. The solution acts as a single point of truth, centralizing employee data (roles, expertise, etc.) and helping HR managers track in-house experts across the internal talent pool based on a set of given parameters.

Recruiter is a hiring platform by LinkedIn featuring a talent search and recommendation system powered by ML algorithms. This HR solution can compile lists of candidates matching a search request or job posting and rank them based on their expertise, current location, and other factors. It also considers the mutual interest between candidates and recruiters (for instance, if the former positively reply to HR managers' InMail messages).

1 Position, location 2 Candidates for position & location 3 Translate into Queries for Ranking 6 Candidate Arm 1 Cand 1
Cand 2
Cand 3 Cand 1
Cand 2
Cand 3 Arm 2 Cand 1
Cand 2
Cand 3 Arm 3 4 Choose next arm (intent cluster) 5 Recommend next candidate from next arm 7 Response 8 Update arm parameters utilized for selection of next arm 9 Re-rank candidates for each arm by updating query weights

Scheme title: LinkedIn Recruiter’s operation
Data source: LinkedIn

Eightfold AI is a deep learning-powered talent intelligence platform covering recruitment processes, upskilling, employee retention, and workforce diversity. This tool automates resume screening and minimizes bias via profile data masking. It can also aggregate employee data and leverage AI to match staff members with the most suitable internal jobs, projects, career paths, and development opportunities based on their performance.

HireVue is a talent experience platform focusing on recruitment at scale through AI-based video interviewing. The system provides candidates with a list of questions to be answered autonomously via video. Then, it transcribes the answers and issues a score based on the use of keywords, tone of voice, and other parameters, combined with a game-based test and a technical skills assessment to rank the applicants.

HireVue

Image title: HireVue’s interface
Image source: hirevue.com — Professional hiring software

Phenom AI is a comprehensive tool leveraging ML to enhance talent acquisition, employee development, and HR administration. The platform can automate routine tasks, such as candidate screening and scheduling, and provide job seekers with recommendations tailored to their interests and browsing history. It also relies on data analytics to help hiring managers identify suitable candidates based on an AI-generated fit score.

Benefits of AI in human resource management

Enhanced HR efficiency

achieved through the automation of time-consuming tasks, such as content creation and benefits management using generative AI, chatbots, and AI agents.

Improved employee performance

thanks to targeted upskilling programs and motivational incentives and rewards based on KPIs.

Business risk mitigation

through AI-enabled predictions and proactive recruiting and retention programs to prevent churn, understaffing, and other disrupting outcomes.

HR cost reduction

secured by minimizing administrative overhead through automation and avoiding additional recruiting expenses due to lowered employee turnover.

Better employee experience

thanks to seamless onboarding via chatbots and data-driven, bias-free decisions on benefits and career progression.

Roadblocks & guidelines for adopting AI in HR

Organizations willing to enhance their HR processes with AI should address various implementation considerations. Keep in mind these recommended best practices.

Challenges

Recommendations

Data availability
Given the highly data-driven nature of AI, any HR solution leveraging this technology for analytical or operational purposes should be fueled with historical data and ongoing streams of real-time information.
  • Enable communication between your HR software and ERP, LMS, or third-party tools and platforms by setting up suitable APIs. Several cloud-based services can facilitate this process, including Azure API Management or Amazon API Gateway.
  • If the tools to integrate rely on different communication protocols, you may need to build a middleware architecture, such as an enterprise service bus (ESB), to convert them. You can also opt for data virtualization techniques.
  • Configure an ETL pipeline to integrate heterogeneous data from multiple sources and consolidate it into a unified data storage, such as a NoSQL database, a time-series database, or a data lake. Cloud data integration tools like AWS Glue and Azure Data Factory can streamline this process.
AI model reliability
While artificial intelligence can certainly foster data-driven decision-making, AI models aren’t 100% accurate and can still suffer from bias. For instance, some recruiting engines have been shown to disadvantage female candidates in the past.
  • Train AI algorithms on reliable, high-volume datasets from selected sources, including properly integrated corporate systems.
  • Consider using built-in algorithms and pre-trained AI models provided by cloud platforms and services, such as Amazon SageMaker or Azure Machine Learning. These companies have access to a large pool of experts, huge volumes of training data, and enormous computing power to build, test, and optimize algorithms and models for maximum performance.
  • Divide the data used in the modeling phase into training, validation, and test sets to address overfitting (when the model was overtrained on specific data and performed poorly with other sets).
  • After deployment, perform multiple retraining iterations according to MLOps' best practices to fine-tune the model with new data and mitigate model drift (progressive changes in input data and related variables that reduce model performance).
Security & compliance
AI-based HR software solutions typically handle a fair amount of sensitive data, including employees' personal information and financial reports. This makes them ideal targets for hacking, breaches, or leaks. Integrations with other systems multiply the potential points of vulnerability, aggravating cybersecurity and compliance issues.
  • Use dynamic data masking in all cases where it’s possible.
  • Deploy HR software designed in strict compliance with applicable data management standards and regulations, such as GDPR, FISMA, and HIPAA.
  • Protect your software and corporate data assets with a range of cybersecurity features encompassing, for instance, encrypted data exchange via cryptographic protocols, identity and access management based on a zero-trust approach, multi-factor authentication, and user activity monitoring.
  • Adopt company policies for data governance establishing how data should be managed and shared across your organization.
AI consulting

AI consulting

Rely on our expert consultants to plan and supervise your AI project, overcome technical roadblocks, and maximize the adoption payoffs of your new AI solution.

AI development

Team up with our developers to build AI solutions tailored to your needs or modernize existing software in line with new tech trends and business requirements.

AI for a more human approach to HR

AI for a more human approach to HR

Often regarded as a depersonalizing force, artificial intelligence in HR has proven capable of amplifying the most exquisitely human facets of our jobs and workplaces. AI-powered solutions can help organizations ensure a fair career progression, improve employee engagement, create positive working environments, and ease HR managers' administrative burden.

At the same time, the architectural complexity, data voracity, and “black box” nature of these systems call for prudent and reasoned implementation. Consider relying on Itransition to maximize the benefits of AI for HR and overcome the challenges of its adoption.

Support your workforce with Itransition’s AI solutions

Let’s talk

FAQs

AI adoption across key HR functions is likely to expand in the future, as predicted by multiple case studies, such as HR’s Future State Report by Eightfold AI. Popular use cases will include upskilling and reskilling, workforce equity and inclusion, turnover and retention, talent acquisition, talent redeployment, and diversity in hiring. Furthermore, McKinsey highlighted the growing role of generative AI in writing job descriptions and requirements, powering chatbots, and preparing performance reviews.

McKinsey pointed out that while AI tools may not completely replace HR managers, they are likely to reshape their job. If supported with proper retraining initiatives, HR professionals will progressively shift from administrative duties to employee-facing roles and supervision tasks (the so-called "human-in-the-loop" model).

Contact us

Sales and general inquires

info@itransition.com

Want to join Itransition?

Explore careers

Contact us

Please be informed that when you click the Send button Itransition Group will process your personal data in accordance with our Privacy notice for the purpose of providing you with appropriate information.

The total size of attachments should not exceed 10 MB.

Allowed types:

jpg

jpeg

png

gif

doc

docx

ppt

pptx

pdf

txt

rtf

odt

ods

odg

odp

xls

xlsx

xlxs

vcf

vcard

key

rar

zip

7z

gz

gzip

tar