The AI in Human Resources Market Size is valued at USD 4.3 billion in 2023 and is predicted to reach USD 25.0 billion by the year 2031 at a 24.8% CAGR during the forecast period for 2024-2031.
AI in Human Resources (HR) enhances efficiency by automating key processes like resume screening, candidate matching, and interview scheduling. AI-driven tools analyze job applications to identify top candidates and predict their success, reducing time-to-hire and human bias. In employee management, AI personalizes training, monitors performance, and provides real-time feedback. Workforce analytics powered by AI offers insights into engagement, turnover risks, and productivity trends.
However, the high cost of developing AI in the human resources sector is a significant market constraint. Additionally, market growth is further hindered by a need for more knowledge and familiarity with these technologies. Additionally, a number of factors are creating opportunities in the AI human resources market. These include more efficient recruitment through AI-driven talent matching, better workforce analytics for strategic decision-making, and more personalized employee experiences. Furthermore, AI can facilitate diversity and inclusion programs and assist in managing distant workers.
The AI in the human resources market is segmented based on type, application, deployment mode, and organization size. Based on type, the market is segmented into recruitment and selection, employee onboarding, performance management, talent management, workforce planning and analytics, employee engagement, and learning and development. By application, the market is segmented into resume screening, candidate matching, predictive analytics for employee success, skill gap analysis, personalized learning paths, employee feedback and sentiment analysis, succession planning, compensation, and benefits optimization. As per the deployment mode, the market is further segmented into cloud-based and on-premises. The organization size segment includes small and medium-sized enterprises (SMEs) and large enterprises.
Recruitment and selection is expected to hold a major global market share in 2023 in the AI in human resources market because AI can improve applicant matching, automate resume screening, and simplify interview processes. Widespread acceptance of AI in human resource tools in recruiting is driven by their ability to decrease hiring biases, improve decision-making using data-driven insights, and drastically reduce the time and expense associated with traditional recruitment approaches.
The cloud-based segment is growing because of its affordability, adaptability, and scalability. With simple access to AI technologies, businesses can reap the benefits without investing heavily in costly on-premise equipment. Cloud-based solutions allow human resource systems to be easily integrated, remote work to be supported, and real-time data analytics to be provided. Businesses are moving to them because of the increased security, frequent updates, and accessibility they offer.
North American AI in the human resources market is expected to have the highest market share in revenue in the near future. This can be due to the region’s stringent regulations, focus on moral AI application, growing usage of AI to enhance decision-making and worker efficiency, and greater use of artificial intelligence driving operational efficiencies. In addition, the Asia Pacific is estimated to grow rapidly in the AI in human resources market because of the region’s investment in artificial intelligence solutions, its superior technology infrastructure, and its emphasis on data-driven human resource strategies to improve workforce efficiency and creativity, and improvements to the region’s infrastructure driven by artificial intelligence.
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Report Attribute |
Specifications |
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Market Size Value In 2023 |
USD 4.3 Bn |
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Revenue Forecast In 2031 |
USD 25.0 Bn |
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Growth Rate CAGR |
CAGR of 24.8% from 2024 to 2031 |
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Quantitative Units |
Representation of revenue in US$ Bn and CAGR from 2024 to 2031 |
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Historic Year |
2019 to 2023 |
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Forecast Year |
2024-2031 |
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Report Coverage |
The forecast of revenue, the position of the company, the competitive market structure, growth prospects, and trends |
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Segments Covered |
By Type, Application, Deployment Mode and Organization Size |
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Regional Scope |
North America; Europe; Asia Pacific; Latin America; Middle East & Africa |
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Country Scope |
U.S.; Canada; U.K.; Germany; China; India; Japan; Brazil; Mexico; France; Italy; Spain; South East Asia; South Korea |
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Competitive Landscape |
IBM Corporation, Oracle Corporation, SAP SE, ADP, LLC, Workday, Inc., Ultimate Software Group, Inc., Cornerstone OnDemand, Inc., Kronos Incorporated, Ceridian HCM, Inc., Talentsoft, PeopleStrong HR Services Pvt. Ltd., Phenom People, Inc., Visier, Inc., Entelo, HireVue Inc., Textio, Brazen Technologies, AllyO, Pymetrics, Eightfold AI, ClearCompany, Jobvite, Inc., Greenhouse Software, Inc., Talview, Avature. |
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Customization Scope |
Free customization report with the procurement of the report and modifications to the regional and segment scope. Particular Geographic competitive landscape. |
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Pricing And Available Payment Methods |
Explore pricing alternatives that are customized to your particular study requirements. |
Chapter 1. Methodology and Scope
1.1. Research Methodology
1.2. Research Scope & Assumptions
Chapter 2. Executive Summary
Chapter 3. Global AI in Human Resources Market Snapshot
Chapter 4. Global AI in Human Resources Market Variables, Trends & Scope
4.1. Market Segmentation & Scope
4.2. Drivers
4.3. Challenges
4.4. Trends
4.5. Investment and Funding Analysis
4.6. Industry Analysis – Porter’s Five Forces Analysis
4.7. Competitive Landscape & Market Share Analysis
4.8. Impact of Covid-19 Analysis
Chapter 5. Market Segmentation 1: by Type Estimates & Trend Analysis
5.1. by Type & Market Share, 2019 & 2031
5.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following by Type:
5.2.1. Recruitment and Selection
5.2.2. Employee Onboarding
5.2.3. Performance Management
5.2.4. Talent Management
5.2.5. Workforce Planning and Analytics
5.2.6. Employee Engagement
5.2.7. Learning and Development
Chapter 6. Market Segmentation 2: by Application Estimates & Trend Analysis
6.1. by Application & Market Share, 2019 & 2031
6.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following by Application:
6.2.1. Resume Screening
6.2.2. Candidate Matching
6.2.3. Predictive Analytics for Employee Success
6.2.4. Skill Gap Analysis
6.2.5. Personalized Learning Paths
6.2.6. Employee Feedback and Sentiment Analysis
6.2.7. Succession Planning
6.2.8. Compensation and Benefits Optimization
Chapter 7. Market Segmentation 3: by Deployment Mode Estimates & Trend Analysis
7.1. by Deployment Mode & Market Share, 2019 & 2031
7.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following by Deployment Mode:
7.2.1. Cloud-based
7.2.2. On-premises
Chapter 8. Market Segmentation 4: by Organization Size Estimates & Trend Analysis
8.1. by Organization Size & Market Share, 2019 & 2031
8.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following by Organization Size:
8.2.1. Small and Medium-sized Enterprises (SMEs)
8.2.2. Large Enterprises
Chapter 9. AI in Human Resources Market Segmentation 5: Regional Estimates & Trend Analysis
9.1. North America
9.1.1. North America AI in Human Resources Market Revenue (US$ Million) Estimates and Forecasts by Type, 2024-2031
9.1.2. North America AI in Human Resources Market Revenue (US$ Million) Estimates and Forecasts by Application, 2024-2031
9.1.3. North America AI in Human Resources Market Revenue (US$ Million) Estimates and Forecasts by Deployment Mode, 2024-2031
9.1.4. North America AI in Human Resources Market Revenue (US$ Million) Estimates and Forecasts by Organization Size, 2024-2031
9.1.5. North America AI in Human Resources Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031
9.2. Europe
9.2.1. Europe AI in Human Resources Market Revenue (US$ Million) Estimates and Forecasts by Type, 2024-2031
9.2.2. Europe AI in Human Resources Market Revenue (US$ Million) Estimates and Forecasts by Application, 2024-2031
9.2.3. Europe AI in Human Resources Market Revenue (US$ Million) Estimates and Forecasts by Deployment Mode, 2024-2031
9.2.4. Europe AI in Human Resources Market Revenue (US$ Million) Estimates and Forecasts by Organization Size, 2024-2031
9.2.5. Europe AI in Human Resources Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031
9.3. Asia Pacific
9.3.1. Asia Pacific AI in Human Resources Market Revenue (US$ Million) Estimates and Forecasts by Type, 2024-2031
9.3.2. Asia Pacific AI in Human Resources Market Revenue (US$ Million) Estimates and Forecasts by Application, 2024-2031
9.3.3. Asia-Pacific AI in Human Resources Market Revenue (US$ Million) Estimates and Forecasts by Deployment Mode, 2024-2031
9.3.4. Asia-Pacific AI in Human Resources Market Revenue (US$ Million) Estimates and Forecasts by Organization Size, 2024-2031
9.3.5. Asia Pacific AI in Human Resources Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031
9.4. Latin America
9.4.1. Latin America AI in Human Resources Market Revenue (US$ Million) Estimates and Forecasts by Type, 2024-2031
9.4.2. Latin America AI in Human Resources Market Revenue (US$ Million) Estimates and Forecasts by Application, 2024-2031
9.4.3. Latin America AI in Human Resources Market Revenue (US$ Million) Estimates and Forecasts by Deployment Mode, 2024-2031
9.4.4. Latin America AI in Human Resources Market Revenue (US$ Million) Estimates and Forecasts by Organization Size, 2024-2031
9.4.5. Latin America AI in Human Resources Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031
9.5. Middle East & Africa
9.5.1. Middle East & Africa AI in Human Resources Market Revenue (US$ Million) Estimates and Forecasts by Type, 2024-2031
9.5.2. Middle East & Africa AI in Human Resources Market Revenue (US$ Million) Estimates and Forecasts by Application, 2024-2031
9.5.3. Middle East & Africa AI in Human Resources Market Revenue (US$ Million) Estimates and Forecasts by Deployment Mode, 2024-2031
9.5.4. Middle East & Africa AI in Human Resources Market Revenue (US$ Million) Estimates and Forecasts by Organization Size, 2024-2031
9.5.5. Middle East & Africa AI in Human Resources Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031
Chapter 10. Competitive Landscape
10.1. Major Mergers and Acquisitions/Strategic Alliances
10.2. Company Profiles
10.2.1. IBM Corporation
10.2.2. Oracle Corporation
10.2.3. SAP SE
10.2.4. ADP, LLC
10.2.5. Workday, Inc.
10.2.6. Ultimate Software Group, Inc.
10.2.7. Cornerstone OnDemand, Inc.
10.2.8. Kronos Incorporated
10.2.9. Ceridian HCM, Inc.
10.2.10. Talentsoft
10.2.11. PeopleStrong HR Services Pvt. Ltd.
10.2.12. Phenom People, Inc.
10.2.13. Visier, Inc.
10.2.14. Entelo
10.2.15. HireVue Inc.
10.2.16. Textio
10.2.17. Brazen Technologies
10.2.18. AllyO
10.2.19. Pymetrics
10.2.20. Eightfold AI
10.2.21. ClearCompany
10.2.22. Jobvite, Inc.
10.2.23. Greenhouse Software, Inc.
10.2.24. Talview
10.2.25. Avature
10.2.26. Other Prominent Players
AI in the Human Resources Market By Type-
AI in the Human Resources Market By Application-
AI in the Human Resources Market By Deployment Mode-
AI in the Human Resources Market By Organization Size-
AI in the Human Resources Market By Region-
North America-
Europe-
Asia-Pacific-
Latin America-
Middle East & Africa-
InsightAce Analytic follows a standard and comprehensive market research methodology focused on offering the most accurate and precise market insights. The methods followed for all our market research studies include three significant steps – primary research, secondary research, and data modeling and analysis - to derive the current market size and forecast it over the forecast period. In this study, these three steps were used iteratively to generate valid data points (minimum deviation), which were cross-validated through multiple approaches mentioned below in the data modeling section.
Through secondary research methods, information on the market under study, its peer, and the parent market was collected. This information was then entered into data models. The resulted data points and insights were then validated by primary participants.
Based on additional insights from these primary participants, more directional efforts were put into doing secondary research and optimize data models. This process was repeated till all data models used in the study produced similar results (with minimum deviation). This way, this iterative process was able to generate the most accurate market numbers and qualitative insights.
Secondary research
The secondary research sources that are typically mentioned to include, but are not limited to:
The paid sources for secondary research like Factiva, OneSource, Hoovers, and Statista
Primary Research:
Primary research involves telephonic interviews, e-mail interactions, as well as face-to-face interviews for each market, category, segment, and subsegment across geographies
The contributors who typically take part in such a course include, but are not limited to:
Data Modeling and Analysis:
In the iterative process (mentioned above), data models received inputs from primary as well as secondary sources. But analysts working on these models were the key. They used their extensive knowledge and experience about industry and topic to make changes and fine-tuning these models as per the product/service under study.
The standard data models used while studying this market were the top-down and bottom-up approaches and the company shares analysis model. However, other methods were also used along with these – which were specific to the industry and product/service under study.
