Artificial Intelligence in HR Market (By Offering: Hardware, Software Services; By Technology: Virtual Assistants, Metaverse, AI Chatbot, People Analytics, Machine Learning, Computer Vision, Natural Language Processing; By Enterprise Size: Small, Large Enterprises; By Application: Workforce Management, Recruitment and Hiring; By Industry: Academic, Banking Financial Services and Insurance, Retail ) - Global Industry Analysis, Size, Share, Growth, Trends, Regional Outlook, and Forecast 2024-2033
The global artificial intelligence in HR market size was USD 6.03 billion in 2023, estimated at USD 7.01 billion in 2024 and is projected to hit around USD 27.30 billion by 2033, expanding at a CAGR of 16.30% from 2024 to 2033. The artificial intelligence in HR market is driven by the growing interest in making decisions based on data in multiple firms, especially in developed countries.
To Access our Exclusive Data Intelligence Tool with 15000+ Database, Visit: Precedence Statistics
The U.S. artificial intelligence in HR market size was valued at USD 1.65 billion in 2023 and is expected to be worth around USD 7.60 billion by 2033 with a CAGR of 16.50% from 2024 to 2033.
North America dominated the artificial intelligence in HR market in 2023. AI businesses are financed by a thriving venture capital ecosystem in North America, especially in the United States. AI businesses specializing in HR solutions have received significant investment from Sequoia Capital, Andreessen Horowitz, and Accel Partners. Federal and state governments encourage innovation in the HR industry by offering grants and subsidies for AI research and businesses.
Asia- Pacific is observed to be the fastest growing in the artificial intelligence in HR market during the forecast period. Asia-Pacific nations boast some of the world's largest populations, contributing to a diverse labor force. Sophisticated HR solutions are needed to manage this workforce effectively. AI solutions assist local businesses in effectively managing personnel acquisition, employee engagement, and retention. These solutions offer data-driven insights, predictive analytics, and tailored experiences to manage massive amounts of HR data.
In the HR industry, artificial intelligence (AI) refers to the application of AI technology to human resources operations to improve and expedite workforce management, recruitment, employee engagement, training, and performance evaluation procedures. Artificial intelligence (AI) may automate tedious processes like resume screening, allowing HR personnel to concentrate on key projects. This efficiency might result in significant cost reductions in hiring procedures and day-to-day HR duties. AI in HR can support fairness and diversity in hiring and performance reviews by standardizing candidate evaluation criteria and reducing human bias in decision-making processes.
Report Coverage | Details |
Market Size by 2033 | USD 27.30 Billion |
Market Size in 2023 | USD 6.03 Billion |
Market Size in 2024 | USD 7.01 Billion |
Market Growth Rate from 2024 to 2033 | CAGR of 16.30% |
Largest Market | North America |
Base Year | 2023 |
Forecast Period | 2024 to 2033 |
Segments Covered | Offering,Technology, Enterprise Size, Application, Industry, and Regions |
Regions Covered | North America, Europe, Asia-Pacific, Latin America, and Middle East & Africa |
Enhanced recruitment processes
AI-powered hiring procedures can improve candidates' experiences by responding more quickly, facilitating individualized conversations, and maintaining constant contact throughout the hiring process. Artificial intelligence (AI)-powered chatbots can quickly and effectively respond to candidate inquiries, guaranteeing a seamless and satisfying experience essential for company branding. AI dramatically lowers hiring expenses by increasing productivity and automating monotonous jobs. Businesses can allocate resources more efficiently by concentrating on the strategic elements of hiring and employee engagement instead of administrative duties.
Cost of implementation
For AI systems to work well, a strong infrastructure is needed. This could entail modernizing networking infrastructure, servers, and storage systems to meet the processing demands of artificial intelligence algorithms. It could be difficult for small to mid-sized businesses to justify or finance these infrastructural expenditures. Implementing AI carries some inherent risks, like the possibility of algorithm biases, data breaches, or problems with regulatory compliance. The entire cost of AI adoption in HR is increased by the need to spend on cybersecurity safeguards, auditing procedures, and legal advice to mitigate these risks. This limits the growth of artificial intelligence in HR market.
Automation of routine tasks
AI systems can forecast future patterns in employee engagement, performance, and attrition using historical data. HR departments can improve organizational stability and retain top people by taking proactive initiatives to anticipate possible issues before they arise. AI may help with administrative duties including payroll processing, benefits administration, compliance monitoring, recruiting, and talent management. While these tasks are vital, they are frequently resource-intensive; automation lowers errors and frees HR specialists to work on more important tasks.
Improved employee engagement
AI can analyze enormous volumes of employee data to comprehend work habits, career goals, and personal preferences. This enables HR departments to better fit everyone with experiences like job assignments, career growth pathways, and training programs. Artificial Intelligence improves employee engagement and happiness by personalizing these experiences. This opens an opportunity for the rise of artificial intelligence in HR market.
The services segment held the significant share of the artificial intelligence in HR market in 2023.
HR AI has an enormous effect on an organization's strategy. Service providers provide consulting services to assist firms in creating and implementing a strategy plan for the use of AI in HR. A change in organizational culture is necessary to incorporate AI in HR. Service providers aid with change management, guiding businesses through the shift and winning over stakeholders. AI-powered HR solutions must expand to accommodate the company's expansion. Service providers guarantee long-term viability and efficacy by providing scalable solutions that can expand with the company.
The machine learning segment led the artificial intelligence in HR market in 2023.
The entire employee experience can be improved by machine learning by enabling the personalization of HR services. Employees' abilities, career objectives, and performance data can all be used to develop personalized learning paths for them, resulting in more efficient and interesting training sessions. ML can track indicators of employee well-being, which can also recommend resources or interventions to promote work-life balance and mental health.
By examining the abilities, responsibilities, and career pathways of others, machine learning techniques can assist staff members in understanding possible career paths inside the company. The virtual assistance segment is observed to grow at a notable rate in the artificial intelligence in HR market during the forecast period. As remote work becomes more common, virtual assistants are becoming increasingly important in ensuring that remote workers receive smooth support and communication.
Virtual assistants can assist recently hired remote workers with onboarding, ensuring they have access to all the tools and information they need. Keeping employees engaged in a remote work environment can be difficult, but virtual assistants can help by helping, feedback, and regular check-ins.
The large enterprises segment dominated artificial intelligence in HR market in 2023. Regarding financial resources, large companies have a lot more than small and medium-sized businesses (SMBs). Their strong financial position enables them to invest significantly in AI technology, such as advanced HR software. They can cover the initial expenditures of implementing AI systems and continuing maintenance, updates, and training charges. Over time, these investments strengthen their capacity to save operating expenses, increase efficiency, and streamline HR procedures. Large businesses place a high premium on improving the employee experience.
Artificial Intelligence (AI) in HR may make a big difference by offering individualized help via chatbots, virtual assistants, and self-service portals. These systems increase employee happiness and engagement by managing employee inquiries, helping with onboarding, and facilitating anytime access to HR services.
The recruitment and hiring segment dominated the artificial intelligence in HR market in 2023. Recruiters can spend less time assessing resumes by using AI solutions to automate this process. Natural language processing (NLP) is a technique automated systems use to comprehend and assess resumes to select the best applicants for additional review. Using predictive analytics, artificial intelligence (AI) tools evaluate candidates' probable future performance and cultural fit with the organization. This leads to greater workforce quality overall and increased retention rates by assisting recruiters in making more educated judgments.
The IT and telecom segment dominated the artificial intelligence in HR market in 2023. With AI-powered recruitment tools, these businesses can effectively sort through many applications, find the best candidates using machine learning and predictive analytics solutions, gain insight into employee engagement and satisfaction, and proactively address issues that may cause turnover. AI technologies may expand as a firm grows, effectively managing growing quantities of HR activities. AI-driven HR solutions can be customized to handle problems unique to a certain business, such overseeing distant workers or guaranteeing adherence to international legal requirements.
The BFSI segment is observed to be the fastest growing in artificial intelligence in HR market during the forecast period. BFSI organizations use AI solutions in HR to analyze employee data and obtain insights into employee engagement and satisfaction levels. Predictive analytics can identify at-risk individuals and provide interventions to keep top talent on board. AI-powered personalized training and development plans adapted to each employee's unique needs result in reduced employee turnover and increased job satisfaction.
Since the BFSI industry is heavily regulated, following the law is crucial. By automating compliance monitoring and reporting, AI-powered HR solutions contribute to maintaining compliance with internal policies and labor laws. AI solutions can monitor regulation changes and update HR procedures, lowering the risk of non-compliance and the fines that come with it.
In May 2023, With the recent announcement of SAP and Microsoft's extended relationship, the dream of enterprise-ready generative AI that can improve worker productivity and development is becoming closer to reality. By combining SAP SuccessFactors solutions with Copilot in Viva Learning and Microsoft 365 Copilot, enterprises will be able to better retain, upskill, and hire workers to close skills shortages.
Segments Covered in the Report
By Offering
By Technology
By Enterprise Size
By Application
By Industry
By Geography
Chapter 1. Introduction
1.1. Research Objective
1.2. Scope of the Study
1.3. Definition
Chapter 2. Research Methodology (Premium Insights)
2.1. Research Approach
2.2. Data Sources
2.3. Assumptions & Limitations
Chapter 3. Executive Summary
3.1. Market Snapshot
Chapter 4. Market Variables and Scope
4.1. Introduction
4.2. Market Classification and Scope
4.3. Industry Value Chain Analysis
4.3.1. Raw Material Procurement Analysis
4.3.2. Sales and Distribution Channel Analysis
4.3.3. Downstream Buyer Analysis
Chapter 5. COVID 19 Impact on Artificial Intelligence in HR Market
5.1. COVID-19 Landscape: Artificial Intelligence in HR Industry Impact
5.2. COVID 19 - Impact Assessment for the Industry
5.3. COVID 19 Impact: Global Major Government Policy
5.4. Market Trends and Opportunities in the COVID-19 Landscape
Chapter 6. Market Dynamics Analysis and Trends
6.1. Market Dynamics
6.1.1. Market Drivers
6.1.2. Market Restraints
6.1.3. Market Opportunities
6.2. Porter’s Five Forces Analysis
6.2.1. Bargaining power of suppliers
6.2.2. Bargaining power of buyers
6.2.3. Threat of substitute
6.2.4. Threat of new entrants
6.2.5. Degree of competition
Chapter 7. Competitive Landscape
7.1.1. Company Market Share/Positioning Analysis
7.1.2. Key Strategies Adopted by Players
7.1.3. Vendor Landscape
7.1.3.1. List of Suppliers
7.1.3.2. List of Buyers
Chapter 8. Global Artificial Intelligence in HR Market, By Offering
8.1. Artificial Intelligence in HR Market, by Offering, 2024-2033
8.1.1. Hardware
8.1.1.1. Market Revenue and Forecast (2021-2033)
8.1.2. Software
8.1.2.1. Market Revenue and Forecast (2021-2033)
8.1.3. Services
8.1.3.1. Market Revenue and Forecast (2021-2033)
Chapter 9. Global Artificial Intelligence in HR Market, By Technology
9.1. Artificial Intelligence in HR Market, by Technology, 2024-2033
9.1.1. Virtual Assistants
9.1.1.1. Market Revenue and Forecast (2021-2033)
9.1.2. Metaverse
9.1.2.1. Market Revenue and Forecast (2021-2033)
9.1.3. AI Chatbot
9.1.3.1. Market Revenue and Forecast (2021-2033)
9.1.4. People Analytics
9.1.4.1. Market Revenue and Forecast (2021-2033)
9.1.5. Machine Learning
9.1.5.1. Market Revenue and Forecast (2021-2033)
9.1.6. Computer Vision
9.1.6.1. Market Revenue and Forecast (2021-2033)
9.1.7. Natural Language Processing
9.1.7.1. Market Revenue and Forecast (2021-2033)
Chapter 10. Global Artificial Intelligence in HR Market, By Enterprise Size
10.1. Artificial Intelligence in HR Market, by Enterprise Size, 2024-2033
10.1.1. Small and Medium Enterprises
10.1.1.1. Market Revenue and Forecast (2021-2033)
10.1.2. Large Enterprises
Chapter 11. Global Artificial Intelligence in HR Market, By Application
11.1. Artificial Intelligence in HR Market, by Application, 2024-2033
11.1.1. Workforce Management
11.1.1.1. Market Revenue and Forecast (2021-2033)
11.1.2. Talent Management
11.1.2.1. Market Revenue and Forecast (2021-2033)
11.1.3. Payroll Management
11.1.3.1. Market Revenue and Forecast (2021-2033)
11.1.4. Payroll Management
11.1.4.1. Market Revenue and Forecast (2021-2033)
11.1.5. Recruitment and Hiring
11.1.5.1. Market Revenue and Forecast (2021-2033)
Chapter 12. Global Artificial Intelligence in HR Market, By Industry
12.1. Artificial Intelligence in HR Market, by Industry, 2024-2033
12.1.1. Academic
12.1.1.1. Market Revenue and Forecast (2021-2033)
12.1.2. Banking Financial Services and Insurance (BFSI)
12.1.2.1. Market Revenue and Forecast (2021-2033)
12.1.3. Government
12.1.3.1. Market Revenue and Forecast (2021-2033)
12.1.4. Healthcare
12.1.4.1. Market Revenue and Forecast (2021-2033)
12.1.5. Information Technology (IT) and Telecom
12.1.5.1. Market Revenue and Forecast (2021-2033)
12.1.6. Manufacturing
12.1.6.1. Market Revenue and Forecast (2021-2033)
12.1.7. Retail
12.1.7.1. Market Revenue and Forecast (2021-2033)
Chapter 13. Global Artificial Intelligence in HR Market, Regional Estimates and Trend Forecast
13.1. North America
13.1.1. Market Revenue and Forecast, by Offering (2021-2033)
13.1.2. Market Revenue and Forecast, by Technology (2021-2033)
13.1.3. Market Revenue and Forecast, by Enterprise Size (2021-2033)
13.1.4. Market Revenue and Forecast, by Application (2021-2033)
13.1.5. Market Revenue and Forecast, by Industry (2021-2033)
13.1.6. U.S.
13.1.6.1. Market Revenue and Forecast, by Offering (2021-2033)
13.1.6.2. Market Revenue and Forecast, by Technology (2021-2033)
13.1.6.3. Market Revenue and Forecast, by Enterprise Size (2021-2033)
13.1.6.4. Market Revenue and Forecast, by Application (2021-2033)
13.1.6.5. Market Revenue and Forecast, by Industry (2021-2033)
13.1.7. Rest of North America
13.1.7.1. Market Revenue and Forecast, by Offering (2021-2033)
13.1.7.2. Market Revenue and Forecast, by Technology (2021-2033)
13.1.7.3. Market Revenue and Forecast, by Enterprise Size (2021-2033)
13.1.7.4. Market Revenue and Forecast, by Application (2021-2033)
13.1.7.5. Market Revenue and Forecast, by Industry (2021-2033)
13.2. Europe
13.2.1. Market Revenue and Forecast, by Offering (2021-2033)
13.2.2. Market Revenue and Forecast, by Technology (2021-2033)
13.2.3. Market Revenue and Forecast, by Enterprise Size (2021-2033)
13.2.4. Market Revenue and Forecast, by Application (2021-2033)
13.2.5. Market Revenue and Forecast, by Industry (2021-2033)
13.2.6. UK
13.2.6.1. Market Revenue and Forecast, by Offering (2021-2033)
13.2.6.2. Market Revenue and Forecast, by Technology (2021-2033)
13.2.6.3. Market Revenue and Forecast, by Enterprise Size (2021-2033)
13.2.7. Market Revenue and Forecast, by Application (2021-2033)
13.2.8. Market Revenue and Forecast, by Industry (2021-2033)
13.2.9. Germany
13.2.9.1. Market Revenue and Forecast, by Offering (2021-2033)
13.2.9.2. Market Revenue and Forecast, by Technology (2021-2033)
13.2.9.3. Market Revenue and Forecast, by Enterprise Size (2021-2033)
13.2.10. Market Revenue and Forecast, by Application (2021-2033)
13.2.11. Market Revenue and Forecast, by Industry (2021-2033)
13.2.12. France
13.2.12.1. Market Revenue and Forecast, by Offering (2021-2033)
13.2.12.2. Market Revenue and Forecast, by Technology (2021-2033)
13.2.12.3. Market Revenue and Forecast, by Enterprise Size (2021-2033)
13.2.12.4. Market Revenue and Forecast, by Application (2021-2033)
13.2.13. Market Revenue and Forecast, by Industry (2021-2033)
13.2.14. Rest of Europe
13.2.14.1. Market Revenue and Forecast, by Offering (2021-2033)
13.2.14.2. Market Revenue and Forecast, by Technology (2021-2033)
13.2.14.3. Market Revenue and Forecast, by Enterprise Size (2021-2033)
13.2.14.4. Market Revenue and Forecast, by Application (2021-2033)
13.2.15. Market Revenue and Forecast, by Industry (2021-2033)
13.3. APAC
13.3.1. Market Revenue and Forecast, by Offering (2021-2033)
13.3.2. Market Revenue and Forecast, by Technology (2021-2033)
13.3.3. Market Revenue and Forecast, by Enterprise Size (2021-2033)
13.3.4. Market Revenue and Forecast, by Application (2021-2033)
13.3.5. Market Revenue and Forecast, by Industry (2021-2033)
13.3.6. India
13.3.6.1. Market Revenue and Forecast, by Offering (2021-2033)
13.3.6.2. Market Revenue and Forecast, by Technology (2021-2033)
13.3.6.3. Market Revenue and Forecast, by Enterprise Size (2021-2033)
13.3.6.4. Market Revenue and Forecast, by Application (2021-2033)
13.3.7. Market Revenue and Forecast, by Industry (2021-2033)
13.3.8. China
13.3.8.1. Market Revenue and Forecast, by Offering (2021-2033)
13.3.8.2. Market Revenue and Forecast, by Technology (2021-2033)
13.3.8.3. Market Revenue and Forecast, by Enterprise Size (2021-2033)
13.3.8.4. Market Revenue and Forecast, by Application (2021-2033)
13.3.9. Market Revenue and Forecast, by Industry (2021-2033)
13.3.10. Japan
13.3.10.1. Market Revenue and Forecast, by Offering (2021-2033)
13.3.10.2. Market Revenue and Forecast, by Technology (2021-2033)
13.3.10.3. Market Revenue and Forecast, by Enterprise Size (2021-2033)
13.3.10.4. Market Revenue and Forecast, by Application (2021-2033)
13.3.10.5. Market Revenue and Forecast, by Industry (2021-2033)
13.3.11. Rest of APAC
13.3.11.1. Market Revenue and Forecast, by Offering (2021-2033)
13.3.11.2. Market Revenue and Forecast, by Technology (2021-2033)
13.3.11.3. Market Revenue and Forecast, by Enterprise Size (2021-2033)
13.3.11.4. Market Revenue and Forecast, by Application (2021-2033)
13.3.11.5. Market Revenue and Forecast, by Industry (2021-2033)
13.4. MEA
13.4.1. Market Revenue and Forecast, by Offering (2021-2033)
13.4.2. Market Revenue and Forecast, by Technology (2021-2033)
13.4.3. Market Revenue and Forecast, by Enterprise Size (2021-2033)
13.4.4. Market Revenue and Forecast, by Application (2021-2033)
13.4.5. Market Revenue and Forecast, by Industry (2021-2033)
13.4.6. GCC
13.4.6.1. Market Revenue and Forecast, by Offering (2021-2033)
13.4.6.2. Market Revenue and Forecast, by Technology (2021-2033)
13.4.6.3. Market Revenue and Forecast, by Enterprise Size (2021-2033)
13.4.6.4. Market Revenue and Forecast, by Application (2021-2033)
13.4.7. Market Revenue and Forecast, by Industry (2021-2033)
13.4.8. North Africa
13.4.8.1. Market Revenue and Forecast, by Offering (2021-2033)
13.4.8.2. Market Revenue and Forecast, by Technology (2021-2033)
13.4.8.3. Market Revenue and Forecast, by Enterprise Size (2021-2033)
13.4.8.4. Market Revenue and Forecast, by Application (2021-2033)
13.4.9. Market Revenue and Forecast, by Industry (2021-2033)
13.4.10. South Africa
13.4.10.1. Market Revenue and Forecast, by Offering (2021-2033)
13.4.10.2. Market Revenue and Forecast, by Technology (2021-2033)
13.4.10.3. Market Revenue and Forecast, by Enterprise Size (2021-2033)
13.4.10.4. Market Revenue and Forecast, by Application (2021-2033)
13.4.10.5. Market Revenue and Forecast, by Industry (2021-2033)
13.4.11. Rest of MEA
13.4.11.1. Market Revenue and Forecast, by Offering (2021-2033)
13.4.11.2. Market Revenue and Forecast, by Technology (2021-2033)
13.4.11.3. Market Revenue and Forecast, by Enterprise Size (2021-2033)
13.4.11.4. Market Revenue and Forecast, by Application (2021-2033)
13.4.11.5. Market Revenue and Forecast, by Industry (2021-2033)
13.5. Latin America
13.5.1. Market Revenue and Forecast, by Offering (2021-2033)
13.5.2. Market Revenue and Forecast, by Technology (2021-2033)
13.5.3. Market Revenue and Forecast, by Enterprise Size (2021-2033)
13.5.4. Market Revenue and Forecast, by Application (2021-2033)
13.5.5. Market Revenue and Forecast, by Industry (2021-2033)
13.5.6. Brazil
13.5.6.1. Market Revenue and Forecast, by Offering (2021-2033)
13.5.6.2. Market Revenue and Forecast, by Technology (2021-2033)
13.5.6.3. Market Revenue and Forecast, by Enterprise Size (2021-2033)
13.5.6.4. Market Revenue and Forecast, by Application (2021-2033)
13.5.7. Market Revenue and Forecast, by Industry (2021-2033)
13.5.8. Rest of LATAM
13.5.8.1. Market Revenue and Forecast, by Offering (2021-2033)
13.5.8.2. Market Revenue and Forecast, by Technology (2021-2033)
13.5.8.3. Market Revenue and Forecast, by Enterprise Size (2021-2033)
13.5.8.4. Market Revenue and Forecast, by Application (2021-2033)
13.5.8.5. Market Revenue and Forecast, by Industry (2021-2033)
Chapter 14. Company Profiles
14.1. IBM Corporation
14.1.1. Company Overview
14.1.2. Product Offerings
14.1.3. Financial Performance
14.1.4. Recent Initiatives
14.2. Oracle Corporation
14.2.1. Company Overview
14.2.2. Product Offerings
14.2.3. Financial Performance
14.2.4. Recent Initiatives
14.3. SAP SE
14.3.1. Company Overview
14.3.2. Product Offerings
14.3.3. Financial Performance
14.3.4. Recent Initiatives
14.4. Automatic Data Processing Inc
14.4.1. Company Overview
14.4.2. Product Offerings
14.4.3. Financial Performance
14.4.4. Recent Initiatives
14.5. Cegid Group
14.5.1. Company Overview
14.5.2. Product Offerings
14.5.3. Financial Performance
14.5.4. Recent Initiatives
14.6. Cornerstone OnDemand Inc
14.6.1. Company Overview
14.6.2. Product Offerings
14.6.3. Financial Performance
14.6.4. Recent Initiatives
14.7. Job Teaser
14.7.1. Company Overview
14.7.2. Product Offerings
14.7.3. Financial Performance
14.7.4. Recent Initiatives
14.8. Phenom People Inc
14.8.1. Company Overview
14.8.2. Product Offerings
14.8.3. Financial Performance
14.8.4. Recent Initiatives
14.9. Eightfold AI
14.9.1. Company Overview
14.9.2. Product Offerings
14.9.3. Financial Performance
14.9.4. Recent Initiatives
14.10. Simpplr
14.10.1. Company Overview
14.10.2. Product Offerings
14.10.3. Financial Performance
14.10.4. Recent Initiatives
Chapter 15. Research Methodology
15.1. Primary Research
15.2. Secondary Research
15.3. Assumptions
Chapter 16. Appendix
16.1. About Us
16.2. Glossary of Terms
No cookie-cutter, only authentic analysis – take the 1st step to become a Precedence Research client