AI 기반 인력 계획 시장 : 점유율 분석, 업계 동향과 통계, 성장 예측(2026-2031년)

According to Mordor Intelligence, the aI-powered workforce planning market size is expected to grow from USD 1.75 billion in 2025 to USD 1.87 billion in 2026 and is forecast to reach USD 2.69 billion by 2031 at 7.52% CAGR over 2026-2031.

This report is Segmented by Component (Software, and Services), Software Type (Workforce Scheduling and Planning, Workforce Analytics, and More), Deployment Mode (Cloud, and On-Premises), Organization Size (Large Enterprises, and Small and Medium Enterprises), End-User Industry (Government and Public Sector, and More), and Geography. The Market Forecasts are Provided in Terms of Value (USD).

Global AI-Powered Workforce Planning Market Trends and Insights

Agentic AI Copilots Compress Enterprise Planning Cycles

The AI-powered workforce planning market is moving beyond assistive AI tools and toward agentic systems that can connect data, run scenarios, and recommend actions with less human intervention. Product launches in 2025 and 2026 show that autonomous planning workflows are moving into mainstream workforce software roadmaps rather than remaining in experimental pilots. Legion introduced more than 90 AI workforce innovations in January 2026, and Eightfold introduced TalentForge in May 2026 to enable enterprises to build custom HR applications on its talent intelligence layer. That shift reduces the distance between a planning question and an operating response, especially when labor forecasts, schedules, and skills data need to be updated together. It also puts pressure on vendors that still rely on slower, human-reviewed batch workflows, as buyers increasingly expect continuous planning rather than periodic reporting. Enterprises still need strong override rules and auditable workflows because faster automation only supports the AI-powered workforce planning market when governance is embedded into day-to-day planning processes.

Need for Data-Driven Talent Allocation in Hybrid and Distributed Workforces

Hybrid and distributed work models are making static workforce snapshots much less useful in the AI-powered workforce planning market. Buyers increasingly need live visibility into staffing levels, schedules, internal mobility, labor demand, and budget limits across locations, teams, and worker types. SD Worx reported that 48.2% of European organizations identified scheduling efficiency and adequate staffing as primary reasons for making workforce planning a 2026 priority. That pattern shows that many employers are buying these tools to protect day-to-day operating continuity and service levels, not simply to pursue digital experimentation. Oracle's prebuilt AI agents in Fusion Cloud HCM also demonstrate how vendors are integrating internal mobility, career development, succession planning, and payroll anomaly detection into a single, connected workflow. As hybrid work structures remain in place, platforms that connect talent availability with business demand are improving their position in the AI-powered workforce planning market.

Data Privacy, Explainability, and Bias Risks in HR AI Models

Compliance pressure remains a real brake on the AI-powered workforce planning market when AI models influence task allocation, performance review, workforce monitoring, or skill inference. The EU AI Act classifies several workplace AI uses as high-risk, requiring buyers to implement stronger documentation, oversight controls, and accountability before full deployment. In the United States, rules such as California's FEHA obligations and New York City's annual bias audit requirements are pushing enterprises to require bias testing, record retention, and auditable decision logs before approving purchases. These obligations raise implementation costs and often lengthen sales cycles, especially for smaller vendors without dedicated governance teams. They also affect product design, because explainability is becoming a core buying criterion rather than an optional compliance feature. The result is a slower rollout path in regulated settings, even as larger vendors use governance readiness to differentiate themselves inside the AI-powered workforce planning market.

Other drivers and restraints analyzed in the detailed report include:

1. Rising Adoption of Skills-Based Workforce Planning and Internal Mobility
2. Cloud HCM and ERP Integration Enable Continuous Workforce Forecasting
3. Legacy Data Silos and Difficult Integration across HR, Finance, and Operations

For complete list of drivers and restraints, kindly check the Table Of Contents.

Segment Analysis

Software accounted for 63.12% of the AI-powered workforce planning market share in 2025, indicating that scheduling, analytics, and planning platforms remain the foundational technology layer for enterprise deployment. This weight reflects the product-led structure used by many vendors, where software subscriptions establish the account footprint before service work expands it across teams and geographies. Even so, services are forecast to grow at a 10.41% CAGR through 2031, the fastest pace among component segments, indicating where implementation complexity is rising. The gap between software scale and services growth suggests that buyers are no longer purchasing only a tool; they are also purchasing configuration, governance support, and operating assistance. That pattern is becoming more visible as the AI-powered workforce planning market moves from rule-based automation toward model-driven planning and continuous workforce intelligence.

Service demand rises further when vendors expand into verticals and countries where labor rules, union terms, and sector taxonomies need local configuration before the platform can be used effectively. ATOSS reported consulting revenue of EUR 35.9 million (USD 38.8 million) in FY2024, up 8% year over year, and linked part of that increase to more complex deployments in healthcare and logistics. For the AI-powered workforce planning industry, the result shows that product-led onboarding is still insufficient for many advanced planning and scheduling use cases. It also means the services layer can remain a meaningful revenue stream rather than a short implementation bridge that fades after go-live. Vendors that can combine scalable software with strong configuration, integration, and change support are likely to capture more durable revenue within the AI-powered workforce planning market.

Time and attendance management accounted for 37.14% of the software type segment in 2025, while workforce analytics will grow at a 9.33% CAGR through 2031, reflecting a shift from control functions toward decision support. Time and attendance remained central because compliance, labor rules, payroll linkage, and schedule execution still anchor platform selection in many enterprise accounts. Workforce analytics is expanding faster because buyers increasingly want systems that connect workforce data to cost, risk, skill availability, and capacity decisions. This changes the way software budgets are framed, since planning tools are being evaluated not only as HR applications but also as operating intelligence layers. In the AI-powered workforce planning market, that upgrade cycle is moving more value toward predictive and prescriptive capabilities than toward basic record-keeping functions.

Transactional modules such as scheduling, leave and absence management, and performance management remain sticky because they sit close to daily operations and are difficult to replace quickly. The next layer of spending is moving into analytics tools that sit above those modules and interpret attendance, performance, and staffing signals in a combined planning view. Orgvue introduced the Henshaw AI suite in December 2025, including automated role grouping and a natural language assistant for organizational data, which reduced manual work from months to minutes. That type of functionality supports faster role clustering, better skill mapping, and earlier detection of capacity gaps before those gaps affect business continuity. As a result, the AI-powered workforce planning market is rewarding vendors that can turn operational data into forward-looking planning actions rather than static reports.

Geography Analysis

North America held 38.56% of the AI-powered workforce planning market share in 2025, which made it the largest regional contributor and reflected earlier enterprise AI spending, mature cloud HCM adoption, and stronger software procurement cycles. The United States remains the core of that position because large health systems, technology firms, and retailers have sizable planning needs across distributed workforces and complex labor models. Health system labor pressure remains especially important, since hospitals are still absorbing high turnover costs and need better staffing forecasts and scheduling control to contain labor leakage. California FEHA rules and New York City's annual bias audit requirements are also pushing buyers toward platforms with clearer controls, stronger auditability, and documented decision logic. Canada and Mexico add smaller but expanding demand as cross-border talent visibility and regional labor coordination become more relevant to enterprise workforce strategies.

Asia-Pacific is forecast to grow at 9.67% CAGR through 2031, which makes it the fastest-growing geography in the AI-powered workforce planning market size. Growth in the region is being shaped by China's enterprise AI programs, India's large technology services base, and Japan's need to manage labor scarcity more tightly across aging workforce structures. Demand also benefits from the need to coordinate permanent staff, contractors, and gig workers across large operating footprints, especially in technology and business services. Australia and New Zealand, Japan, South Korea, and the rest of Asia-Pacific broaden the regional base, while South Korea is showing early traction in electronics and semiconductor scheduling use cases.

Europe holds a material position in the AI-powered workforce planning market, but procurement there is shaped by stronger compliance demands and more careful governance review than in several other regions. Workday reported in March 2026 that 41% of German companies said more than 60% of their workforce used AI tools in 2025, which shows high workplace AI exposure across the DACH region. That same environment also requires employers to work through co-determination and monitoring concerns before deploying workforce AI at scale. South America remains earlier in adoption, with Brazil's financial services and technology sectors supporting incremental demand, while the Middle East is using AI workforce planning inside broader digital transformation agendas. Africa is still nascent, but financial services and telecommunications in markets such as South Africa and Nigeria are creating early openings for the AI-powered workforce planning market.

1. ATOSS Software SE
2. WorkForce Software, LLC
3. Quinyx AB
4. Legion Technologies, Inc.
5. Deputechnologies Pty Ltd.
6. Shiftboard, Inc.
7. Sona Technologies Ltd.
8. TeamOhana, Inc.
9. Visier, Inc.
10. Orgvue Limited
11. Positive Circularity Inc. dba LIFELENZ
12. Ando Technologies, Inc.
13. Teambridge LLC
14. Vemo, Inc.
15. INOP B.V.
16. JobRoute, Inc.
17. Invero Holdings, LLC
18. Gloat Ltd.
19. Eightfold AI Inc.
20. Career Engagement Group d/b/a Fuel50

Additional Benefits:

• The market estimate (ME) sheet in Excel format
• 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

• 1.1 Study Assumptions and Market Definition
• 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET LANDSCAPE

• 4.1 Market Overview
• 4.2 Market Drivers
  • 4.2.1 Need for Data-Driven Talent Allocation in Hybrid and Distributed Workforces
  • 4.2.2 Rising Adoption of Skills-Based Workforce Planning and Internal Mobility
  • 4.2.3 Cloud HCM and ERP Integration Enabling Continuous Workforce Forecasting
  • 4.2.4 Labor Cost Pressure and Need for Productivity Optimization
  • 4.2.5 Agentic AI Copilots Compressing Workforce Planning Cycle Times
  • 4.2.6 AI-Led Workforce Redeployment for Enterprise Automation Programs
• 4.3 Market Restraints
  • 4.3.1 Data Privacy, Explainability, and Bias Risks in HR AI Models
  • 4.3.2 Legacy Data Silos and Difficult Integration Across HR, Finance, and Operations
  • 4.3.3 Low Confidence in AI-Generated Skill Inference for Regulated and Unionized Roles
  • 4.3.4 Diffuse Ownership Across HR, Finance, and Operations Slowing Enterprise Rollouts
• 4.4 Industry Value Chain Analysis
• 4.5 Regulatory Landscape
• 4.6 Technological Outlook
• 4.7 Impact of Macroeconomic Factors on the Market
• 4.8 Porter's Five Forces Analysis
  • 4.8.1 Threat of New Entrants
  • 4.8.2 Bargaining Power of Buyers
  • 4.8.3 Bargaining Power of Suppliers
  • 4.8.4 Threat of Substitutes
  • 4.8.5 Intensity of Competitive Rivalry

5 MARKET SIZE AND GROWTH FORECASTS (VALUE)

• 5.1 By Component
  • 5.1.1 Software
  • 5.1.2 Services
• 5.2 By Software Type
  • 5.2.1 Workforce Scheduling and Planning
  • 5.2.2 Time and Attendance Management
  • 5.2.3 Leave and Absence Management
  • 5.2.4 Workforce Analytics
  • 5.2.5 Employee Performance Management
  • 5.2.6 Other Software Types
• 5.3 By Deployment Mode
  • 5.3.1 Cloud
  • 5.3.2 On-premises
• 5.4 By Organization Size
  • 5.4.1 Large Enterprises
  • 5.4.2 Small and Medium Enterprises
• 5.5 By End-user Industry
  • 5.5.1 Banking, Financial Services, and Insurance
  • 5.5.2 Healthcare and Life Sciences
  • 5.5.3 IT and Telecommunications
  • 5.5.4 Manufacturing
  • 5.5.5 Retail and E-commerce
  • 5.5.6 Government and Public Sector
  • 5.5.7 Other End-User Industries
• 5.6 By Geography
  • 5.6.1 North America
    • 5.6.1.1 United States
    • 5.6.1.2 Canada
    • 5.6.1.3 Mexico
  • 5.6.2 South America
    • 5.6.2.1 Brazil
    • 5.6.2.2 Argentina
    • 5.6.2.3 Rest of South America
  • 5.6.3 Europe
    • 5.6.3.1 Germany
    • 5.6.3.2 United Kingdom
    • 5.6.3.3 France
    • 5.6.3.4 Italy
    • 5.6.3.5 Spain
    • 5.6.3.6 Russia
    • 5.6.3.7 Rest of Europe
  • 5.6.4 Asia-Pacific
    • 5.6.4.1 China
    • 5.6.4.2 Japan
    • 5.6.4.3 India
    • 5.6.4.4 Australia and New Zealand
    • 5.6.4.5 South Korea
    • 5.6.4.6 Rest of Asia-Pacific
  • 5.6.5 Middle East
    • 5.6.5.1 United Arab Emirates
    • 5.6.5.2 Saudi Arabia
    • 5.6.5.3 Turkey
    • 5.6.5.4 Rest of Middle East
  • 5.6.6 Africa
    • 5.6.6.1 South Africa
    • 5.6.6.2 Nigeria
    • 5.6.6.3 Rest of Africa

6 COMPETITIVE LANDSCAPE

• 6.1 Market Concentration
• 6.2 Strategic Moves
• 6.3 Market Share Analysis
• 6.4 Company Profiles (includes Global Level Overview, Market Level Overview, Core Segments, Financials as available, Strategic Information, Market Rank/Share, Products and Services, Recent Developments)
  • 6.4.1 ATOSS Software SE
  • 6.4.2 WorkForce Software, LLC
  • 6.4.3 Quinyx AB
  • 6.4.4 Legion Technologies, Inc.
  • 6.4.5 Deputechnologies Pty Ltd.
  • 6.4.6 Shiftboard, Inc.
  • 6.4.7 Sona Technologies Ltd.
  • 6.4.8 TeamOhana, Inc.
  • 6.4.9 Visier, Inc.
  • 6.4.10 Orgvue Limited
  • 6.4.11 Positive Circularity Inc. dba LIFELENZ
  • 6.4.12 Ando Technologies, Inc.
  • 6.4.13 Teambridge LLC
  • 6.4.14 Vemo, Inc.
  • 6.4.15 INOP B.V.
  • 6.4.16 JobRoute, Inc.
  • 6.4.17 Invero Holdings, LLC
  • 6.4.18 Gloat Ltd.
  • 6.4.19 Eightfold AI Inc.
  • 6.4.20 Career Engagement Group d/b/a Fuel50

7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK

• 7.1 White-Space and Unmet-Need Assessment