하이퍼오토메이션 : 시장 점유율 분석, 업계 동향과 통계, 성장 예측(2026-2031년)

According to Mordor Intelligence, the hyper automation market size in 2026 is estimated at USD 18.64 billion, growing from 2025 value of USD 15.62 billion with 2031 projections showing USD 45.17 billion, growing at 19.36% CAGR over 2026-2031.

This report is Segmented by Component (Solutions, Services), Technology Type (RPA, ML/DL, NLP/Chatbots, Process Mining, Computer Vision), Deployment Mode (On-Premise, Cloud, Hybrid), Enterprise Size (Large, Smes), End-User Industry (BFSI, Retail, IT, Manufacturing, and More), and Geography (North America, South America, Europe, Asia Pacific, MEA). Market Forecasts are Provided in Value (USD).

Global Hyperautomation Market Trends and Insights

Rising Industrial Automation Initiatives

Manufacturers now embed the hyper automation market's toolset across production lines to remedy supply-chain shocks and worker scarcity observed after 2024. Coca-Cola's Singapore lighthouse plant lifted throughput 28% and labor productivity 70% by merging predictive scheduling with computer-vision quality control. Textile producer Delta Galil harnessed RFID insights to benchmark line-level efficiency and spark inter-team competition, shrinking downtime and boosting yields. Hyper automation reaches beyond robotics by logging granular asset data, feeding machine-learning models that flag anomalies before they disrupt production. That shift from reactive to predictive maintenance reduces scrap, lengthens equipment life, and improves schedule adherence, making investment cases compelling even in cost-sensitive environments. Enterprises increasingly standardize data capture at the edge, enabling centralized analytics that iterate process tweaks in near real time.

Digital-First Enterprise Strategies for Cost Optimization

Board mandates for structural cost take-out now demand redesign of core workflows rather than piecemeal savings. Companies replacing manual invoice handling, claims adjudication, and customer onboarding report triple-digit ROI inside 12 months, driven by lower error rates and faster cycle times. Ring Container's deployment of AI-infused automation shaved USD 102,000 annually from freight paperwork processing and accelerated customer inquiry resolution by 96%. These initiatives redirect labor toward higher-value analysis and innovation, fortifying customer loyalty through shorter time-to-market. Hyper automation further underpins data-driven revenue plays such as dynamic pricing and personalized offers, reinforcing its position as a catalyst for both cost and top-line gains.

High Upfront Investment Requirements

Comprehensive hyper automation programs require sizable capital software, infrastructure upgrades, and change-management spending that can dwarf ordinary IT refresh cycles. SAP budgeted EUR 2 billion (USD 2.18 billion) restructuring outlays to unlock AI-driven efficiencies, illustrating the scale facing Fortune 500 peers. Mid-market firms often struggle to finance similar journeys despite compelling payback models, forcing phased rollouts or managed-service engagements. The sticker shock also includes training existing staff, re-engineering processes, and integrating legacy systems, making clear executive sponsorship essential to cross the investment hurdle.

Other drivers and restraints analyzed in the detailed report include:

1. Rapid Adoption of RPA-AI Convergence Platforms
2. Skill-Gap Driven Demand for Low-Code Citizen-Developer Tools
3. Shortage of Integration Talent

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

Segment Analysis

Solutions retained 60.58% of the hyper automation market share in 2025 as enterprises gravitated toward unified suites that bundle process discovery, orchestration, and analytics. Vendor roadmaps emphasize modular architectures so customers can activate new capabilities without large-scale re-implementations. Services, however, are growing faster at 20.05% CAGR because organizations increasingly rely on external experts to customize deployments and manage iterative optimization. Advisory partners design governance frameworks, center-of-excellence models, and ROI dashboards, ensuring business outcomes outweigh feature checklists. Managed services gain traction where internal teams lack round-the-clock talent, shifting cost from capital budgets to predictable operating expense.

Professional services further expand the hyper automation market size by de-risking global rollouts through accelerate-to-value methodologies, industry-specific templates, and post-go-live monitoring. Providers bundle change-management coaching with technical delivery, helping staff adapt to new human-bot collaboration patterns. The move toward outcome-based pricing aligns incentives, with service firms staking fees on productivity benchmarks, fueling a virtuous cycle of continuous improvement and deeper platform penetration.

Robotic process automation held 38.92% revenue in 2025, yet process and task mining's 28.10% CAGR signals an analytic-first era where data-derived insights guide investment order. Mining tools scrutinize event logs to surface fragmentation, latency, and compliance deviations, translating findings into automation candidate pipelines with quantified savings potential. Machine-learning and deep-learning components amplify this discovery by predicting volume spikes, exception scenarios, and failure likelihood, informing dynamic resource allocation. Natural-language interfaces allow business analysts to query process maps conversationally, widening access to optimization insights.

Computer-vision modules extend the hyper automation market beyond back-office screens to physical-world inspection, identity verification, and inventory checks. Chatbots, powered by large language models, blend empathetic dialogue with transactional execution, elevating customer experience. Collectively, these converging technologies push vendors to offer plug-and-play orchestration layers that support heterogeneous engines, ensuring clients can evolve stacks without lock-in.

Complete Report Scope:

• By Component
  • Solutions
  • Services
• By Technology Type
  • Robotic Process Automation (RPA)
  • Machine Learning and Deep Learning
  • Natural Language Processing and Chatbots
  • Process and Task Mining
  • Computer Vision and Biometrics
• By Deployment Mode
  • On-premise
  • Cloud
  • Hybrid
• By End-User Enterprise Size
  • Large Enterprises
  • Small and Mid-Sized Enterprises (SMEs)
• By End-User Industry
  • BFSI
  • Retail and e-Commerce
  • IT and Telecom
  • Manufacturing and Automotive
  • Healthcare and Life Sciences
  • Education
  • Others End-user Industry
• By Geography
  • North America
    • United States
    • Canada
    • Mexico
  • South America
    • Brazil
    • Argentina
    • Rest of South America
  • Europe
    • Germany
    • United Kingdom
    • France
    • Italy
    • Spain
    • Russia
    • Rest of Europe
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • ASEAN-5
    • Australia and New Zealand
    • Rest of Asia Pacific
  • Middle East and Africa
    • Middle East
      • United Arab Emirates
      • Saudi Arabia
      • Rest of Middle East
    • Africa
      • South Africa
      • Nigeria
      • Rest of Africa

Geography Analysis

North America held 36.27% hyper automation market share in 2025, anchored by deep enterprise budgets, venture capital ecosystems, and seasoned automation talent pools. U.S. healthcare provider Dexcom saved 200,000 hours annually and cut cycle times 80% by harnessing AI-enabled bots inside finance and supply-chain teams. Financial regulators' emphasis on operational resilience further accelerates uptake across banking and insurance. Canada complements with manufacturing use cases in automotive parts and food processing, while Mexico advances border-zone smart factories, showcasing cross-regional supply-chain orchestration.

Asia Pacific posts the fastest trajectory at 19.10% CAGR to 2031, invigorated by state-sponsored Industry 4.0 funds, large-scale electronics hubs, and competitive wage pressures. China's provincial grants subsidize hyper automation adoption in textiles and logistics, while Japan embeds cognitive quality control in automotive paint shops. India leverages bots to enhance BPO accuracy and reduce average handling time for global clients. Australia stands out: 96% of enterprises reported automation plans spanning finance, HR, and customer service, indicating near-universal intent. ASEAN manufacturers deploy edge analytics to cut energy costs and meet export quality mandates.

Europe balances innovation with governance, guided by the AI Act that classifies hyper automation applications by risk category and stipulates transparency, bias mitigation, and human-in-the-loop provisions. Germany leads industrial transformation, embedding process-mining dashboards in discrete manufacturing plants. The United Kingdom positions hyper automation as a lever for competitive post-Brexit trade facilitation, emphasizing customs clearance automation. France pilots hospital workflow bots to relieve administrative overload, while Italy incentivizes SME adoption through tax credits linked to digitalization milestones.

1. ABBYY Solutions Ltd.
2. akaBot (FPT Software)
3. Alteryx Inc.
4. Appian Corporation
5. Automation Anywhere Inc.
6. Blue Prism Ltd.
7. Catalytic Inc.
8. Celonis SE
9. IBM Corporation
10. Microsoft Corporation
11. Mitsubishi Electric Corporation
12. NICE Ltd.
13. OneGlobe LLC
14. Pegasystems Inc.
15. Rocketbot SpA
16. Salesforce Inc.
17. Simple Fractal LLC
18. SolveXia Pty Ltd.
19. UiPath Inc.
20. WorkFusion Inc.

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 Rising industrial automation initiatives
  • 4.2.2 Digital-first enterprise strategies for cost optimisation
  • 4.2.3 Rapid adoption of RPA-AI convergence platforms
  • 4.2.4 Skill-gap driven demand for low-code citizen-developer tools
  • 4.2.5 Process-mining-led self-optimising workflows
  • 4.2.6 Edge-enabled hyperautomation in connected factories
• 4.3 Market Restraints
  • 4.3.1 High upfront investment requirements
  • 4.3.2 Shortage of integration talent
  • 4.3.3 Data-sovereignty barriers to cloud deployment
  • 4.3.4 Algorithmic-transparency compliance delays
• 4.4 Industry Value-Chain Analysis
• 4.5 Regulatory Landscape
• 4.6 Technological Outlook
• 4.7 Porter's Five Forces Analysis
  • 4.7.1 Bargaining Power of Suppliers
  • 4.7.2 Bargaining Power of Buyers
  • 4.7.3 Threat of New Entrants
  • 4.7.4 Threat of Substitutes
  • 4.7.5 Intensity of Competitive Rivalry

5 MARKET SIZE AND GROWTH FORECASTS (VALUE)

• 5.1 By Component
  • 5.1.1 Solutions
  • 5.1.2 Services
• 5.2 By Technology Type
  • 5.2.1 Robotic Process Automation (RPA)
  • 5.2.2 Machine Learning and Deep Learning
  • 5.2.3 Natural Language Processing and Chatbots
  • 5.2.4 Process and Task Mining
  • 5.2.5 Computer Vision and Biometrics
• 5.3 By Deployment Mode
  • 5.3.1 On-premise
  • 5.3.2 Cloud
  • 5.3.3 Hybrid
• 5.4 By End-User Enterprise Size
  • 5.4.1 Large Enterprises
  • 5.4.2 Small and Mid-Sized Enterprises (SMEs)
• 5.5 By End-User Industry
  • 5.5.1 BFSI
  • 5.5.2 Retail and e-Commerce
  • 5.5.3 IT and Telecom
  • 5.5.4 Manufacturing and Automotive
  • 5.5.5 Healthcare and Life Sciences
  • 5.5.6 Education
  • 5.5.7 Others End-user Industry
• 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 South Korea
    • 5.6.4.5 ASEAN-5
    • 5.6.4.6 Australia and New Zealand
    • 5.6.4.7 Rest of Asia Pacific
  • 5.6.5 Middle East and Africa
    • 5.6.5.1 Middle East
      • 5.6.5.1.1 United Arab Emirates
      • 5.6.5.1.2 Saudi Arabia
      • 5.6.5.1.3 Rest of Middle East
    • 5.6.5.2 Africa
      • 5.6.5.2.1 South Africa
      • 5.6.5.2.2 Nigeria
      • 5.6.5.2.3 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 for key companies, Products and Services, Recent Developments)
  • 6.4.1 ABBYY Solutions Ltd.
  • 6.4.2 akaBot (FPT Software)
  • 6.4.3 Alteryx Inc.
  • 6.4.4 Appian Corporation
  • 6.4.5 Automation Anywhere Inc.
  • 6.4.6 Blue Prism Ltd.
  • 6.4.7 Catalytic Inc.
  • 6.4.8 Celonis SE
  • 6.4.9 IBM Corporation
  • 6.4.10 Microsoft Corporation
  • 6.4.11 Mitsubishi Electric Corporation
  • 6.4.12 NICE Ltd.
  • 6.4.13 OneGlobe LLC
  • 6.4.14 Pegasystems Inc.
  • 6.4.15 Rocketbot SpA
  • 6.4.16 Salesforce Inc.
  • 6.4.17 Simple Fractal LLC
  • 6.4.18 SolveXia Pty Ltd.
  • 6.4.19 UiPath Inc.
  • 6.4.20 WorkFusion Inc.

7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK

• 7.1 White-space and Unmet-Need Assessment