AI 기반 자동화 시장 : 시장 예측 - 컴포넌트별, 전개 모드별, 기술별, 조직 규모별, 용도별, 최종 사용자별, 지역별 분석

According to Stratistics MRC, the Global AI-Enhanced Automation Market is accounted for $91.50 billion in 2025 and is expected to reach $368.07 billion by 2032 growing at a CAGR of 22.0% during the forecast period. AI-Enhanced Automation combines advanced artificial intelligence capabilities with conventional automation to create intelligent systems that can think, learn, and adapt. Instead of relying solely on predefined instructions, these systems analyze large volumes of data, identify trends, and make autonomous decisions in dynamic environments. By using technologies like machine learning and analytics, AI-driven automation improves productivity, minimizes errors, and optimizes processes across industries such as industrial production, banking, healthcare, and supply chains, ultimately enabling faster, smarter, and more resilient business operations.

Market Dynamics:

Driver:

Rise of agentic and autonomous systems

Organizations are increasingly deploying AI agents capable of independently executing tasks, optimizing workflows, and making contextual decisions with minimal human oversight. These systems improve operational efficiency by dynamically adapting to real-time data and changing business conditions. Advances in reinforcement learning, large language models, and orchestration platforms are expanding the scope of autonomous automation. Enterprises are leveraging intelligent agents for process optimization, customer engagement, and predictive decision-making. The ability of agentic systems to coordinate across multiple applications is transforming traditional automation architectures. As enterprises pursue scalable and resilient operations, demand for AI-driven autonomous solutions continues to rise.

Restraint:

Data privacy and sovereignty concerns

Automated systems rely heavily on large volumes of sensitive enterprise and consumer data to deliver accurate insights and decisions. Regulations such as GDPR, HIPAA, and regional data localization laws restrict how data can be collected, stored, and processed. Organizations operating across borders face complexities in complying with varying regulatory frameworks. The use of cloud-based AI platforms raises concerns about unauthorized access and cross-jurisdictional data transfer. Enterprises are increasingly cautious about deploying autonomous systems that lack transparent governance controls. These regulatory and compliance challenges can slow deployment and increase implementation costs.

Opportunity:

Sustainability and ESG optimization

Organizations are increasingly using AI-driven automation to monitor energy consumption, reduce emissions, and optimize resource utilization. Intelligent systems enable real-time tracking of ESG metrics across supply chains and operations. Automation platforms can identify inefficiencies and recommend corrective actions aligned with sustainability goals. Enterprises are leveraging predictive analytics to minimize waste and improve environmental compliance. Regulatory pressure and investor focus on ESG performance are accelerating technology adoption. As sustainability becomes a strategic priority, AI-enabled automation is emerging as a critical enabler.

Threat:

Sophisticated AI-powered cyberattacks

Malicious actors are using AI to exploit vulnerabilities, bypass security controls, and launch adaptive attacks. Automated environments with interconnected systems expand the potential attack surface. Compromised AI models can lead to manipulated decisions and operational disruptions. As automation becomes more autonomous, the impact of cyber breaches becomes more severe. Organizations must invest heavily in AI-driven cybersecurity and continuous monitoring frameworks. Failure to address these risks may undermine trust and slow market adoption.

Covid-19 Impact:

The COVID-19 pandemic accelerated the adoption of AI-enhanced automation across multiple industries. Lockdowns and workforce disruptions highlighted the need for resilient and autonomous operational models. Organizations rapidly deployed intelligent automation to maintain business continuity and manage remote operations. Supply chain volatility increased demand for AI-driven forecasting and adaptive planning tools. Enterprises also adopted automation to improve digital customer engagement and service delivery. The crisis accelerated cloud adoption and AI integration timelines. Post-pandemic strategies now emphasize scalable automation and reduced dependence on manual processes.

The software segment is expected to be the largest during the forecast period

The software segment is expected to account for the largest market share during the forecast period. Software platforms enable intelligent orchestration, analytics, and decision-making across enterprise workflows. The shift toward cloud-based AI solutions is driving widespread adoption of automation software. Continuous advancements in AI models and low-code platforms are expanding usability across industries. Software solutions offer scalability and flexibility compared to hardware-centric automation. Enterprises prefer modular platforms that integrate with existing IT ecosystems.

The healthcare & life sciences segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the healthcare & life sciences segment is predicted to witness the highest growth rate, due to its central role in enabling AI intelligence and autonomy. Automation software supports data ingestion, model training, and real-time execution of workflows. Organizations are increasingly investing in platforms that deliver end-to-end automation capabilities. Software updates and AI model improvements can be deployed rapidly without infrastructure changes. Integration with enterprise applications enhances operational visibility and control. Subscription-based pricing models further improve adoption rates.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share. Healthcare providers are adopting AI automation to streamline clinical workflows and administrative operations. Intelligent systems support diagnostics, patient scheduling, and treatment planning. Automation is improving data accuracy and reducing clinician workload. Life sciences companies are using AI-driven automation for drug discovery and clinical trial management. Regulatory compliance and data management are also being enhanced through intelligent platforms.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR, owing to increasing digital transformation initiatives. AI-enhanced automation enables faster decision-making and improved patient outcomes. Hospitals are deploying intelligent systems to optimize resource allocation and reduce operational costs. Life sciences firms benefit from automated analytics in research and manufacturing processes. The growing adoption of electronic health records supports automation deployment. Government initiatives promoting digital healthcare further accelerate adoption.

Key players in the market

Some of the key players in AI-Enhanced Automation Market include UiPath, WorkFusion, Automation Anywhere, Verint Systems, Microsoft, Kofax Inc., IBM, Infosys Ltd., SS&C Blue Prism, EdgeVerve, SAP, AntWorks, Pegasystems, Appian Corp., and NICE Ltd.

Key Developments:

In December 2025, UiPath announced it has joined the Veeva AI Partner Program. As part of the program, UiPath will help simplify and orchestrate the complex, manual, and highly regulated processes of application testing and validation. This partnership will deliver agentic, end-to-end workflows that will transform computer software assurance (CSA) testing and validation for quality management.

In November 2025, WorkFusion, the market standard for AI Agents for financial crime compliance (FCC), announced a strategic partnership with Allied Engineering Group (AEG), a leading provider of banking technology with operations across the Middle East, GCC, Africa, Turkey, Cyprus and Greece. Through this collaboration, AEG will serve as a reseller of WorkFusion's AI agents, including its flagship Evelyn, Tara and Evan offerings, enabling banks and financial institutions across the region to significantly reduce false positives in sanction screening, enhance accuracy in payments filtering, and accelerate compliance operations.

Components Covered:

• Software
• Services

Deployment Modes Covered:

• Cloud-Based
• On-Premises
• Hybrid

Technologies Covered:

• Machine Learning
• Natural Language Processing (NLP)
• Computer Vision
• Deep Learning
• Reinforcement Learning
• Process Mining
• Generative AI

Organization Sizes Covered:

• Large Enterprises
• Small & Medium Enterprises (SMEs)

Applications Covered:

• Business Process Automation
• Decision Intelligence
• Predictive Maintenance
• Customer Service Automation
• Fraud Detection & Risk Management
• Supply Chain Automation
• Quality Control & Compliance

End Users Covered:

• BFSI
• Manufacturing
• Healthcare & Life Sciences
• Retail & E-commerce
• IT & Telecom
• Automotive
• Energy & Utilities
• Government & Public Sector

Regions Covered:

• North America
  • US
  • Canada
  • Mexico
• Europe
  • Germany
  • UK
  • Italy
  • France
  • Spain
  • Rest of Europe
• Asia Pacific
  • Japan
  • China
  • India
  • Australia
  • New Zealand
  • South Korea
  • Rest of Asia Pacific
• South America
  • Argentina
  • Brazil
  • Chile
  • Rest of South America
• Middle East & Africa
  • Saudi Arabia
  • UAE
  • Qatar
  • South Africa
  • Rest of Middle East & Africa

What our report offers:

• Market share assessments for the regional and country-level segments
• Strategic recommendations for the new entrants
• Covers Market data for the years 2024, 2025, 2026, 2028, and 2032
• Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
• Strategic recommendations in key business segments based on the market estimations
• Competitive landscaping mapping the key common trends
• Company profiling with detailed strategies, financials, and recent developments
• Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

• Company Profiling
  • Comprehensive profiling of additional market players (up to 3)
  • SWOT Analysis of key players (up to 3)
• Regional Segmentation
  • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
• Competitive Benchmarking
  • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

• 2.1 Abstract
• 2.2 Stake Holders
• 2.3 Research Scope
• 2.4 Research Methodology
  • 2.4.1 Data Mining
  • 2.4.2 Data Analysis
  • 2.4.3 Data Validation
  • 2.4.4 Research Approach
• 2.5 Research Sources
  • 2.5.1 Primary Research Sources
  • 2.5.2 Secondary Research Sources
  • 2.5.3 Assumptions

3 Market Trend Analysis

• 3.1 Introduction
• 3.2 Drivers
• 3.3 Restraints
• 3.4 Opportunities
• 3.5 Threats
• 3.6 Technology Analysis
• 3.7 Application Analysis
• 3.8 End User Analysis
• 3.9 Emerging Markets
• 3.10 Impact of Covid-19

4 Porters Five Force Analysis

• 4.1 Bargaining power of suppliers
• 4.2 Bargaining power of buyers
• 4.3 Threat of substitutes
• 4.4 Threat of new entrants
• 4.5 Competitive rivalry

5 Global AI-Enhanced Automation Market, By Component

• 5.1 Introduction
• 5.2 Software
• 5.3 Services
  • 5.3.1 Consulting
  • 5.3.2 Integration & Deployment
  • 5.3.3 Support & Maintenance
  • 5.3.4 Managed Services

6 Global AI-Enhanced Automation Market, By Deployment Mode

• 6.1 Introduction
• 6.2 Cloud-Based
• 6.3 On-Premises
• 6.4 Hybrid

7 Global AI-Enhanced Automation Market, By Technology

• 7.1 Introduction
• 7.2 Machine Learning
• 7.3 Natural Language Processing (NLP)
• 7.4 Computer Vision
• 7.5 Deep Learning
• 7.6 Reinforcement Learning
• 7.7 Process Mining
• 7.8 Generative AI

8 Global AI-Enhanced Automation Market, By Organization Size

• 8.1 Introduction
• 8.2 Large Enterprises
• 8.3 Small & Medium Enterprises (SMEs)

9 Global AI-Enhanced Automation Market, By Application

• 9.1 Introduction
• 9.2 Business Process Automation
• 9.3 Decision Intelligence
• 9.4 Predictive Maintenance
• 9.5 Customer Service Automation
• 9.6 Fraud Detection & Risk Management
• 9.7 Supply Chain Automation
• 9.8 Quality Control & Compliance

10 Global AI-Enhanced Automation Market, By End User

• 10.1 Introduction
• 10.2 BFSI
• 10.3 Manufacturing
• 10.4 Healthcare & Life Sciences
• 10.5 Retail & E-commerce
• 10.6 IT & Telecom
• 10.7 Automotive
• 10.8 Energy & Utilities
• 10.9 Government & Public Sector

11 Global AI-Enhanced Automation Market, By Geography

• 11.1 Introduction
• 11.2 North America
  • 11.2.1 US
  • 11.2.2 Canada
  • 11.2.3 Mexico
• 11.3 Europe
  • 11.3.1 Germany
  • 11.3.2 UK
  • 11.3.3 Italy
  • 11.3.4 France
  • 11.3.5 Spain
  • 11.3.6 Rest of Europe
• 11.4 Asia Pacific
  • 11.4.1 Japan
  • 11.4.2 China
  • 11.4.3 India
  • 11.4.4 Australia
  • 11.4.5 New Zealand
  • 11.4.6 South Korea
  • 11.4.7 Rest of Asia Pacific
• 11.5 South America
  • 11.5.1 Argentina
  • 11.5.2 Brazil
  • 11.5.3 Chile
  • 11.5.4 Rest of South America
• 11.6 Middle East & Africa
  • 11.6.1 Saudi Arabia
  • 11.6.2 UAE
  • 11.6.3 Qatar
  • 11.6.4 South Africa
  • 11.6.5 Rest of Middle East & Africa

12 Key Developments

• 12.1 Agreements, Partnerships, Collaborations and Joint Ventures
• 12.2 Acquisitions & Mergers
• 12.3 New Product Launch
• 12.4 Expansions
• 12.5 Other Key Strategies

13 Company Profiling

• 13.1 UiPath
• 13.2 WorkFusion Inc.
• 13.3 Automation Anywhere
• 13.4 Verint Systems Inc.
• 13.5 Microsoft
• 13.6 Kofax Inc.
• 13.7 IBM
• 13.8 Infosys Ltd.
• 13.9 SS&C Blue Prism
• 13.10 EdgeVerve Systems Ltd.
• 13.11 SAP
• 13.12 AntWorks
• 13.13 Pegasystems
• 13.14 Appian Corp.
• 13.15 NICE Ltd.