자동화용 생성형 AI 시장 예측 : 솔루션 유형별, 조직 규모별, 전개 형태별, 기술별, 용도별, 최종 사용자별, 지역별 분석(-2030년)

According to Stratistics MRC, the Global Generative AI in Automation Market is accounted for $1409.5 million in 2024 and is expected to reach $3487.8 million by 2030 growing at a CAGR of 16.3% during the forecast period. Generative AI in automation refers to the use of artificial intelligence technologies that can create content, designs, or solutions autonomously by learning from existing data. This approach leverages advanced algorithms, such as deep learning and neural networks, to generate new outputs, including text, images, and even software code, based on patterns recognized in the training data. In automation, generative AI enhances processes by optimizing workflows, improving decision-making, and enabling the creation of personalized solutions, thereby increasing efficiency and productivity across various industries.

According to Gartner's predictions, Automation technologies like RPA, virtual assistants and artificial intelligence can reduce operational costs as much as 30% by 2024.

Market Dynamics:

Driver:

Growing demand for personalization

The growing demand for personalization in automation market increasingly expects tailored experiences, whether in customer service, product recommendations. Generative AI excels at analyzing vast datasets to generate personalized solutions, enhancing customer satisfaction and engagement. In sectors like e-commerce, marketing, and entertainment, AI-driven automation enables real-time customization at scale, improving operational efficiency while meeting individual preferences. This demand for personalized interactions pushes businesses to adopt generative AI technologies, driving growth and innovation in the automation market.

Restraint:

High implementation costs

High implementation costs in many businesses find it challenging to allocate sufficient budgets for integrating generative AI into their existing workflows, given the costs associated with infrastructure, software, and skilled personnel. Furthermore, the need for extensive customization and fine-tuning of models to fit specific organizational needs can increase these expenses. Companies may hesitate to invest heavily without guaranteed returns, leading to slower adoption rates and limiting the overall growth of the market.

Opportunity:

Expanding applications across industries

The expanding applications of generative AI across various industries for diverse uses, including personalized marketing, content creation, data analysis, and customer service automation. This versatility allows businesses to enhance operational efficiency and improve user engagement. Sectors like healthcare, finance, and media are leveraging generative AI for innovative solutions, driving demand and investment in AI technologies. As the technology evolves, it continues to create new opportunities, pushing the market forward at an impressive pace.

Threat:

Regulatory challenges

Regulatory challenges are introduced by complexities around compliance and risk management. As governments, particularly in the EU and US, move toward stringent regulations like the AI Act, businesses must adapt to various requirements, including risk assessments for high-impact AI systems. These regulations can slow product development, impose limitations on AI applications deemed unacceptable, and create uncertainties regarding liability and accountability, potentially discouraging investment and innovation, further hampering the growth of the market.

Covid-19 Impact

The COVID-19 pandemic accelerated the adoption of generative AI in the automation market as companies sought to maintain operations amid workforce disruptions. With the shift to remote work and the need for digital transformation, businesses turned to AI-driven automation for process optimization, cost reduction, and enhanced productivity. However, initial supply chain disruptions and economic uncertainty slowed investments in AI technologies. As recovery progressed, demand for automation surged, positioning generative AI as a critical tool for resilience and future growth.

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

The software segment is predicted to secure the largest market share throughout the forecast period, due to increase integrate generative AI capabilities into existing software applications, it enhances automation processes across various industries, including finance, healthcare, and manufacturing. This integration allows for improved decision-making, process optimization, and productivity gains. Major companies like Microsoft and IBM are focusing on developing AI-enabled software that can support automated workflows, such as intelligent chatbot and robotic process automation (RPA), fuelling the growth of the market.

The media and entertainment segment is expected to have the highest CAGR during the forecast period

The media and entertainment segment is projected to witness substantial growth during the projection period, due to enhanced content creation and personalization. Generative AI tools are being utilized to develop more engaging advertising campaigns and optimize pricing strategies, enabling companies to tailor offers to individual customer preferences. Additionally, the integration of these technologies is expected to continue propelling growth in this sector, as companies seek to leverage data for more effective marketing and content delivery.

Region with largest share:

During the projected timeframe, the Asia Pacific region is expected to hold the largest market share due to driven by advancements in deep learning algorithms, increased adoption of cloud-based solutions, and a rising demand for AI-generated content across sectors like media, e-commerce, and healthcare. Countries like China and India are leading in adoption, supported by government initiatives fostering AI innovation and investment. Additionally, young employees are playing a pivotal role in accelerating the integration of Generative AI in various industries.

Region with highest CAGR:

Over the forecasted timeframe, the North America region is anticipated to exhibit the highest CAGR, owing to advanced technological infrastructure and significant investments from leading companies like IBM, Microsoft, and Google. Companies are increasingly leveraging generative AI to enhance productivity, streamline operations, and improve customer experiences, with significant applications in automation, content generation, and predictive analytics. The region's focus on research and development and collaborations between tech companies and start-ups further fuels this growth.

Key players in the market

Some of the key players profiled in the Generative AI in Automation Market include OpenAI, Google DeepMind, Microsoft, International Business Machines Corporation (IBM), NVIDIA, Salesforce, Adobe, C3.ai, Hugging Face, DataRobot, UiPath, Appen, Twilio, Zoho, Botpress, SingularityNET, Algolia, PaddlePaddle and KAI Technologies.

Key Developments:

In April 2024, Microsoft and The Coca-Cola Company announced a five-year strategic partnership. This collaboration, with Coca-Cola committing $1.1 billion, focuses on enhancing cloud services and generative AI capabilities. The partnership aims to leverage Microsoft's Azure OpenAI Service to improve various business functions, from marketing to supply chain operations.

In January 2024, Microsoft entered a 10-year partnership with Vodafone. This deal aims to enhance customer experiences using Microsoft's generative AI, particularly for small and medium-sized enterprises (SMEs). Vodafone plans to invest $1.5 billion in cloud and AI services, and the partnership will also expand the M-Pesa platform to improve financial inclusion in Africa.

In January 2024, IBM signed a definitive agreement to acquire application modernization capabilities from Advanced. This move aims to bolster IBM Consulting's mainframe application and data modernization services.

Solution Types Covered:

• Software
• Services
• Other Solution Types

Organization Sizes Covered:

• Small and Medium Enterprises (SMEs)
• Large Enterprises
• Other Organization Sizes

Deployment Modes Covered:

• Cloud-based
• On-premises
• Hybrid
• Other Deployment Modes

Technologies Covered:

• Natural Language Processing (NLP)
• Machine Learning (ML)
• Computer Vision
• Deep Learning
• Reinforcement Learning
• Other Technologies

Applications Covered:

• Chatbot and Virtual Assistants
• Content Creation
• Image and Video Generation
• Data Generation and Augmentation
• Automated Reporting
• Code Generation
• Other Applications

End Users Covered:

• Healthcare
• Retail and E-commerce
• Manufacturing
• Telecommunications
• Media and Entertainment
• Automotive
• Other End Users

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 2022, 2023, 2024, 2026, and 2030
• 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 Generative AI in Automation Market, By Solution Type

• 5.1 Introduction
• 5.2 Software
• 5.3 Services
• 5.4 Other Solution Types

6 Global Generative AI in Automation Market, By Organization Size

• 6.1 Introduction
• 6.2 Small and Medium Enterprises (SMEs)
• 6.3 Large Enterprises
• 6.4 Other Organization Sizes

7 Global Generative AI in Automation Market, By Deployment Mode

• 7.1 Introduction
• 7.2 Cloud-based
• 7.3 On-premises
• 7.4 Hybrid
• 7.5 Other Deployment Modes

8 Global Generative AI in Automation Market, By Technology

• 8.1 Introduction
• 8.2 Natural Language Processing (NLP)
• 8.3 Machine Learning (ML)
• 8.4 Computer Vision
• 8.5 Deep Learning
• 8.6 Reinforcement Learning
• 8.7 Other Technologies

9 Global Generative AI in Automation Market, By Application

• 9.1 Introduction
• 9.2 Chatbots and Virtual Assistants
• 9.3 Content Creation
• 9.4 Image and Video Generation
• 9.5 Data Generation and Augmentation
• 9.6 Automated Reporting
• 9.7 Code Generation
• 9.8 Other Applications

10 Global Generative AI in Automation Market, By End User

• 10.1 Introduction
• 10.2 Healthcare
• 10.3 Retail and E-commerce
• 10.4 Manufacturing
• 10.5 Telecommunications
• 10.6 Media and Entertainment
• 10.7 Automotive
• 10.8 Other End Users

11 Global Generative AI in 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 OpenAI
• 13.2 Google DeepMind
• 13.3 Microsoft
• 13.4 International Business Machines Corporation (IBM)
• 13.5 NVIDIA
• 13.6 Salesforce
• 13.7 Adobe
• 13.8 C3.ai
• 13.9 Hugging Face
• 13.10 DataRobot
• 13.11 UiPath
• 13.12 Appen
• 13.13 Twilio
• 13.14 Zoho
• 13.15 Botpress
• 13.16 SingularityNET
• 13.17 Algolia
• 13.18 PaddlePaddle
• 13.19 KAI Technologies