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Generative AI in Automation Market Based on Technology (Computer Vision, Natural Language Processing (NLP), Reinforcement Learning, Deep Learning, and Others), Based on Application, Based on End User - Global Industry Outlook, Key Companies (SAP SE, IBM Corporation, Microsoft Corporation, and Others), Trends and Forecast 2024-2033

Published on : April-2024  Report Code : RC-898  Pages Count : 245  Report Format : PDF
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Market Overview

The Global Generative AI in Automation Market size is estimated to reach USD 1.5 billion in 2024 and is further anticipated to value USD 5.2 billion by 2033, at a CAGR of 14.8%.
 
Generative AI in Automation Market Growth Analysis

Generative AI in Automation is the process of using artificial intelligence to create content, data, or outputs according to existing information and learned patterns. Automation through generative AI is different than traditional automation as it generates a unique output that replicates human creativity or decision-making process. AI is extensively used in content creation to write articles, create music, or design graphics based on sample and training data. AI-powered platforms are capable of making decisions and producing outputs without human intervention as they can adapt to new situations, learn from feedback, and generate outputs that can be similar to those created by humans.

Generative AI in the automation market is experiencing rapid growth and transformation due to the development of deep generative AI techniques that revolutionize the decision-making process of each organization. Deep generative AI models allow for the creation of new content, simulate realistic scenarios, and optimize automation workflows. They are known for generating content across text, image, and video domains, identifying mistakes and patterns to smoothen process optimization, and providing personalized recommendations and predictive insights to improve decision-making. These technologies help reshape automation across many industries boosting productivity, efficiency, and innovation in the automation market.

Key Takeaways

  • Market size: The global generative AI in automation market size is expected to grow by 3.5 billion, at a CAGR of 14.8 % during the forecasted period of 2025 to 2033.
  • Market Definition: Generative AI in Automation uses the AI algorithm to create new content, and make decisions autonomously based on learned patterns and data inputs.
  • Technology Analysis: Computer Vision is projected to be the dominant force in the market based on technology capturing the largest revenue share of 36.5% in 2024.
  • Application Analysis: Robotic Process Automation (RPA) as an application is expected to witness significant growth with the highest revenue share of 43.2% throughout the forecast period.
  • End User Analysis: Automotive is forecasted to hold the largest market share of 46.2 % and dominate the generative AI in automation market based on end-users in 2024.
  • Regional Analysis: North America is anticipated to dominate the generative AI in automation market, capturing a revenue share of 41.2 % in 2024.

Use Cases

  • Image and Video Analysis: Generative AI is useful in design, advertising, and entertainment industries as it can generate realistic images and videos based on input parameters.
  • Virtual assistant: AI models are also capable of having conversational skills like chatbots and virtual assistants which understand natural language, engage in meaningful conversations, and provide automated assistance to users in customer service, sales, and support functions.
  • Content Generation: Content creation tasks like writing articles, product descriptions can be automated with the help of generative AI by generating text that is coherent, relevant, and tailored to specific audiences which saves time and resources for businesses.
  • Code Generation: Generative AI automates software development tasks by generating code snippets, improving developer productivity, accelerating the coding process, and also assisting in debugging and code optimization tasks.

Market Dynamic

Drivers

Use of Vast Data for Generative AI:
The successive use of automation is heavily dependent on a large amount of structured and unstructured data. Organizations are coming up with extensive data sets due to the increase in digital technologies and the growth of data sources. Generative AI empowers these organizations to identify patterns, create new content, and optimize automation processes, driving the growth of the automation market.

Advanced Automation Capabilities with Generative AI:
There is a shift in the process of automation due to generative AI's capability to generate data, simulate situations, and forecast results which fuel the growth of automation.

Growing Popularity of Process Automation:
Industries across various sectors from manufacturing and finance to healthcare and retail are employing automation as a strategic initiative to stay competitive and improve overall performance. These technologies play a crucial role in improving productivity, faster decision-making, reduced errors, and enhanced scalability.

Restraints

Transparency and Trust:
Deep learning AI models can be confusing, complex, and challenging to interpret, therefore it is difficult to understand and trust these systems. Interpretability and trust in generative AI outputs are the two main challenges that obstruct the growth of this market.

Data Security and Privacy Concerns:
Organizations must stick to data protection regulations and address concerns regarding unauthorized access or misuse of sensitive data. Generative AI models are primarily data-centric which could produce unethical outcomes if the training data contains errors or skewed representations.

Opportunities

Demand for Automation:
The increasing demand for using generative AI to automate content creation, refine resource allocation strategies, improve decision-making processes, and deliver according to customers, expanded the growth opportunities for the market. Organizations are using these technologies to drive efficiency enhancements and unlock new avenues for creativity which highlights the growth opportunities for generative AI in automation.

Adoption among different industries:
The increasing adoption of automation across many industries increases the demand for AI solutions capable of optimizing processes, streamlining workflows, and bolstering operational efficacy.

Trend

Integration of Generative AI with Reinforcement Learning and Pre-trained Models:
AI systems are ready to adapt and learn effectively in changing environments with limited data by integration of generative AI with reinforcement learning which improves the generalization and adaptability of automation systems.

Increase of trained generative AI models:
The automation process is increased due to the rise of trained generative AI models and platforms which allows businesses to use existing knowledge and increase the implementation of AI-driven automation solutions.

Research Scope and Analysis

By Technology

Computer Vision is likely to dominate the generative AI in the Automation market with a revenue share of 36.5% by the end of 2024 as it uses generative AI to understand and process visual information effectively. AI models with the help of computer vision algorithms allow machines to analyze images, videos, and other visual data thoroughly. It offers automation of tasks like object detection, image recognition, and image synthesis which is valuable across many sectors including autonomous vehicles, surveillance, quality control, and augmented reality. The visual content creation process can be automated by using computer vision technology which extracts actionable insights from visual data and makes real-time decisions based on visual inputs.
 
Generative AI in Automation Market Technology Share Analysis
 
They improve operational efficiency, strengthen security measures, and deliver innovative user experiences, therefore increasing the growth of generative AI within the automation market. Computer vision techniques like a variational auto-encoders are useful in reconstructing damaged or incomplete images, which is useful for tasks like restoring old photos or enhancing medical images. In addition, Conditional generative models are useful in generating realistic images from text descriptions, which is useful for many tasks, such as creating new artwork and visual content and generating realistic images for video games and movies.

By Application

Robotic Process Automation (RPA) is anticipated to dominate the generative AI in automation with a revenue share of 43.2% by the end of 2024. RPA can automate rule-based tasks by using software bots and its capabilities are increased by Generative AI using advanced machine learning techniques. RPA with the help of generative AI enables to generate quality content and improves decision-making and workflow management. Businesses use RPA to improve automation levels, operational efficiency, and customer experiences. RPA is used to automate tasks while generative AI is used to create new content and data.
 
The integration of RPA and AI provides a good opportunity for innovation, like conversational AI-powered customer service, analytics-driven decision-making, and the automation of knowledge work. Intelligence chatbots are expected to show notable growth during the forecasted period due to their numerous capabilities and applications. Combining generative AI with automation improves the capabilities of intelligent chatbots, powering them to deliver personalized responses, tackle intricate queries, and optimize customer interactions smoothly. These chatbots use the ability of generative AI to craft authentic and captivating conversations, providing users with an interactive and gratifying experience.

By End Users

Generative AI in the automation market is segmented into automotive, aerospace, electronics, consumer goods, and others based on end-users. Automotive is expected to dominate the market with the largest revenue share of 46.2% by the end of 2024, due to rising demand for autonomous vehicles, efficient production methods, and personalized driving experiences. Advanced driver assistance system is created using computer vision and deep learning which enhances car safety, object recognition, and driving capabilities, therefore driving the growth of automotive in this segment.

AI models offer the analysis of extensive large sensor data to enhance manufacturing efficiency and quality control measures, contributing significantly to process optimization. They help in the customization of in-car entertainment systems and deliver personalized recommendations with maintenance notifications, which improve the experience of car users. In the aerospace domain, generative AI is used to create digital twins, which are virtual models of aircraft and their subsystems which speed up the process of product development timelines, reduce the need for physical testing, and enable predictive maintenance.

The Generative AI in Automation Market Report is segmented based on the following:

By Technology

  • Computer Vision
  • Natural Language Processing (NLP)
  • Reinforcement Learning
  • Deep Learning
  • Others

By Application

  • Robotic Process Automation (RPA)
  • Process Optimization
  • Intelligent Chatbots
  • Predictive Maintenance
  • Quality Control and Anomaly Detection
  • Others

By End Users

  • Automotive
  • Aerospace
  • Electronics
  • Consumer Goods
  • Others

Regional Analysis

North America is expected to dominate the generative AI in automation market with the largest revenue share of 41.2 % by the end of 2024. This region is leading due to its advanced technological infrastructure, intense research & development activities, and the presence of leading AI companies, which contribute to the growth of the market in this region.
 
Generative AI in Automation Market Regional Analysis
 
Several major technology companies in this region are heavily invested in developing generative AI capabilities, using it for many purposes, including image manipulation, content creation, and design automation. In addition, collaboration among industry players, research institutions, & startups is essentially driving the growth of this market. The increasing demand for AI-generated content, the rising adoption of generative AI in various industries, and the emergence of fully autonomous generative AI solutions are driving the growth of the market in this region. Major technology hubs like Silicon Valley play an important role in driving investment and cultivating an innovative atmosphere, contributing to the growth of the automation market.
 
The presence of a developed automation landscape in the manufacturing, financial, and healthcare sectors of North America provides a favorable environment for the use of generative AI in streamlining operations and raising efficiency. After North America, the Asia Pacific region is anticipated to witness rapid growth in the market due to the development and adoption of generative AI solutions, fueled by robust economic growth, technological advancements, and increasing digitalization across industries.

By Region

North America
  • The U.S.
  • Canada
Europe
  • Germany
  • The U.K.
  • France
  • Italy
  • Russia
  • Spain
  • Benelux
  • Nordic
  • Rest of Europe
Asia-Pacific
  • China
  • Japan
  • South Korea
  • India
  • ANZ
  • ASEAN
  • Rest of Asia-Pacific
Latin America
  • Brazil
  • Mexico
  • Argentina
  • Colombia
  • Rest of Latin America
Middle East & Africa
  • Saudi Arabia
  • UAE
  • South Africa
  • Israel
  • Egypt
  • Rest of MEA

Competitive Landscape

Major market players provide various generative AI solutions offering automation, process enhancement, and informed decision-making. Companies like Microsoft, IBM, and Autodesk Inc. have made significant development in Generative AI research and development. Collaboration & partnerships between tech giants, startups, and industry players are common in the Generative AI in Automation market. These companies provide a diverse array of AI & machine learning solutions aimed at improving automation processes and elevating customer satisfaction. Companies offer comprehensive AI platforms, tools, & solutions that encompass generative AI capabilities, catering to a wide range of automation needs across industries.

Some of the prominent players in the global generative AI in automation market are:
  • SAP SE
  • IBM Corporation
  • Microsoft Corporation
  • Alphabet Inc.
  • Siemens AG
  • General Electric Company
  • Autodesk Inc.
  • NVIDIA Corporation
  • Cisco Systems Inc.
  • Oracle Corporation
  • Others

Recent Development

  • In March 2024, ServiceNow, a leading digital workflow company, expanded its leadership in generative AI through recent advancements by improving Now Assist GenAI functionalities, providing responsible and intelligent automation integrated within the ServiceNow platform.
  • In February 2024, Tungsten Automation, a trusted leader in Intelligent Automation software and the new identity of the Tungsten Automation brand launched, TotalAgility 8, which offers new AI enhancements that help organizations become more agile and accelerate their returns on investment faster.
  • In April 2023, PWC announced an investment of USD 1.0 billion into developing generative AI services to support clients who are trying to elevate their businesses by generating richer insights.
  • In July 2023, Infosys announced an investment of USD 2.0 billion to provide artificial intelligence (AI) and automation-led services.

Report Details

                                    Report Characteristics
Market Size (2024) USD 1.5 Bn
Forecast Value (2033) USD 5.2 Bn
CAGR (2023-2032) 41.2%
Historical Data 2018 – 2023
Forecast Data 2024 – 2033
Base Year 2023
Estimate Year 2024
Report Coverage Market Revenue Estimation, Market Dynamics, Competitive Landscape, Growth Factors and etc.
Segments Covered Based on Technology (Computer Vision, Natural Language Processing (NLP), Reinforcement Learning, Deep Learning, and Others), Based on Application (Robotic Process Automation (RPA), Process Optimization, Intelligent Chatbots, Predictive Maintenance, Quality Control and Anomaly Detection, and Others), Based on End-Users (Automotive, Aerospace, Electronics, Consumer Goods, and Others)
Regional Coverage North America – The US and Canada; Europe – Germany, The UK, France, Russia, Spain, Italy, Benelux, Nordic, & Rest of Europe; Asia- Pacific– China, Japan, South Korea, India, ANZ, ASEAN, Rest of APAC; Latin America – Brazil, Mexico, Argentina, Colombia, Rest of Latin America; Middle East & Africa – Saudi Arabia, UAE, South Africa, Turkey, Egypt, Israel, & Rest of MEA
Prominent Players SAP SE, IBM Corporation, Microsoft Corporation, Alphabet Inc., Siemens AG, General Electric Company, Autodesk Inc., NVIDIA Corporation, Cisco Systems Inc., Oracle Corporation, and Other Key Players
Purchase Options We have three licenses to opt for: Single User License (Limited to 1 user), Multi-User License (Up to 5 Users), and Corporate Use License (Unlimited User) along with free report customization equivalent to 0 analyst working days, 3 analysts working days and 5 analysts working days respectively.

 

Frequently Asked Questions

  • How big is the Global Generative AI in Automation Market?

    The Global Generative AI in Automation Market size is estimated to have a value of USD 1.5 billion in 2024 and is expected to reach USD 5.2 billion by the end of 2033.

  • Which region accounted for the largest Global Generative AI in Automation Market?

    North America is expected to be the largest market share for the Global Generative AI in Automation Market with a share of about 41.2% in 2024.

  • Who are the key players in the Global Generative AI in Automation Market?

    Some of the major key players in the Global Generative AI in Automation Market are SAP SE, IBM Corporation, Microsoft Corporation and many others.

  • What is the growth rate in the Global Generative AI in Automation Market?

    The market is growing at a CAGR of 14.8 percent over the forecasted period. SAP SE, IBM Corporation, Microsoft Corporation.

  • Contents

      1.Introduction
        1.1.Objectives of the Study
        1.2.Market Scope
        1.3.Market Definition and Scope
      2.Generative AI in Automation Market Overview
        2.1.Global Generative AI in Automation Market Overview by Type
        2.2.Global Generative AI in Automation Market Overview by Application
      3.Generative AI in Automation Market Dynamics, Opportunity, Regulations, and Trends Analysis
        3.1.Market Dynamics
          3.1.1.Generative AI in Automation Market Drivers
          3.1.2.Generative AI in Automation Market Opportunities
          3.1.3.Generative AI in Automation Market Restraints
          3.1.4.Generative AI in Automation Market Challenges
        3.2.Emerging Trend/Technology
        3.3.PESTLE Analysis
        3.4.PORTER'S Five Forces Analysis
        3.5.Technology Roadmap
        3.6.Opportunity Map Analysis
        3.7.Case Studies
        3.8.Opportunity Orbits
        3.9.Pricing Analysis
        3.10.Ecosystem Analysis
        3.11.Supply/Value Chain Analysis
        3.12.Covid-19 & Recession Impact Analysis
        3.13.Product/Brand Comparison
      4.Global Generative AI in Automation Market Value ((US$ Mn)), Share (%), and Growth Rate (%) Comparison by By Technology, 2017-2032
        4.1.Global Generative AI in Automation Market Analysis by By Technology: Introduction
        4.2.Market Size and Forecast by Region
        4.3.Computer Vision
        4.4.Natural Language Processing (NLP)
        4.5.Reinforcement Learning
        4.6.Deep Learning
        4.7.Others
      5.Global Generative AI in Automation Market Value ((US$ Mn)), Share (%), and Growth Rate (%) Comparison by By Application, 2017-2032
        5.1.Global Generative AI in Automation Market Analysis by By Application: Introduction
        5.2.Market Size and Forecast by Region
        5.3.Robotic Process Automation (RPA)
        5.4.Process Optimization
        5.5.Intelligent Chatbots
        5.6.Predictive Maintenance
        5.7.Quality Control and Anomaly Detection
        5.8.Others
      6.Global Generative AI in Automation Market Value ((US$ Mn)), Share (%), and Growth Rate (%) Comparison by By End Users, 2017-2032
        6.1.Global Generative AI in Automation Market Analysis by By End Users: Introduction
        6.2.Market Size and Forecast by Region
        6.3.Automotive
        6.4.Aerospace
        6.5.Electronics
        6.6.Consumer Goods
        6.7.Others
      10.Global Generative AI in Automation Market Value ((US$ Mn)), Share (%), and Growth Rate (%) Comparison by Region, 2017-2032
        10.1.North America
          10.1.1.North America Generative AI in Automation Market: Regional Analysis, 2017-2032
            10.1.1.1.The US
            10.1.1.2.Canada
        10.2.1.Europe
          10.2.1.Europe Generative AI in Automation Market: Regional Trend Analysis
            10.2.1.1.Germany
            10.2.1.2.France
            10.2.1.3.UK
            10.2.1.4.Russia
            10.2.1.5.Italy
            10.2.1.6.Spain
            10.2.1.7.Nordic
            10.2.1.8.Benelux
            10.2.1.9.Rest of Europe
        10.3.Asia-Pacific
          10.3.1.Asia-Pacific Generative AI in Automation Market: Regional Analysis, 2017-2032
            10.3.1.1.China
            10.3.1.2.Japan
            10.3.1.3.South Korea
            10.3.1.4.India
            10.3.1.5.ANZ
            10.3.1.6.ASEAN
            10.3.1.7.Rest of Asia-Pacifc
        10.4.Latin America
          10.4.1.Latin America Generative AI in Automation Market: Regional Analysis, 2017-2032
            10.4.1.1.Brazil
            10.4.1.2.Mexico
            10.4.1.3.Argentina
            10.4.1.4.Colombia
            10.4.1.5.Rest of Latin America
        10.5.Middle East and Africa
          10.5.1.Middle East and Africa Generative AI in Automation Market: Regional Analysis, 2017-2032
            10.5.1.1.Saudi Arabia
            10.5.1.2.UAE
            10.5.1.3.South Africa
            10.5.1.4.Israel
            10.5.1.5.Egypt
            10.5.1.6.Turkey
            10.5.1.7.Rest of MEA
      11.Global Generative AI in Automation Market Company Evaluation Matrix, Competitive Landscape, Market Share Analysis, and Company Profiles
        11.1.Market Share Analysis
        11.2.Company Profiles
          11.3.1.Company Overview
          11.3.2.Financial Highlights
          11.3.3.Product Portfolio
          11.3.4.SWOT Analysis
          11.3.5.Key Strategies and Developments
        11.4.SAP SE
          11.4.1.Company Overview
          11.4.2.Financial Highlights
          11.4.3.Product Portfolio
          11.4.4.SWOT Analysis
          11.4.5.Key Strategies and Developments
        11.5.IBM Corporation
          11.5.1.Company Overview
          11.5.2.Financial Highlights
          11.5.3.Product Portfolio
          11.5.4.SWOT Analysis
          11.5.5.Key Strategies and Developments
        11.6.Microsoft Corporation
          11.6.1.Company Overview
          11.6.2.Financial Highlights
          11.6.3.Product Portfolio
          11.6.4.SWOT Analysis
          11.6.5.Key Strategies and Developments
        11.7.Alphabet Inc.
          11.7.1.Company Overview
          11.7.2.Financial Highlights
          11.7.3.Product Portfolio
          11.7.4.SWOT Analysis
          11.7.5.Key Strategies and Developments
        11.8.Siemens AG
          11.8.1.Company Overview
          11.8.2.Financial Highlights
          11.8.3.Product Portfolio
          11.8.4.SWOT Analysis
          11.8.5.Key Strategies and Developments
        11.9.General Electric Company
          11.9.1.Company Overview
          11.9.2.Financial Highlights
          11.9.3.Product Portfolio
          11.9.4.SWOT Analysis
          11.9.5.Key Strategies and Developments
        11.10.Autodesk Inc.
          11.10.1.Company Overview
          11.10.2.Financial Highlights
          11.10.3.Product Portfolio
          11.10.4.SWOT Analysis
          11.10.5.Key Strategies and Developments
        11.11.NVIDIA Corporation
          11.11.1.Company Overview
          11.11.2.Financial Highlights
          11.11.3.Product Portfolio
          11.11.4.SWOT Analysis
          11.11.5.Key Strategies and Developments
        11.12.Cisco Systems Inc.
          11.12.1.Company Overview
          11.12.2.Financial Highlights
          11.12.3.Product Portfolio
          11.12.4.SWOT Analysis
          11.12.5.Key Strategies and Developments
        11.13.Oracle Corporation
          11.13.1.Company Overview
          11.13.2.Financial Highlights
          11.13.3.Product Portfolio
          11.13.4.SWOT Analysis
          11.13.5.Key Strategies and Developments
        11.14.Others
          11.14.1.Company Overview
          11.14.2.Financial Highlights
          11.14.3.Product Portfolio
          11.14.4.SWOT Analysis
          11.14.5.Key Strategies and Developments
      12.Assumptions and Acronyms
      13.Research Methodology
      14.Contact
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