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Global Generative AI Market Size, Share & Industry Trends Analysis Report By Component, By Technology, By End Use (Media & Entertainment, BFSI, IT & Telecommunication, Healthcare, Automotive & Transportation), By Regional Outlook and Forecast, 2022 - 2028

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    Report

  • 232 Pages
  • December 2022
  • Region: Global
  • Marqual IT Solutions Pvt. Ltd (KBV Research)
  • ID: 5723562
The Global Generative AI Market size is expected to reach $53.9 billion by 2028, rising at a market growth of 32.2% CAGR during the forecast period.

The term 'generative AI' refers to a new branch of machine learning that builds new things using neural networks, which are models based on the organization of animal brains. Traditional machine learning algorithms can only interpret the data that was provided to them by their human designers; they are not capable of producing new data on their own.



In contrast to conventional machine learning, generative AI may produce creative material, such as songs, artwork, and even complete words. People will be able to be more inventive, creative, and innovative owing to generative AI. It has the capacity to break down the boundaries of human imagination and produce new concepts that were previously unimaginable.

This can be done using a technique called generative design, where one commences with a set of guidelines or restrictions and then give it some time to work. The drawings it generates can then be viewed to help individuals either come up with a solution to the problem or learn fresh perspectives on it. New avenues for how people work, play, and create are emerging thanks to generative AI.

For consumers, companies, governments, and nonprofit groups, this field is very promising. Programs that enable machines to create content using elements like audio recordings, text, and graphics are known as generative artificial intelligence (AI). One of the most exciting developments in the field of AI over the past ten years, according to MIT, is generative AI.

COVID-19 Impact Analysis

The commercial operations and economies of numerous locations were impacted by the COVID-19 outbreak in 2020. Lower IT investment by firms, particularly small businesses, was noted as a result of the closure of commercial activities to stop the disease's spread. The COVID-19 pandemic has, however, been a big win for cloud-based software suppliers since most IT employees now manage various business processes from home. Over the course of the forecast period, these factors are anticipated to support the market for generative AI.

Market Growth Factors

Detecting Fraud Among Drivers

The use of synthetic data has the potential to solve the problems the banking sector is now experiencing, particularly with regard to data protection. In place of client data that cannot be shared owing to privacy issues, shareable data can be created using synthetic data. Additionally, artificial consumer data are perfect for training machine learning (ML) models that help banks assess whether and how much they can offer a client in the way of credit or a mortgage loan.

Management Of Risk

For banks to maintain an appropriate amount of risk exposure, identify potential risk areas, and take action to sustain profitability, a risk management plan must be established. Whenever liquidity, credit, operational, and other risks really aren't properly managed, banks could experience losses. Because of this advantage, generative AI is widely used nowadays, particularly in the BFSI industry.

Market Restraining Factor

Ethics Of Ai-Generated Content

People are frequently the target of propaganda, obscene content, and fraudulent videos produced by AI. Privacy and consent issues are brought up by this. Additionally, there is a real chance that once AI can produce content in a person's manner, with or without that person's consent, individuals will lose their jobs. Due to these generative AI limitations, businesses may be hesitant to use them, which would hinder the market's expansion.

Component Outlook

Based on the component, the generative AI market is classified into software and services. With the largest revenue share in 2021, the software sector led the generative AI market. In order to anticipate the following word from past word sequences or the following image from words describing prior images, the software makes use of sophisticated machine learning algorithms. The expansion of the software market can be ascribed to a number of variables, including an increase in fraud, an overestimation of skills, unexpected results, and increased data privacy concerns.



Technology Outlook

Based on the technology, the generative AI market is categorized into generative adversarial networks (GANs), transformers, variational auto-encoders, and diffusion networks. The generative AI market's diffusion network segment grew significantly in revenue in 2021. Image generation has become crucial for many industries, including BFSI, healthcare, automotive & transportation, media & entertainment, defense, and many others, in order to meet the growing demands of image synthesis because these sectors are equipped to offer high-value to enterprises, the government, and the general public.

End-use Outlook

On the basis of End-use, generative AI market is categorized into Media & entertainment, BFSI, IT & communications, healthcare, automotive & transportation, and others. The market for generative AI has experienced a promising growth rate in the healthcare sector in 2021. When activated by 3D printing, CRISPR, and other technologies, generative AI can be used to create organic molecules, prosthetic limbs, and other things from nothing. Additionally, early detection of possible malignancy can lead to better treatment strategies. In order to find treatments for COVID-19, IBM is now using this technology to study antimicrobial peptides (AMP).

Regional Outlook

Based on geography, the generative AI market is classified as North America, Europe, Asia Pacific, and LAMEA. The North American region generated the largest revenue share, thereby dominating the generative AI market in 2021 globally. This is because of things like rising medical care and pseudo-imagination, as well as rising banking frauds. The regional generative AI market is also projected to increase due to the existence of key market participants, including the U.S.-based Microsoft, Meta, and Google LLC, as well as sophisticated technology companies and the availability of specialists.

The Cardinal Matrix - Generative AI Market Competition Analysis


The major strategies followed by the market participants are Acquisition. Based on the Analysis presented in the Cardinal matrix; Google LLC and Microsoft Corporation are the forerunners in the Generative AI Market. Companies such as Amazon.com, Inc., Adobe, Inc., and IBM Corporation are some of the key innovators in Generative AI Market.

The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Google LLC, Amazon Web Services, Inc. (Amazon.com, Inc.), IBM Corporation, Microsoft Corporation, Adobe, Inc, MOSTLY AI Solutions MP GmbH, Synthesia Limited, Genie AI, Inc, Rephrase.ai, and De-Identification Ltd.

Recent Strategies Deployed in Generative AI Market

  • Nov-2022: Microsoft came into collaboration with NVIDIA, an American multinational technology company. This collaboration would aim to create one of the most powerful AI supercomputers, powered by Microsoft Azure's advance. Moreover, this collaboration opens the door to a supercomputer platform that benefits every enterprise on the Microsoft Azure platform.
  • Oct-2022: Adobe is introducing Generative AI, an AI-based technology. The product features Photoshop, Adobe Express, and Lightroom. Additionally, the latest technology would enable creators to give their idea to Artificial Intelligence and the machine would process certain images.
  • Oct-2022: Google completed the acquisition of Alter, an artificial intelligence (AI) avatar startup engaged in helping brands and creators express themselves. Through this acquisition, Google would improve both the quality and quantity of the content provided to consumers.
  • Jun-2022: Google added new features to its previously launched product Vertex. The addition of new features in Vertex AI would boost the deployment of machine learning models in organizations and democratize AI so more people can distribute models in production, driving business impact and continuous monitoring with AI.
  • Jun-2022: Amazon released CodeWhisperer, an AI pair programming tool that is capable of performing the entire function set only by pressing certain keynotes or based on the comment. The launched product works on Python, Java, and JavaScript as well as on numerous publicly available open-source codes and documents and its database of codes.
  • Dec-2021: Amazon Web Services, Inc. collaborated with Meta, an American multinational technology conglomerate to provide cloud services to AWS. Under this collaboration, both companies would work together to enhance the functioning of customers running PyTorch on AWS and boost how developers create, train, deploy and operate machine learning/artificial intelligence models.
  • Apr-2021: IBM took over Turbonomic, a company engaged in offering tools to manage application performance. With this move, IBM would enhance its footprint by offering enterprises AI-based services to manage their workloads and networks.
  • Apr-2021: Microsoft completed the acquisition of Nuance, an American multinational computer software technology corporation. This acquisition would integrate specializations and expertise to provide new AI and cloud abilities across healthcare and other areas.
  • Mar-2021: IBM launched Molecule Generation Experience (MolGX), a cloud-based AI-driven molecular design platform that itself invents new molecular structures. This newly launched product boosts the discovery of new materials by 10 to 100 times as well as finds materials from the property targets of a given product.
  • May-2020: Mircosoft took over Softomotive, a leading provider of robotic process automation. Under this acquisition, Microsoft would combine Softomotive’s desktop automation with the present Microsoft Power Automate abilities, at a uniquely low cost. Additionally, Microsoft would balance RPA and allow everyone to build bots to automate manual business processes.
  • Sep-2018: Microsoft took over Lobe, a start-up that makes it easier to build an A.I. model with its drag-and-drop interface. With this acquisition, Microsoft would create its own effort to design AI models easier as well for some time Lobe would operate as before.
  • Jul-2018: IBM Watson Health, a division of IBM Corporation, partnered with Guerbet, a manufacturer of contrast agents used in medical imaging. Through this partnership, the companies would use AI for the medical imagining of the liver. Additionally, both companies together would develop advanced clinical decision support solutions.

Scope of the Study

By Component

  • Software
  • Service

By Technology

  • Transformers
  • Generative Adversarial Networks (GANs)
  • Variational Auto-encoders
  • Diffusion Networks

By End-Use

  • Media & Entertainment
  • BFSI
  • IT & Telecommunication
  • Healthcare
  • Automotive & Transportation
  • Others

By Geography

  • North America
  • US
  • Canada
  • Mexico
  • Rest of North America
  • Europe
  • Germany
  • UK
  • France
  • Russia
  • Spain
  • Italy
  • Rest of Europe
  • Asia Pacific
  • China
  • Japan
  • India
  • South Korea
  • Singapore
  • Malaysia
  • Rest of Asia Pacific
  • LAMEA
  • Brazil
  • Argentina
  • UAE
  • Saudi Arabia
  • South Africa
  • Nigeria
  • Rest of LAMEA

Key Market Players

List of Companies Profiled in the Report:

  • Google LLC
  • Amazon Web Services, Inc. (Amazon.com, Inc.)
  • IBM Corporation
  • Microsoft Corporation
  • Adobe, Inc
  • MOSTLY AI Solutions MP GmbH
  • Synthesia Limited
  • Genie AI, Inc
  • Rephrase.ai
  • De-Identification Ltd

Unique Offerings

  • Exhaustive coverage
  • The highest number of market tables and figures
  • Subscription-based model available
  • Guaranteed best price
  • Assured post sales research support with 10% customization free

Table of Contents

Chapter 1. Market Scope & Methodology
1.1 Market Definition
1.2 Objectives
1.3 Market Scope
1.4 Segmentation
1.4.1 Global Generative AI Market, by Component
1.4.2 Global Generative AI Market, by Technology
1.4.3 Global Generative AI Market, by End-Use
1.4.4 Global Generative AI Market, by Geography
1.5 Methodology for the research

Chapter 2. Market Overview
2.1 Introduction
2.1.1 Overview
2.1.1.1 Market Composition & Scenario
2.2 Key Factors Impacting the Market
2.2.1 Market Drivers
2.2.2 Market Restraints

Chapter 3. Competition Analysis - Global
3.1 Cardinal Matrix
3.2 Recent Industry Wide Strategic Developments
3.2.1 Partnerships, Collaborations and Agreements
3.2.2 Product Launches and Product Expansions
3.2.3 Acquisition and Mergers
3.3 Top Winning Strategies
3.3.1 Key Leading Strategies: Percentage Distribution (2018-2022)

Chapter 4. Global Generative AI Market by Component
4.1 Global Software Market by Region
4.2 Global Service Market by Region

Chapter 5. Global Generative AI Market by Technology
5.1 Global Transformers Market by Region
5.2 Global Generative Adversarial Networks (GANs) Market by Region
5.3 Global Variational Auto-encoders Market by Region
5.4 Global Diffusion Networks Market by Region

Chapter 6. Global Generative AI Market by End-use
6.1 Global Media & Entertainment Market by Region
6.2 Global BFSI Market by Region
6.3 Global IT & Telecommunication Market by Region
6.4 Global Healthcare Market by Region
6.5 Global Automotive & Transportation Market by Region
6.6 Global Others Market by Region

Chapter 7. Global Generative AI Market by Region
7.1 North America Generative AI Market
7.1.1 North America Generative AI Market by Component
7.1.1.1 North America Software Market by Country
7.1.1.2 North America Service Market by Country
7.1.2 North America Generative AI Market by Technology
7.1.2.1 North America Transformers Market by Country
7.1.2.2 North America Generative Adversarial Networks (GANs) Market by Country
7.1.2.3 North America Variational Auto-encoders Market by Country
7.1.2.4 North America Diffusion Networks Market by Country
7.1.3 North America Generative AI Market by End-use
7.1.3.1 North America Media & Entertainment Market by Country
7.1.3.2 North America BFSI Market by Country
7.1.3.3 North America IT & Telecommunication Market by Country
7.1.3.4 North America Healthcare Market by Country
7.1.3.5 North America Automotive & Transportation Market by Country
7.1.3.6 North America Others Market by Country
7.1.4 North America Generative AI Market by Country
7.1.4.1 US Generative AI Market
7.1.4.1.1 US Generative AI Market by Component
7.1.4.1.2 US Generative AI Market by Technology
7.1.4.1.3 US Generative AI Market by End-use
7.1.4.2 Canada Generative AI Market
7.1.4.2.1 Canada Generative AI Market by Component
7.1.4.2.2 Canada Generative AI Market by Technology
7.1.4.2.3 Canada Generative AI Market by End-use
7.1.4.3 Mexico Generative AI Market
7.1.4.3.1 Mexico Generative AI Market by Component
7.1.4.3.2 Mexico Generative AI Market by Technology
7.1.4.3.3 Mexico Generative AI Market by End-use
7.1.4.4 Rest of North America Generative AI Market
7.1.4.4.1 Rest of North America Generative AI Market by Component
7.1.4.4.2 Rest of North America Generative AI Market by Technology
7.1.4.4.3 Rest of North America Generative AI Market by End-use
7.2 Europe Generative AI Market
7.2.1 Europe Generative AI Market by Component
7.2.1.1 Europe Software Market by Country
7.2.1.2 Europe Service Market by Country
7.2.2 Europe Generative AI Market by Technology
7.2.2.1 Europe Transformers Market by Country
7.2.2.2 Europe Generative Adversarial Networks (GANs) Market by Country
7.2.2.3 Europe Variational Auto-encoders Market by Country
7.2.2.4 Europe Diffusion Networks Market by Country
7.2.3 Europe Generative AI Market by End-use
7.2.3.1 Europe Media & Entertainment Market by Country
7.2.3.2 Europe BFSI Market by Country
7.2.3.3 Europe IT & Telecommunication Market by Country
7.2.3.4 Europe Healthcare Market by Country
7.2.3.5 Europe Automotive & Transportation Market by Country
7.2.3.6 Europe Others Market by Country
7.2.4 Europe Generative AI Market by Country
7.2.4.1 Germany Generative AI Market
7.2.4.1.1 Germany Generative AI Market by Component
7.2.4.1.2 Germany Generative AI Market by Technology
7.2.4.1.3 Germany Generative AI Market by End-use
7.2.4.2 UK Generative AI Market
7.2.4.2.1 UK Generative AI Market by Component
7.2.4.2.2 UK Generative AI Market by Technology
7.2.4.2.3 UK Generative AI Market by End-use
7.2.4.3 France Generative AI Market
7.2.4.3.1 France Generative AI Market by Component
7.2.4.3.2 France Generative AI Market by Technology
7.2.4.3.3 France Generative AI Market by End-use
7.2.4.4 Russia Generative AI Market
7.2.4.4.1 Russia Generative AI Market by Component
7.2.4.4.2 Russia Generative AI Market by Technology
7.2.4.4.3 Russia Generative AI Market by End-use
7.2.4.5 Spain Generative AI Market
7.2.4.5.1 Spain Generative AI Market by Component
7.2.4.5.2 Spain Generative AI Market by Technology
7.2.4.5.3 Spain Generative AI Market by End-use
7.2.4.6 Italy Generative AI Market
7.2.4.6.1 Italy Generative AI Market by Component
7.2.4.6.2 Italy Generative AI Market by Technology
7.2.4.6.3 Italy Generative AI Market by End-use
7.2.4.7 Rest of Europe Generative AI Market
7.2.4.7.1 Rest of Europe Generative AI Market by Component
7.2.4.7.2 Rest of Europe Generative AI Market by Technology
7.2.4.7.3 Rest of Europe Generative AI Market by End-use
7.3 Asia Pacific Generative AI Market
7.3.1 Asia Pacific Generative AI Market by Component
7.3.1.1 Asia Pacific Software Market by Country
7.3.1.2 Asia Pacific Service Market by Country
7.3.2 Asia Pacific Generative AI Market by Technology
7.3.2.1 Asia Pacific Transformers Market by Country
7.3.2.2 Asia Pacific Generative Adversarial Networks (GANs) Market by Country
7.3.2.3 Asia Pacific Variational Auto-encoders Market by Country
7.3.2.4 Asia Pacific Diffusion Networks Market by Country
7.3.3 Asia Pacific Generative AI Market by End-use
7.3.3.1 Asia Pacific Media & Entertainment Market by Country
7.3.3.2 Asia Pacific BFSI Market by Country
7.3.3.3 Asia Pacific IT & Telecommunication Market by Country
7.3.3.4 Asia Pacific Healthcare Market by Country
7.3.3.5 Asia Pacific Automotive & Transportation Market by Country
7.3.3.6 Asia Pacific Others Market by Country
7.3.4 Asia Pacific Generative AI Market by Country
7.3.4.1 China Generative AI Market
7.3.4.1.1 China Generative AI Market by Component
7.3.4.1.2 China Generative AI Market by Technology
7.3.4.1.3 China Generative AI Market by End-use
7.3.4.2 Japan Generative AI Market
7.3.4.2.1 Japan Generative AI Market by Component
7.3.4.2.2 Japan Generative AI Market by Technology
7.3.4.2.3 Japan Generative AI Market by End-use
7.3.4.3 India Generative AI Market
7.3.4.3.1 India Generative AI Market by Component
7.3.4.3.2 India Generative AI Market by Technology
7.3.4.3.3 India Generative AI Market by End-use
7.3.4.4 South Korea Generative AI Market
7.3.4.4.1 South Korea Generative AI Market by Component
7.3.4.4.2 South Korea Generative AI Market by Technology
7.3.4.4.3 South Korea Generative AI Market by End-use
7.3.4.5 Singapore Generative AI Market
7.3.4.5.1 Singapore Generative AI Market by Component
7.3.4.5.2 Singapore Generative AI Market by Technology
7.3.4.5.3 Singapore Generative AI Market by End-use
7.3.4.6 Malaysia Generative AI Market
7.3.4.6.1 Malaysia Generative AI Market by Component
7.3.4.6.2 Malaysia Generative AI Market by Technology
7.3.4.6.3 Malaysia Generative AI Market by End-use
7.3.4.7 Rest of Asia Pacific Generative AI Market
7.3.4.7.1 Rest of Asia Pacific Generative AI Market by Component
7.3.4.7.2 Rest of Asia Pacific Generative AI Market by Technology
7.3.4.7.3 Rest of Asia Pacific Generative AI Market by End-use
7.4 LAMEA Generative AI Market
7.4.1 LAMEA Generative AI Market by Component
7.4.1.1 LAMEA Software Market by Country
7.4.1.2 LAMEA Service Market by Country
7.4.2 LAMEA Generative AI Market by Technology
7.4.2.1 LAMEA Transformers Market by Country
7.4.2.2 LAMEA Generative Adversarial Networks (GANs) Market by Country
7.4.2.3 LAMEA Variational Auto-encoders Market by Country
7.4.2.4 LAMEA Diffusion Networks Market by Country
7.4.3 LAMEA Generative AI Market by End-use
7.4.3.1 LAMEA Media & Entertainment Market by Country
7.4.3.2 LAMEA BFSI Market by Country
7.4.3.3 LAMEA IT & Telecommunication Market by Country
7.4.3.4 LAMEA Healthcare Market by Country
7.4.3.5 LAMEA Automotive & Transportation Market by Country
7.4.3.6 LAMEA Others Market by Country
7.4.4 LAMEA Generative AI Market by Country
7.4.4.1 Brazil Generative AI Market
7.4.4.1.1 Brazil Generative AI Market by Component
7.4.4.1.2 Brazil Generative AI Market by Technology
7.4.4.1.3 Brazil Generative AI Market by End-use
7.4.4.2 Argentina Generative AI Market
7.4.4.2.1 Argentina Generative AI Market by Component
7.4.4.2.2 Argentina Generative AI Market by Technology
7.4.4.2.3 Argentina Generative AI Market by End-use
7.4.4.3 UAE Generative AI Market
7.4.4.3.1 UAE Generative AI Market by Component
7.4.4.3.2 UAE Generative AI Market by Technology
7.4.4.3.3 UAE Generative AI Market by End-use
7.4.4.4 Saudi Arabia Generative AI Market
7.4.4.4.1 Saudi Arabia Generative AI Market by Component
7.4.4.4.2 Saudi Arabia Generative AI Market by Technology
7.4.4.4.3 Saudi Arabia Generative AI Market by End-use
7.4.4.5 South Africa Generative AI Market
7.4.4.5.1 South Africa Generative AI Market by Component
7.4.4.5.2 South Africa Generative AI Market by Technology
7.4.4.5.3 South Africa Generative AI Market by End-use
7.4.4.6 Nigeria Generative AI Market
7.4.4.6.1 Nigeria Generative AI Market by Component
7.4.4.6.2 Nigeria Generative AI Market by Technology
7.4.4.6.3 Nigeria Generative AI Market by End-use
7.4.4.7 Rest of LAMEA Generative AI Market
7.4.4.7.1 Rest of LAMEA Generative AI Market by Component
7.4.4.7.2 Rest of LAMEA Generative AI Market by Technology
7.4.4.7.3 Rest of LAMEA Generative AI Market by End-use

Chapter 8. Company Profiles
8.1 Google LLC
8.1.1 Company Overview
8.1.2 Financial Analysis
8.1.3 Segmental and Regional Analysis
8.1.4 Research & Development Expense
8.1.5 Recent strategies and developments:
8.1.5.1 Product Launches and Product Expansions:
8.1.5.2 Acquisition and Mergers:
8.1.6 SWOT Analysis
8.2 Amazon Web Services, Inc. (Amazon.com, Inc.)
8.2.1 Company Overview
8.2.2 Financial Analysis
8.2.3 Segmental Analysis
8.2.4 Recent strategies and developments:
8.2.4.1 Product Launches and Product Expansions:
8.2.4.2 Partnerships, Collaborations & Agreements
8.2.5 SWOT Analysis
8.3 IBM Corporation
8.3.1 Company Overview
8.3.2 Financial Analysis
8.3.3 Regional & Segmental Analysis
8.3.4 Research & Development Expenses
8.3.5 Recent strategies and developments:
8.3.5.1 Partnerships, Collaborations, and Agreements:
8.3.5.2 Product Launches and Product Expansions:
8.3.5.3 Acquisition and Mergers:
8.3.6 SWOT Analysis
8.4 Microsoft Corporation
8.4.1 Company Overview
8.4.2 Financial Analysis
8.4.3 Segmental and Regional Analysis
8.4.4 Research & Development Expenses
8.4.5 Recent strategies and developments:
8.4.5.1 Partnerships, Collaborations, and Agreements:
8.4.5.2 Acquisition and Mergers:
8.4.6 SWOT Analysis
8.5 Adobe, Inc.
8.5.1 Company Overview
8.5.2 Financial Analysis
8.5.3 Segmental and Regional Analysis
8.5.4 Research & Development Expense
8.5.5 Recent strategies and developments:
8.5.5.1 Product Launches and Product Expansions:
8.6 MOSTLY AI Solutions MP GmbH
8.6.1 Company Overview
8.7 Synthesia Limited
8.7.1 Company Overview
8.8 Genie AI, Inc.
8.8.1 Company Overview
8.9 Rephrase.ai
8.9.1 Company Overview
8.10. De-Identification Ltd.
8.10.1 Company Overview

Companies Mentioned

  • Google LLC
  • Amazon Web Services, Inc. (Amazon.com, Inc.)
  • IBM Corporation
  • Microsoft Corporation
  • Adobe, Inc
  • MOSTLY AI Solutions MP GmbH
  • Synthesia Limited
  • Genie AI, Inc
  • Rephrase.ai
  • De-Identification Ltd

Methodology

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