Generative Ai Market

Generative AI Market Overview 2023:

The global Generative AI market size was USD 28.7 billion in 2022 and is expected to register a CAGR of 47 % during the forecast period. The demand for creating a virtual world and the increasing use of technologies such as super-resolution, text-to-image conversion, and text-to-video conversion are the key factors fueling the growth of the generative AI market. Additionally, the increasing need to modernize workflow systems and processes across various industries is also expected to drive the growth of this market during the forecast period.

Generative AI is a prominent field of artificial intelligence that focuses on creating or generating novel content, including images, text, music, and videos. This approach involves training machine learning models to recognize and learn patterns in existing data to produce new and unique content. Generative AI techniques typically employ deep learning algorithms, such as Generative Adversarial Networks (GANs) and variational auto-encoders (VAEs), to generate content that closely resembles input data. These models acquire knowledge from the underlying patterns and structures of the training data and create new content based on the extrapolation of information.

Generative artificial intelligence (AI) has emerged as a powerful tool for enhancing various areas of industry. Through the use of unsupervised learning algorithms, generative AI has been applied in detecting spam, compressing images, and pre-processing data, such as reducing noise in visual data to improve picture quality. Additionally, supervised learning algorithms have been employed for medical imaging and image classification.

Generative AI has proven to be a valuable resource for organizations seeking to save time and money, increase efficiency, and enhance generated content quality. It has wide-ranging applications in industries such as BFSI, healthcare, automotive and transportation, IT and telecommunications, as well as media and entertainment. generative AI’s potential to foster innovation and solve complex problems has made it a vital technology for the modern business landscape.

However, Generative AI services are costly. In addition, it requires a vast amount of data to train effectively which can raise privacy concerns. These factors can hamper the overall market growth during the forecast period.

Graphical Overview:

Key Takeaways:

Growing Demand to Create a Virtual World:

Generative AI is a commonly used tool among developers of virtual reality (VR) games and worlds. With its ability to create immersive and exclusive game environments, it has become an invaluable asset in the development of VR games and training simulations. The implementation of generative AI to augment human AI with a workforce is the first practical application of AI in businesses, which is driving global market growth.

Data Breaches and Unauthorized Leakage of Sensitive Information:

The global generative AI market revenue is expected to fall during the forecast period due to potential risks associated with data breaches and unauthorized leakage of sensitive information. These concerns have a direct impact on the confidentiality, integrity, and availability of the data, which is crucial for the smooth operation of the business. This may result in financial losses, loss of customers' trust, and damage to the business's reputation in the market.

Market Opportunities:

Generative AI technology offers an opportunity to create fresh and innovative content, including images, videos, and text, for various purposes such as marketing, entertainment, and education. This technology helps product design companies by generating designs that help businesses create new and more appealing products that meet the needs of their customers. Furthermore, generative AI contributes to healthcare technologies by creating opportunities to identify new drugs, design treatments for curing diseases, and predict the effectiveness of new treatments.

Component Outlook:

The generative AI market is segmented into two components, namely software and services. The software segment is expected to account for largest revenue share during the forecast period owing to factors such as increasing number of fraudulent activities, overestimation of capabilities, unexpected outcomes, and rising concerns over data privacy. With robust machine learning models, generative AI software is expected to play a significant role in various sectors such as fashion, entertainment, transportation, and other industries.

Technology Outlook:

Based on technology, the Generative Adversarial Networks segment is expected to register robust revenue CAGR over the forecast period. This can be attributed to GANs' capabilities in generating highly realistic and diverse content. GANs function through a competitive framework where a generator network produces synthetic data, and a discriminator network evaluates its authenticity. GANs have demonstrated unparalleled success in tasks such as image and video synthesis, natural language generation, and creative content creation through continuous iterations and improvements.

By End Use Outlook:

Among the end users, the healthcare segment is expected to account for a significantly larger revenue share during the forecast period due to factors such as rising adoption of automation and advanced AI techniques in the healthcare sector, high usage of generative AI tools for medical imaging and diagnostics, personalized medicine, drug discovery and development, remote monitoring, patient engagement and enhancing operational efficiency.

Regional Outlook: 

North America is expected to account for the largest revenue share during the forecast period owing to rapid technological advancements, high adoption of advanced techniques including generative AI across various domains, presence of extensive research and development endeavors, and increasing investments in AI research. In addition, growing demand for personalized content, rapid proliferation of digital devices, social media platforms, and IoT devices, and rising investments in R&D activities are expected to drive North America market growth during the forecast period.

Asia-Pacific market is expected to register rapid revenue CAGR over the forecast period. This growth can be attributed to growing adoption of AI applications across various sectors, rising awareness about importance of generative AI, rapidly digitizing businesses, and ongoing research on exploring applications of generative AI across lesser known fields.

Report Coverage: 

Competitive Landscape:

The global Generative AI market is extremely competitive, comprising several regional and global level key players. Leading key players are focused on adopting various strategic alliances like mergers and acquisitions, partnerships, joint ventures, collaborations, and product launches to maintain their global position and enhance their product offerings. They are also focused on innovation, and scalability, adapting to evolving technology trends and consumer needs.

Some Leading Market Companies Listed in the Report:

• Microsoft Corporation
• D-ID, Genie AI Ltd.
• IBM Corporation
• Rephrase.ai
• Synthesia
• Adobe
• MOSTLY AI Inc
• Amazon Web Services, Inc.
• Google LLC
• Accenture
• Salesforce
  
  

Generative AI Industry Recent Developments:

• In June 2023, Salesforce launched two major generative artificial intelligence products, Commerce GPT and Marketing GPT, for commerce experience and customized consumers.
• In June 2023, Microsoft and Accenture collaborated to help other businesses transform their operations with the help of generative AI that is accelerated by the cloud.
  
  

The global Generative AI Market has been segmented based on Component, Model, Technology, Application, End Use, and Region:

By Component:

• Software
• Services
  
  

By Model:

• Large Language Models
• Image and video Generative Models
• Multi-modal Generative Models
• Others
  
  

By Technology:

• Generative Adversarial Networks (GANs)
• Transformer, Variational Autoencoder (VAE),
• Diffusion Networks
• Retrieval Augmented Generation
  
  

By Application:

• Computer Vision
• NLP
• Robotics and Automation
• Content Generation
• Chatbots & Intelligent Virtual Assistants
• Predictive Analytics
• Others
  
  

By End-users:

• Media and Entertainment
• BFSI
• IT and Telecom
• Healthcare
• Automotive and Transportation
• Others
  
  

By Region:

• North America
  • United States
  • Canada
• Europe
  • Germany
  • France
  • UK
  • Italy
  • Russia
  • Nordic Countries
• Asia Pacific
  • China
  • Japan
  • South Korea
  • Southeast Asia
  • India
  • Australia
  • Rest of Asia
• Latin America
  • Mexico
  • Brazil
  • Rest of Latin America
• Middle East & Africa
  • Turkey
  • Saudi Arabia
  • UAE
  • Rest of MEA

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