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Generative AI Market
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Generative AI Market Size & Share Analysis - Trends, Drivers, Competitive Landscape, and Forecasts (2024-2030)

Get a Comprehensive Overview of the Generative AI Market Report Prepared by P&S Intelligence, Segmented by Component, Application, End User, Technology, Model, and Geographic Regions. This Report Provides Insights From 2017 to 2030.

  • Published: March 2024
  • Pages: 340
  • Report Code: 12927
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Generative AI Market Data

Market Statistics

Study Period 2017 - 2030
2023 Market SizeUSD 12.0 Billion
2024 Market SizeUSD 15.6 Billion
2030 ForecastUSD 81.1 Billion
Growth Rate(CAGR) 31.6%
Largest RegionNorth America
Fastest Growing RegionAsia Pacific
Nature of the Market Consolidated
Largest Application NLP

Growth Forecast

Generative AI Market Size Analysis

Key Players

Generative AI Market Key Players

Key Report Highlights

  • Value Chain Analysis
  • Regulatory Landscape
  • Recent Strategical Developments
  • Key Stakeholders
  • Technology Roadmap
  • Future Opportunities
  • Market Indicators
  • Competitive Analysis

Explore the market potential with our data-driven report

The generative AI market had a size of USD 12 billion in 2023, which is expected to grow to USD 81.1 billion in 2030, advancing at a CAGR of 31.6% throughout the forecast period (2024–2030). This market is thriving because this technology has the potential to change the whole industry by providing new opportunities for innovation and automation.

Gen-AI is a set of algorithms that can generate realistic content by using training data, such as text, audio, and images. For instance, ChatGPT is trained on large volumes of text for summary extraction, sentimental monitoring, and answering questions. The main goal of these generative adversarial networks (GANs) is to create new information that is identifiable to the given data sets. Unlike traditional AI models, these new models use deep learning to generate the data samples. These models are multimodal, which means they can handle more than two processes simultaneously. Using these models, the interactions between machines and humans have improved with the help of NLP.

Many organizations are creating chatbot-based applications similar to ChatGPT and Bard (now Gemini), which take input from the user and generate text as output. Applications like these are helping many to resolve their issue or inquiries. These AI models have the potential to boost the work output by approximately 40%, which can lead many industries to significant gains. They can solve the challenging problems that the world is facing, such as traffic congestion, by analyzing traffic with the help of a camera or sensors that are installed in vehicles and providing route recommendations.

Generative AI Market Trends and Drivers

Rapid Growth of Large Language Models (LLMs)

  • One of the main factors that is helping this gen-AI market grow is the existence of large language models, because of their exceptional ability to create, manipulate, and understand natural language.
  • Language computational tasks are being reshaped by LLMs, such as the open-AI GPT series, which are now crucial parts of the various applications across industries.
  • LLMs display in-depth comprehension of grammar, semantics, and context, which allows them to create logical as well as appropriately suited text.
  • Precise and fluent language is important in applications including chatbots, language translators, and summary generation, where LLMs play an important role.
  • Due to their outstanding adaptability and versatility, LLMs can be utilized in various situations and programs. These models can be modified to meet specific needs and requirements that involve producing creative writing, codes, and documents.
  • Their boundaries are constantly being pushed by the continuous efforts of scientists and software engineers, by which their performance, ability, and effectiveness are being improved.
  • The techniques used on large language models to enhance their performance are autonomous learning, multi-modal learning, and few-shot learning, which allow them to accept any complex challenge.

Development of Artificial Intelligence and Deep Learning

  • This market is driven by the rapid evolution of AI and deep learning, which is reshaping the abilities of gen-AI applications. The limits of creating, altering, and comprehending the data are continuously being improved with the help of innovations in AI.
  • One of the primary drivers for the market is the advancements in deep neural networks, which were introduced by Ian Goodfellow and his co-worker in 2014.
  • Using a dataset of real samples as their foundation, a pair of neural networks that are generators and discriminators are trained parallelly to produce real data such as images and audio.
  • This method of generative modeling is helping significantly advance video creation, image processing, and many other creative activities, which is driving interest and high investment in this market.
  • The rise in the popularity of AI shows an evolutionary shift that is happening at speed and has not been witnessed in any prior revolutions. Although, there is no doubt that technological innovations, such as the internet of things and , have also brought evolution; still, they have not progressed as fast as AI.
  • The concept of deep learning, which is an AI algorithmic technique, can allow the system to identify patterns and sequences present in the data, by which its accuracy can be enhanced over time.
  • Neural networks are taking the place of conventional models because of the advanced computing technologies that are contributing to the revolution of AI.

Risks Associated with Theft of Sensitive Information and Data Breaches

  • The risk of data breaches and the chances of sensitive information being stolen is the most-concerning issue in this market. This is because, for learning purposes and to generate data, sometimes, AI models need to access some personal information or crucial data.
  • Unauthenticated usage of personal information is one of the main potential hazards associated with data breaches in the market. Criminals can easily steal the data and use it for various frauds and misdoings, such as financial fraud and violation of privacy.
  • Organizations that outsource AI projects have the highest possibility of running into such problems because most contractors handle data from different locations.
  • According to security organizations, companies that outsource data account for 63% of data breaches.
  • In addition, these AI generative models use images, audio, and videos to create content, which is raising concerns about the generation of misleading data. In the wrong hands, AI has the potential to produce deepfakes, which can spread false information and damage the reputation of individuals and organizations.

Segmentation Analysis

Generative AI Component Insights

  • Software held the larger revenue share, of around 55%, in the market in 2023.
  • Software is the foundation of this market, providing the algorithms, frameworks, and tools that are necessary for generative AI applications.
  • These software components are scalable and adaptable, due to which organizations can opt for them to fulfill their specific requirements. Software tools allow customers to take advantage of new AI technologies and also open fresh opportunities for creativity, such as creating new content and enhancing designs.
  • The functionalities of software components are being enhanced continuously, which includes the improvement of algorithmic techniques and parallel computation.
  • AI software is continuing to advance due to the incorporation of machine learning. It can also play a crucial role in large-scale and critical industries, such as travel, fashion, and entertainment.
  • For instance, Adidas is also using this software to design customized shoes.

Generative AI Market Segmentation Analysis

During the study, two components are covered in the report:

  • Software (Larger Category)
  • Services (Faster-Growing Category)

Application Insights

  • The natural language processing category has captured the largest market share, and it is expected to grow at a significant CAGR, of 31.8%, from 2024 to 2030.
  • The developments in NLP are enabling the creation of sophisticated language models and text. Various applications, such as content generation, artificial intelligence, and chatbots, are being entirely changed with the help of these advancements.
  • An enormous amount of written data is being created through the wide utilization of virtual platforms. NLP encourages organizations to boost consumer experience, make decisions based on this data, and obtain an edge over their competitors with the help of effective tools for the extraction and analysis of the written data.
  • NLP is now an important contributor in the field of customized suggestions and sentiment analysis because of its ability to process and produce text.
  • This market is also growing due to the increasing need for interaction and understanding. NLP can respond to natural language, which helps create unbroken communication between humans and machines.
  • This results in the wide usage of NLP in voice assistants, artificial agents, and automated speech-processing systems.

The major applications covered in this report are:

  • Computer Vision (Fastest-Growing Category)
  • Natural Processing Language (Largest Category)
  • Robotics and Automation
  • Content Generation
  • Chatbots and Intelligent Virtual Assistants
  • Predictive Analysis
  • Others

End User Insights

  • Based on end user, the media and entertainment category is leading the market, and it is expected to grow with a CAGR, of 40%, in the forecast period.
  • This is because of the rapid adoption of AI tools by the media and entertainment sector to enhance its content production and delivery.
  • Everyone in this sector, such as developers, gamers, and content creators, can experience more artistic and creative things with the help of AI models.
  • In January 2023, American media and entertainment company BUZZFeed Inc. declared that it would upgrade and personalize particular services with the help of AI tools provided by Open AI.

The end users included in this report are:

  • Media and Entertainment (Largest Category)
  • IT and Telecommunication
  • BFSI (Fastest-Growing Category)
  • Healthcare and Life Sciences
  • Automotive and Transportation
  • Manufacturing
  • Construction and Real estate
  • Energy and Utilities
  • Retail and E-Commerce
  • Others

Model Insights

  • LLMs category holds the largest share, of around 40%, from 2024 to 2030.
  • This is because they are being highly used in various sectors and organizations, such as the entertainment and software industries.
  • organizations that want to boost their productivity, while providing customized customer experiences are rapidly opting for these models because of their remarkable accuracy in interpreting and understanding human language.
  • Their scalability, productivity, and more intuitive interfaces have made it far easier for businesses and organizations to integrate them into their systems.
  • Organizations using this approach are experiencing substantial boosts in client satisfaction as well as productivity, which is resulting in revenue growth and competitive benefits.

Below are the major models in the market:

  • Large Language Models (Largest Category)
  • Image and Video Generation Models
  • Multi-Modal Generative Models (Fastest-Growing Category)
  • Others

Technology Insights

  • The transformer category is dominating the market as this technology offers exceptional capabilities in NLP and generating output.
  • The unique method of arranging the models in order was possible because of the transformer technology, which made it possible to understand and comprehend sequential data.
  • Its adaptability and scalability are the other reasons for its success. Its potential to manage short and long sequences makes it suitable for many things, such as music generation and image synthesis.
  • It has shown excellent performance in the field of developing natural language. It is a crucial tool for chatbots and content generation as it has the potential to create logical and contextually relative texts.

Technologies analyzed in this report are:

  • Generative Adversarial Networks
  • Transformers (Largest Category)
  • Variational Auto Encoders
  • Diffusion Networks (Fastest-Growing Category)

Drive strategic growth with comprehensive market analysis

North America Holds 50% of Share

  • North America holds the largest share of the market, of around 50%, in 2023.
  • This is due to the increasing rates of banking fraud, rising healthcare burden, and surging popularity of pseudo-imagination.
  • Its advanced technological framework and development, along with its ability to harbor disruptive AI organizations, is one of the major reasons for its growth in the market.
  • Several technology companies in North America, including IBM and Microsoft, have invested in the creation of generative AI models.
  • Organizations in the region use AI to perform many tasks and activities, such as image modification, content creation, and design automation.

Generative AI Market Regional Outlook

The countries and regions analyzed are:

  • North America (Largest Regional Market)
    • U.S (Larger and Faster-Growing Market)
    • Canada
  • Europe
    • U.K. (Largest Country Market)
    • Germany (Fastest-Growing Country Market)
    • France
    • Italy
    • Spain
    • Rest of Europe
  • Asia Pacific (APAC) (Fastest-Growing Regional Market)
    • China (Largest Country Market)
    • India
    • Japan (Fastest-Growing Country Market)
    • South Korea
    • Australia
    • Rest of APAC
  • Latin America (LATAM)
    • Brazil (Largest and Fastest-Growing Country Market)
    • Mexico
    • Rest of LATAM
  • Middle East and Africa (MEA)
    • Saudi Arabia (Largest Country Market)
    • South Africa (Fastest-Growing Country Market)
    • U.A.E.
    • Rest of MEA

The Market is Fragmented

This market is growing rapidly, and competition is intensifying, as new players are emerging in the market with innovative products and services. The significant organizations in this sector are continuously updating their products to ensure security and reliability. Top companies, such as IBM, OpenAI, and Microsoft, are continuously making investments in R&D, to enhance the potential and capacity of AI.

Top Generative AI Companies:

  • Microsoft Corporation
  • IBM Corporation
  • Google LLC
  • Synthesia Ltd.
  • Amazon Web Services (AWS) Inc.
  • Adobe Inc.
  • D-ID
  • Genie AI
  • Media.io
  • OpenAI OpCo LLC
  • Codacy
  • ambeRoad Tech GmbH
  • Lightricks Ltd.
  • Floworks

Generative AI Companies News

  • In January 2024, Vodafone and Microsoft signed a 10-year strategic partnership to make digital services, generative AI, and cloud accessible for over 300 million consumers and businesses.
  • Generative AI image editing startup Photoroom Inc. raised USD 43 million in February 2024.
  • In October 2023, SAP debuted new CX generative AI capabilities to enhance customer experiences and boost business operations.
  • Yantra invested INR 100 crore in the Indian AI market in December 2023.

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