Generative AI Market Size, Share & Trends Analysis Report By Component (Software, Service), By Technology (Generative Adversarial Networks, Transformers), By End Use, By Application, By Model, By Customers, By Region, And Segment Forecasts, 2025 - 2030

Generative AI Market Size & Trends

The global generative AI market size was valued at USD 16.87 billion in 2024 and is projected to grow at a CAGR of 37.6% from 2025 to 2030. The demand for generative AI applications across industries is being driven by factors such as the expanding use of technologies like super-resolution, text-to-image conversion, and text-to-video conversion, along with a growing need to modernize workflows. This trend shows the increasing importance of AI-driven solutions in enhancing operational efficiency and innovation across various sectors. For instance, in March 2023, Microsoft Corporation, a U.S.-based technology company, introduced Visual ChatGPT, a model incorporating multiple visual foundation models, which allows users to interact with ChatGPT through graphical user interfaces.

Generative AI utilizes unsupervised learning algorithms for tasks such as spam detection, image compression, and data preprocessing—for instance, removing noise from visual data to enhance picture quality. Moreover, supervised learning algorithms play a key role in medical imaging and image classification. These AI technologies find applications across a wide range of industries, including BFSI, healthcare, automotive and transportation, IT and telecommunications, media and entertainment, and more. Generative AI stands as a valuable tool for generating new ideas, solving complex problems, and developing innovative products. It also helps organizations save time and money, boost efficiency, and improve the quality of content produced.

The expansion of cloud storage solutions has significantly fueled the growth of the generative AI market by providing a robust foundation for technology development and deployment. Cloud storage offers scalable computing power, enabling businesses to access resource-intensive generative AI model training without substantial capital investment. It enhances data accessibility and collaboration, allowing global teams to store and share diverse datasets efficiently. Moreover, the cost-effective pay-as-you-go model minimizes financial constraints and promotes secure management of sensitive AI projects. With pre-trained models and APIs provided by cloud platforms, development processes are streamlined, while cloud infrastructure optimizes resources and increases business agility. Consequently, cloud storage solutions drive generative AI innovation, empowering companies to explore creative possibilities and support market growth.

Component Insights

The software segment accounted for the dominant share of 64.2% in 2024. The growth of the software segment in generative AI is driven by factors such as the rise in fraudulent activities, overestimation of capabilities, unexpected outcomes, and increasing concerns about data privacy. Generative AI software is expected to become increasingly significant across various industries, including fashion, entertainment, and transportation, as it gains power through advanced machine learning models. Brands such as H&M and Adidas, for instance, have leveraged generative AI to design clothing and create custom sneakers. Moreover, this technology has been applied to generate unique patterns for fabrics and prints, streamlining the design process and saving time for designers.

The service segment is projected to experience the fastest growth rate during the forecast period, driven by rising concerns about data protection, fraud detection, trading prediction, and risk modeling. Cloud-based generative AI services are anticipated to gain popularity due to their flexibility, scalability, and cost-effectiveness, fueling the segment's expansion. For instance, in April 2023, Amazon Web Services (AWS), a U.S.-based IT service management company, introduced Amazon Bedrock and a suite of generative AI services. These offerings are designed to provide AWS customers with tools for building chatbots, generating and summarizing text, and classifying images based on prompts, further advancing generative AI capabilities across industries.

Technology Insights

The transformers segment accounted for the dominant share in 2024, largely due to its capacity to handle vast amounts of data efficiently. These models excel in tasks involving natural language processing, image recognition, and even complex problem-solving. Their architecture, characterized by self-attention mechanisms, enables Transformers to learn intricate patterns in data, making them invaluable in a range of applications. Industries across sectors are increasingly adopting Transformers for personalized content generation, recommendation systems, and automation solutions. With continued advancements, Transformers are setting the standard for generative AI, pushing the limits of what is achievable in this field.

Diffusion networks are gaining momentum in the generative AI market, particularly recognized for their effectiveness in image and video generation. Unlike Transformers, diffusion models progressively refine data by removing noise, which allows for the creation of high-quality, realistic content. This technology is attracting attention in fields where creativity and detail are essential, such as entertainment, fashion, and advertising. As diffusion networks evolve, they are becoming more efficient, overcoming previous limitations in speed and resource usage. Their growing adoption reflects the market’s enthusiasm for diverse, powerful models that cater to specific generative needs.

End Use Insights

The media and entertainment industry accounted for the dominant share in 2024. The media and entertainment industry remains dominant in the generative AI market, as this sector extensively integrates AI for content creation, personalized recommendations, and audience engagement. Generative AI tools enable media companies to produce immersive visuals, generate unique audio tracks, and create interactive storytelling experiences, pushing the boundaries of creativity. This technology is also helping companies to tailor content for individual viewers, enhancing user experience and increasing engagement levels. The rise of virtual and augmented reality content further supports the demand for generative AI within this industry. As a result, media and entertainment continue to be a driving force in the adoption and innovation of generative AI.

The BFSI sector is seeing significant growth in generative AI adoption, focusing on applications that improve fraud detection, risk analysis, and customer service automation. Financial institutions are beginning to use AI-driven models to analyze complex datasets, identify suspicious patterns, and predict potential risks more accurately. Moreover, generative AI is streamlining customer support by enabling virtual assistants to handle routine inquiries and deliver personalized financial advice. With regulatory compliance becoming increasingly critical, AI models are also being utilized to ensure adherence to data privacy and security standards. The growing integration of generative AI within BFSI showcases the sector’s commitment to enhancing efficiency, security, and customer satisfaction.

Application Insights

Natural language processing (NLP) holds a dominant position in the generative AI market, driven by its widespread applications in chatbots, virtual assistants, and content creation. NLP models are highly effective in understanding and generating human-like text, enabling organizations to enhance communication, automate support tasks, and personalize user interactions. These models help businesses analyze customer feedback, interpret complex queries, and provide meaningful responses, contributing to improved user experiences. NLP also supports language translation and sentiment analysis, making it valuable across diverse industries. As a result, NLP continues to be the leading technology in generative AI, shaping how businesses engage with their audiences.

Computer vision is experiencing significant growth within the generative AI market, particularly due to its applications in industries such as healthcare, automotive, and retail. This technology enables machines to interpret and analyze visual data, which is essential for tasks like medical imaging, autonomous driving, and inventory management. Recent advancements are making computer vision models more efficient, allowing for the generation of highly realistic images and videos. The technology also supports object detection and facial recognition, further enhancing its utility across sectors. As computer vision capabilities advance, it is gaining traction and expanding its role in the generative AI landscape.

Model Insights

Large language models (LLMs) continue to dominate the market, primarily due to their impressive capabilities in text-based tasks such as content generation, customer service automation, and data analysis. These models, built on extensive datasets and sophisticated architectures, can produce highly coherent and contextually accurate responses, making them invaluable for applications across sectors. Their widespread adoption in industries like education, healthcare, and finance highlights their versatility in handling complex linguistic tasks. LLMs are also pivotal in sentiment analysis and real-time language translation, enhancing user engagement and accessibility. This dominance solidifies large language models as a cornerstone of generative AI innovation and application.

Multi-modal generative models are experiencing notable growth, fueled by their ability to process and generate content across multiple data types, such as text, images, and audio. These models are gaining traction in fields that benefit from a seamless integration of diverse media, including e-commerce, entertainment, and education. By combining visual, textual, and auditory data, multi-modal models enable more interactive and immersive user experiences, such as creating video content based on textual descriptions or generating audio narrations for visual content. As these models become more refined, their growing adoption showcases the market's enthusiasm for versatile generative AI that supports complex, cross-media interactions.

Customers Insights

App builders stand as the dominant customer segment within the market, driven by their need to integrate AI capabilities into applications across industries. These companies rely on generative AI to create innovative features such as personalized recommendations, automated customer support, and dynamic content generation, adding significant value to their applications. App builders are increasingly focused on enhancing user engagement and improving functionality, and generative AI provides the tools to achieve this efficiently. By incorporating AI-driven insights and interactions, app builders can meet growing customer expectations for responsive, intelligent applications. This demand reinforces the position of app builders as key customers driving generative AI advancements.

Model builders are increasingly using generative AI within this market, focusing on creating and refining advanced AI architectures for diverse applications. These builders play a crucial role in developing foundational models and optimizing them for efficiency, accuracy, and scalability. Model builders are essential in advancing generative AI’s capabilities, working on everything from language and vision models to complex multi-modal frameworks. Their work supports the broader ecosystem by enabling app builders to leverage robust, pre-trained models for specific use cases. As the demand for sophisticated AI grows, model builders are integral to the generative AI landscape, providing the backbone for new, impactful applications.

Regional Insights

North America generative AI market led the global industry, accounting for a revenue share of 40.8% in 2024.In North America, the market is thriving, supported by high investment levels and a strong ecosystem of technology companies and research institutions. The region is witnessing rapid adoption across sectors such as healthcare, finance, and entertainment as organizations seek to enhance productivity and create innovative solutions. Regulatory developments in data privacy and AI ethics are shaping the market, encouraging responsible AI adoption. In Canada, there is a particular focus on AI research and government support for AI-driven innovation. North America’s emphasis on advanced technology positions it as a major hub for generative AI development.

U.S. Generative AI Market Trends

The generative AI market in the U.S. is growing as AI is widely used across industries, from media and entertainment to finance and healthcare. The country is home to leading AI companies and research facilities driving advancements in language, vision, and multi-modal AI technologies. There is also significant investment from both private and public sectors, fueling the growth and adoption of generative AI. Government interest in establishing ethical standards and ensuring AI safety is impacting the regulatory sector.

Europe Generative AI Market Trends

The generative AI market in Europe is expanding, bolstered by supportive government policies and an emphasis on ethical AI. The European Union has set guidelines to ensure that AI is transparent, fair, and accountable, which influences AI deployment across industries. Key industries such as automotive, finance, and retail are actively exploring generative AI to improve customer experience and operational efficiency. Several European countries, including Germany and France, are investing in AI research to strengthen their positions in the global market.

Asia Pacific Generative AI Market Trends

The generative AI market in Asia-Pacific is witnessing rapid growth, driven by technological advancements and increasing adoption across industries. Countries such as China, Japan, and South Korea are investing heavily in AI, aiming to lead in areas like autonomous systems, robotics, and digital transformation. Generative AI is widely used in sectors such as e-commerce, manufacturing, and media, where automation and personalization are in high demand. Governments in the region are actively supporting AI research and development, fueling a competitive market environment.

Key Generative AI Company Insights

Some of the key companies in the generative AI market include Adobe, Amazon Web Services, Inc., D-ID, Genie AI Ltd., Google LLC, and others. Organizations are focusing on increasing customer base to gain a competitive edge in the industry. Therefore, key players are taking several strategic initiatives, such as mergers and acquisitions and partnerships with other major companies.

• Amazon Web Services, Inc. (AWS) has developed Amazon Bedrock, offering pre-trained foundational models for building generative AI applications. AWS provides cloud-based solutions for businesses to create chatbots, summarize text, and generate images. It offers APIs and model training resources customized to various industry needs. AWS’s scalable infrastructure supports businesses in deploying and expanding generative AI models efficiently.

• Google LLC focuses on generative AI with models such as Bard and Gemini, advancing large language and multi-modal systems. Google integrates generative AI into its products, including Google Workspace, to enhance productivity with AI-powered writing and visual tools. It also emphasizes responsible AI use with guidelines for ethical implementation. Google’s ongoing research continues to expand generative AI’s capabilities in enterprise and consumer settings.

Recent Developments

• In November 2024, Amazon Web Services (AWS) collaborated with partners, including Booz Allen Hamilton and Crayon, to launch the Generative AI Partner Innovation. This collaboration aims to expand the reach of the Generative AI Innovation Center and help customers build and deploy AI solutions by utilizing industry-specific expertise and proven methodologies to scale generative AI initiatives globally.

• In September 2024, IBM and Oracle Corporation, a U.S.-based computer software company, collaborated to enhance Oracle clients' use of generative AI by combining IBM's expertise in technologies like OCI Generative AI, Watsonx, and third-party models. Through this partnership, IBM is helping clients maximize ROI and reduce computing costs.

• In October 2024, Adobe expanded its Firefly generative AI to include video to provide creative professionals with new tools for generating and editing content in Photoshop, Illustrator, and Premiere Pro. These updates, available in a limited public beta, enable users to generate videos from text prompts and create faster, more refined images and designs.

Generative AI Market Report Scope

Global Generative AI Market Report Segmentation

This report offers revenue growth forecasts at the global, regional, and country levels and provides an analysis of the latest industry trends in each of the sub-segments from 2018 to 2030. For this study, Grand View Research has segmented the global generative AI market report based on component, technology, end-use, application, model, customers and region:

• Component Outlook (Revenue, USD Million, 2018 - 2030)

  • Software

  • Service

• Technology Outlook (Revenue, USD Million, 2018 - 2030)

  • Generative Adversarial Networks (GANs)

  • Transformers

  • Variational Auto-encoders

  • Diffusion Networks

• End-use Outlook (Revenue, USD Million, 2018 - 2030)

  • Media & Entertainment

  • BFSI

  • IT & Telecommunication

  • Healthcare

  • Automotive & Transportation

  • Gaming

  • Others

• Application (Revenue, USD Million, 2018 - 2030)

  • Computer Vision

  • NLP

  • Robotics & Automation

  • Content Generation

  • Chatbots & Intelligent Virtual Assistants

  • Predictive Analytics

  • Others

• Model (Revenue, USD Million, 2018 - 2030)

  • Large Language Models

  • Image & Video Generative Models

  • Multi-modal Generative Models

  • Others

• Customers (Revenue, USD Million, 2018 - 2030)

  • Model Builders

  • App Builders

• Regional Outlook (Revenue, USD Million, 2018 - 2030)

  • North America

    • U.S.

    • Canada

    • Mexico

  • Europe

    • U.K.

    • Germany

    • France

  • Asia Pacific

    • China

    • Japan

    • India

    • Australia

    • South Korea

  • Latin America

    • Brazil

  • Middle East & Africa (MEA)

    • KSA

    • UAE

    • South Africa