Global Generative AI Market: Analysis By Component (Software and Services), By Technology (Transformer, Generative Adversarial Networks, Variational Auto-encoder and Diffusion Networks), By End User (Media & Entertainment, IT & Telecommunication, Healthca

Global Generative AI Market: Analysis By Component (Software and Services), By Technology (Transformer, Generative Adversarial Networks, Variational Auto-encoder and Diffusion Networks), By End User (Media & Entertainment, IT & Telecommunication, Healthcare, BFSI, Automotive & Transportation and Others), By Region Size and Trends with Impact of COVID-19 and Forecast up to 2029

Generative AI, a subset of artificial intelligence techniques, focuses on creating data or content, often in the form of images, text, or other media, that is original and not directly derived from existing examples. Unlike traditional AI, which primarily analyzes and processes data, generative AI generates new data based on patterns and trends learned from existing datasets. This technology employs advanced algorithms, including neural networks, to generate outputs that mimic human creativity and imagination. Generative AI finds applications in various fields, including art, design, content creation, drug discovery, and natural language processing, where its ability to generate novel and diverse outputs contributes to innovation and problem-solving. The global generative AI market value stood at US$14.56 billion in 2023 and is expected to reach US$94.80 billion by 2029.

The continuous growth of the global generative AI market can be attributed to several key factors. Firstly, the proliferation of virtual and augmented reality (VR/AR) technologies has propelled the demand for generative AI. These technologies rely heavily on realistic and immersive content, driving the need for advanced AI models capable of generating life-like visuals and interactive experiences. Deployment of Large Language Models (LLMs) has emerged as another crucial driver. LLMs, such as GPT-3, have revolutionized natural language processing tasks, enabling the generation of human-like text, translation, and summarization. This adoption fuels the demand for generative AI solutions tailored to language-related applications. Moreover, the rising demand for creative and personalized content across various industries, including marketing, entertainment, and e-commerce, acts as a significant growth driver.

Furthermore, the healthcare and life sciences sectors are increasingly leveraging generative AI for various applications, such as drug discovery, medical imaging analysis, and patient data synthesis. These advancements contribute to improved diagnosis, treatment, and healthcare outcomes. Advancements in deep learning and neural networks play a fundamental role in driving generative AI market growth. Overall, the convergence of these factors fosters a conducive environment for the expansion of the generative AI market, facilitating innovation, and driving adoption across industries, and unlocking new opportunities for growth and development. The market is expected to grow at a CAGR of 36.64% over the projected period of 2024-2029.

Market Segmentation Analysis::

By Component: The report provides bifurcation of the global generative AI market into two segments namely, Software and Services. Software Generative AI currently dominates the market as it encompasses a range of AI software tools, platforms, and applications tailored for generating content such as images, text, and music. These software solutions enable businesses to streamline processes, enhance creativity, and drive innovation. On the other hand, Services Generative AI is poised for rapid growth as businesses increasingly seek specialized assistance in implementing and leveraging generative AI technologies effectively. Cloud-based generative AI services are expected to gain popularity as they provide scalability, flexibility, and cost-effectiveness, fueling the segment's growth. For instance, in December 2023, Mistral AI, an artificial intelligence solutions provider, partnered with Google Cloud, optimized proprietary language models, and distributed both its open weights on Google Cloud's AI-optimized infrastructure. As the demand for generative AI continues to rise, the services segment is expected to expand significantly to meet the growing need for expertise and support in this field.

By Technology: The report provides bifurcation of the global generative AI market into four segments namely, Transformer, Generative Adversarial Networks, Variational Auto-encoder, and Diffusion Networks. The Transformer segment currently dominates the market due to its versatility and widespread adoption across various applications. Transformers, based on attention mechanisms, excel in tasks such as natural language processing, image recognition, and sequence generation. Their ability to capture long-range dependencies and model complex relationships has made them indispensable in numerous industries, including healthcare, finance, and entertainment. Conversely, the Diffusion Networks segment is anticipated to experience fastest growth owing to its ability to generate high-quality images and text samples. Diffusion networks employ a diffusion process to generate outputs that closely match the distribution of training data, enabling the creation of realistic and diverse content. This capability makes them increasingly sought after in applications such as image synthesis, text generation, and creative content production, thus driving the growth in the forecasted period.

By End User: The report provides the bifurcation of the global generative AI market into six segments based on end-user, namely, Media & Entertainment, IT & Telecommunication, Healthcare, BFSI, Automotive & Transportation, and Others. The Media & Entertainment segment held the highest share in the market and BFSI is expected to be the fastest-growing segment in the forecasted period. Generative AI in Media & Entertainment drives content creation, production, and enhancement, meeting the demand for immersive experiences and personalized storytelling. This technology's adoption is fueled by the sector's quest for high-quality content and engaging experiences to remain competitive amid evolving consumer preferences. Conversely, the BFSI sector is embracing generative AI rapidly due to digital transformation initiatives and increasing demands for fraud detection, risk management, personalized customer experiences, and regulatory compliance. With countries like the UK, Spain, and Italy leading AI innovation, BFSI organizations are leveraging generative AI's advanced capabilities in data analysis and automation to enhance operational efficiency and deliver tailored services. As the BFSI sector prioritizes digital transformation to address complex challenges, the adoption of generative AI is expected to soar in the coming years.

By Region: The report bifurcates the global generative AI market into five regions namely, North America, Europe, Asia Pacific, Middle East and Africa, and Latin America. North America emerges as the largest region in the generative AI market, showcasing a promising landscape shaped by countries like the US, Canada, and Mexico, each with distinctive elements influencing their generative AI sector. Industry giants like OpenAI, Google, and Microsoft have significantly contributed to the region's market, driving substantial investments in research and development to push the boundaries of AI capabilities. Both venture capital firms and tech giants are injecting billions into generative AI technology development, fostering innovation and market expansion. This influx of capital has led to the creation of cutting-edge AI platforms, widely adopted across industries such as healthcare, finance, and entertainment. Moreover, the presence of leading market players and technology organizations, alongside a pool of experts, is anticipated to propel regional market growth, with the US expected to exhibit the fastest CAGR, fueled by increased adoption of deep learning and machine learning across diverse industries, including SMEs.

On the other hand, Asia Pacific emerges as the fastest-growing region in the generative AI sector, driven by a significant surge in AI technology adoption across various industries. With countries like China, Japan, India, and South Korea leading AI innovation, the region spearheads progress in generative AI technologies. The availability of vast data sets, particularly in language processing and computer vision, is crucial for training and improving GenAI models, with Asia Pacific's large and diverse population providing a rich data source. China dominates the industry, backed by significant investments in AI research, infrastructure, and talent development, with tech giants Alibaba, Tencent, and Baidu leading innovation across various sectors. Japan, renowned for technological prowess, hosts leading AI research institutions and companies, while India's GenAI market is poised for significant growth, driven by skill development, research advancements, and government support initiatives. For instance, In July 2023, Singapore's digital government agencies partnered with Google Cloud to develop GenAI capabilities in the public and private sectors.

Global Generative AI Market Dynamics:

Growth Drivers: The global generative AI market growth is predicted to be supported by numerous growth drivers such expansion of virtual and augmented reality, deployment of LLM, increasing demand for creative and personalized content, enhanced computing power and increased availability of data, growing applications in healthcare and life sciences, advancements in deep learning and neural networks, etc. Generative AI technologies play a pivotal role in creating immersive and interactive experiences within VR/AR environments, enabling realistic simulations, virtual training programs, and enhanced entertainment content. As the demand for VR/AR applications grows across various industries, including gaming, education, healthcare, and retail, the need for advanced generative AI solutions intensifies to meet the requirements of creating lifelike virtual worlds and experiences. Furthermore, the deployment of Large Language Models (LLM) contributes significantly to market growth. LLMs, such as GPT-3, leverage generative AI to produce human-like text, enabling applications in natural language processing, conversational AI, and content generation. With increasing demand for intelligent language-based applications and services, LLMs drive the adoption of generative AI technologies, fueling market expansion and innovation in text generation and understanding capabilities.

Challenges: However, the market growth would be negatively impacted by various challenges such as deepfakes and misinformation, shortage of skilled personnel, etc. Deepfake technology leverages generative AI algorithms to create highly realistic but fabricated content, including videos, images, and audio recordings. These can be used maliciously to spread false information, manipulate public opinion, and undermine trust in digital media. Failure to effectively address this challenge could hinder the growth of the generative AI market by eroding trust in AI-generated content and undermining confidence in digital media platforms.

Trends: The market is projected to grow at a fast pace during the forecasted period, due to market trends like integration of generative AI with robotics and automation, democratization of AI tools and platforms, growing integration with cloud computing, generative AI for scientific research, continued innovation in generative adversarial networks, emphasis on explainable AI and interpretability, automation and efficiency in enterprise workloads, focus on ethical AI, chatbot-powered customer service, etc. The integration of generative AI with robotics and automation enables the creation of intelligent systems capable of autonomously generating and adapting to new solutions in real-time. By leveraging generative AI, robots and automated systems can enhance their capabilities, such as pattern recognition, decision-making, and problem-solving, leading to more efficient and adaptable operations across various industries, from manufacturing to healthcare. Another key trend fueling market expansion is the democratization of AI tools and platforms, making advanced AI capabilities accessible to a broader range of users. These trends signify a shift towards more autonomous and inclusive AI-driven ecosystems, poised to revolutionize traditional workflows and accelerate innovation.

Impact Analysis of COVID-19 and Way Forward:

The COVID-19 pandemic positively impacted the generative AI market, prompting accelerated adoption in sectors like healthcare for drug discovery and patient monitoring. The need for automation and efficiency drove increased demand across industries. As economies recover, sustained growth is anticipated, fueled by ongoing technological advancements and the persistent demand for automation solutions. Furthermore, the pandemic has underscored the importance of predictive analytics and scenario planning, areas where generative AI excels.

Looking forward, the generative AI market is expected to rebound strongly as economies recover and organizations prioritize digital transformation efforts. Continued advancements in generative AI technologies, coupled with increasing demand for automation and efficiency across industries, are likely to drive sustained growth. Furthermore, ongoing research and development efforts aimed at enhancing the capabilities and applications of generative AI will contribute to its broader adoption and long-term market expansion.

Competitive Landscape and Recent Developments:

The global generative AI market is highly fragmented, characterized by the presence of numerous small and medium-sized companies competing for market share, and the presence of a substantial number of regional market players with limited business offerings and customer base.

The key players in the global generative AI market are:

Amazon.Com, Inc. (Amazon Web Services, Inc.)
Microsoft Corp.
Alphabet Inc.
IBM
Salesforce, Inc.
Nvidia Corporation
Accenture
Cognizant Technology Solutions Corporation
Capgemini
Adobe Inc.
Infosys
SAP SE
Synthesis AI
D-ID
OpenAI Inc.

In terms of market winners, Alphabet, Meta, and Microsoft, along with strategic suppliers such as Nvidia and Amazon Web Services, are expected to emerge as winners in the generative AI market. These companies possess extensive proprietary datasets and cloud infrastructure, enabling them to train large language models (LLMs) and provide generative AI services at scale. Since the introduction of ChatGPT (based on GPT-3.5) in late 2022, there has been a rapid advancement in large language model (LLM) and generative AI technologies within the global AI community. OpenAI unveiled its state-of-the-art GPT-4 in March 2023, which led to the launch of the premium version of ChatGPT Plus. Google introduced its latest LLM, Palm2, in May 2023, while Facebook released the open-source Llama 2 shortly after in July 2023, making it accessible through the Azure cloud platform. Some of the strategies among key players in the market are new launch, mergers, acquisitions, and collaborations. For instance, On March 27, 2024, Amazon has completed the investment of US$4 billion in Anthropic, solidifying their strategic collaboration to advance generative AI technologies. On March 28, 2024, Google Cloud and Valeo expanded their partnership to develop cloud-based generative AI tools and solutions, aimed at enhancing process efficiency and productivity.

Global Generative AI Market: Analysis By Component (Software and Services), By Technology (Transformer, Generative Adversarial Networks, Variational Auto-encoder and Diffusion Networks), By End User (Media & Entertainment, IT & Telecommunication, Healthcare, BFSI, Automotive & Transportation and Others), By Region Size and Trends with Impact of COVID-19 and Forecast up to 2029 - Report Summary

Report Metrics	Details
Years Considered	2019-2029
Base Year	2023
Forecast Period	2024-2029
Page Count	187
Units Referenced	US $
Segments/Key Topics	By Component, By Technology, By End User
Regions Covered	North America (the US, Canada, and Mexico), Europe (Germany, The UK, France, Italy, Spain and Rest of the Europe), Asia Pacific (China, Japan, India, South Korea and Rest of Asia Pacific), Middle East and Africa, and Latin America
Key Companies Mentioned	Amazon.Com, Inc. (Amazon Web Services, Inc.), Microsoft Corp., Alphabet Inc., IBM, Salesforce, Inc., Nvidia Corporation, Accenture, Cognizant Technology Solutions Corporation, Capgemini, Adobe Inc., Infosys, SAP SE, Synthesis AI, D-ID, OpenAI Inc.

Five FAQs about the Report

What is the size of this market?
The global generative AI market was valued at US$14.56 billion in 2023.

What is the forecasted growth for this market?
The global generative AI market is projected to reach US$94.80 billion by 2029. The market is determined to grow at a CAGR of 36.64% over the forecasted period of 2024-2029.

What are the key factors driving this market?
The continuous expansion of the global market for generative AI can be attributed to several pivotal factors. The proliferation of virtual and augmented reality (VR/AR) technologies is creating new opportunities for generative AI, enabling the creation of immersive and interactive experiences. Additionally, the deployment of Large Language Models (LLMs) such as GPT (Generative Pre-trained Transformer) models is revolutionizing natural language processing tasks, fueling demand for AI-generated content. Furthermore, the increasing need for creative and personalized content across various industries is driving the adoption of generative AI solutions. Enhanced computing power and the abundance of data are facilitating the development of more sophisticated generative AI algorithms. Moreover, the healthcare and life sciences sectors are leveraging generative AI for tasks like drug discovery and medical imaging analysis, further contributing to market growth. Advancements in deep learning and neural networks continue to push the boundaries of generative AI capabilities, promising even more transformative applications in the future.

How is this market segmented in this report?
The global generative AI market can be segmented based on the component (software and services), technology (transformer, generative adversarial networks, variational auto-encoder, and diffusion networks), and end user (media & entertainment, IT & telecommunication, healthcare, BFSI, automotive & transportation, and others).

What is the definition of this market in this report?
Generative AI refers to a subset of artificial intelligence (AI) techniques that focus on creating new data or content rather than just analyzing existing data or making predictions based on it. Generative AI algorithms have the ability to generate novel outputs, such as images, text, or audio, that mimic or are indistinguishable from human-created content. This includes techniques such as generative adversarial networks (GANs), variational auto encoders (VAEs), and deep reinforcement learning. The generative AI market encompasses the development, deployment, and adoption of these technologies across various industries and applications.

What are the major influences driving the growth/decline of this market?
The global generative AI market growth is predicted to be supported by numerous growth drivers such as expansion of virtual and augmented reality , deployment of LLM, increasing demand for creative and personalized content, enhanced computing power and increased availability of data, growing applications in healthcare and life sciences, advancements in deep learning and neural networks, and many other factors. Conversely, the market growth would be negatively impacted by various challenges such as deepfakes and misinformation, shortage of skilled personnel, etc. Moreover, the market growth would succeed in various market trends like integration of generative AI with robotics and automation, democratization of AI tools and platforms, growing integration with cloud computing, generative AI for scientific research, continued innovation in generative adversarial networks, emphasis on explainable AI and interpretability, automation and efficiency in enterprise workloads, focus on ethical AI, chatbot-powered customer service, etc.