Generative AI Market Trends, Size, Share, Growth, Industry Analysis, Advance Technology and Forecast 2030
The global generative AI market is projected to register a CAGR of 31.5% during the forecast period, reaching USD 76.8 billion by 2030 from an estimated USD 11.3 billion in 2023. Major factors to boost the market growth include the advent of cloud storage has facilitated convenient data accessibility, the progression of AI and deep learning, and the emergence of an era focused on content creation and imaginative applications.
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By offering, Software to register for the largest market share during the forecast period
The scope of the software segment comprises of rule based models, statistical models, deep learning, generative adversial networks (GANs), autoencoders, convolutional neural networks (CNNs) and transformer models. This dominance can be attributed to the accessibility and ease of adoption of software solutions, which typically have a wider user base. Furthermore, the anticipated technological maturity of Generative AI software tools during this period will likely offer a diverse range of applications, catering to various industries and driving increased adoption rates.
By application, marketing & sales segment of application by business function is expected to hold the largest market share during the forecast period
Marketing & sales segment is anticipated to command the largest market share. This is driven by the increasing recognition of Generative AI’s potential to revolutionize customer engagement and decision-making processes. By automating content generation, customer insights analysis, and personalized recommendations, Generative AI can significantly enhance marketing strategies and sales interactions. As companies seek to gain a competitive edge through data-driven approaches, the adoption of Generative AI in marketing & sales functions is expected to see substantial growth, contributing to its dominant market position during the forecast period.
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Unique Features in the Generative AI Market
With the use of sophisticated algorithms, generative AI creates and synthesises complex content, including text, photos, videos, and music, producing unique and realistic digital assets on its own.
Through real-time user interaction with AI models that offer customisation options, feedback, and advice to co-create content and affect the production process, generative AI promotes creative collaboration.
By adapting generated outputs to unique preferences, traits, and requirements, generative AI enables the generation of personalised and customised information and offers consumers individualised suggestions, designs, and experiences.
Generative AI is a creative tool and inspiration source for artists, designers, and creators. It enhances human creativity by helping users generate ideas, explore design possibilities, and get beyond creative blockages.
The quality, diversity, and relevance of generated outputs are continuously improved by generative AI models, which are evolutionary and adaptive. They also adjust to shifting trends and preferences by continuously learning from user interactions, data, and feedback.
Major Highlights of the Generative AI Market
Deep learning algorithms, in particular Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Transformers, are advancing significantly in the generative AI sector, allowing for the creation of more complex and realistic material across a range of fields.
Generative AI is driving innovation and creativity in product design, content creation, and personalised experiences. Its applications span a wide range of industries, including manufacturing, gaming, entertainment, fashion, and the arts.
By automating content creation procedures and minimising the need for human intervention, generative AI is speeding up production workflows and cutting expenses while enabling the quick development of high-quality digital assets including text, photos, videos, and music.
By adjusting generated outputs to each user’s unique tastes, traits, and needs, generative AI enables personalisation and customisation of content and offers users individualised recommendations, designs, and experiences.
Concerns about bias, fairness, transparency, and data privacy are among the ethical and responsible uses of AI that the generative AI market is addressing. To assure ethical use and reduce potential hazards, safeguards, rules, and regulations are being put in place.
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Top Companies in the Generative AI Market
Some leading players in the generative AI market include Microsoft (US), IBM (US), Google (US), AWS (US), META (US), Adobe (US), OpenAI (US), Insilico Medicine (Hong Kong), Simplified (US), Genie AI (UK), Lightricks (Israel), Lumen5 (Canada), Giphy (US), Dialpad (US), Persado (US) and Codacy (Portugal). These players have adopted various organic and inorganic growth strategies, such as new product launches, partnerships and collaborations, and mergers and acquisitions, to expand their presence in the generative AI market.
OpenAI
OpenAl, founded in 2015 in San Francisco, California, is renowned for its AI innovations including GPT, DALL-E, and ChatGPT. These encompass the Generative Pre-trained Transformer (GPT) products, utilizing deep learning to emulate human-like text. GPT-3, launched in 2020, is a language model trained on extensive internet text and serves as the basis for the commercial “the API” product. This technology excels in natural language processing, translation, and text generation. OpenAl’s journey continued with DALL-E’s introduction in 2021 and a ChatGPT preview in 2022, focusing on conversational AI. The release of DALL-E 2 in 2022 further revolutionized image generation with quadruple the resolution. OpenAl’s prowess lies in driving AI evolution, revolutionizing language and image processing.
AWS
Amazon Web Services (AWS) offers a comprehensive set of artificial intelligence (AI) and machine learning (ML) services to meet business needs. AWS has the broadest and deepest portfolio of AI and ML services at all three layers of the stack. AWS offers the easiest way to build and scale generative AI applications, grounded in model choice and flexibility, making it possible for builders of all levels to innovate with machine learning. AWS provides readily available AI services, allowing users to add AI capabilities to their business applications without requiring ML experience. AWS has invested and innovated to offer the most performant, scalable infrastructure for cost-effective ML training and inference. AWS offers generative AI built-in services such as Amazon CodeWhisperer, an AI coding companion.
Google Cloud is dedicated to infusing AI across solutions, enabling customers to build AI-powered applications for document processing, data analysis, and more. This approach enhances data understanding and delivers industry-specific solutions. A noteworthy endeavor involves creating an AI language model supporting the world’s top 1,000 languages, starting with a model covering over 400 languages, marking a significant leap in language inclusivity. In a strategic acquisition in February 2020, Google gained Looker, a unified platform provider specializing in business intelligence, data applications, and embedded analytics. This move strengthens Google’s data-oriented offerings and reinforces its foothold in the business intelligence sector. Through these initiatives, Google maximizes the value of AI, catering to diverse industries and propelling innovation in language processing and analytics.
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