Generative Artificial Intelligence AI Market Size & Trends 2023 Report

Generative AI Market Update 2023: Predicted to Achieve US$ 30 4 Billion Revenue by 2028 CAGR of 20.01%

They will likely go into specific problem spaces (e.g., code, design, gaming) rather than trying to be everything to everyone. They will likely first integrate deeply into applications for leverage and distribution and later attempt to replace the incumbent applications with AI-native workflows. It will take time to build these applications the right way to accumulate users and data, but we believe the best ones will be durable and have a chance to become massive.

Our customized solutions are tailored to meet the clients’ requirement whether they are looking to expand or planning to launch a new product in the global market. Additionally, generative AI utilizes unsupervised learning algorithms for spam identification, image compression, and preparing data stages like eliminating noise from visual data to enhance picture quality. Moreover, image categorization & medical imaging also involves supervised learning techniques.

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By automating laborious coding, generative AI has also had an impact on the software development industry. Rather than totally coding the software, IT professionals may now swiftly design a solution by communicating what they are searching for to the AI model. Deep learning segment was leading the Yakov Livshits in terms of technology in 2022. The global generative Artificial Intelligence (AI) market is expected to register a revenue Compound Annual Growth Rate (CAGR) of 35.4% during the forecast period. Technavio presents a detailed picture of the market by way of study, synthesis, and summation of data from multiple sources.

IBM focuses on AI for enterprises as rivals eye wider market – ABS-CBN News

IBM focuses on AI for enterprises as rivals eye wider market.

Posted: Mon, 18 Sep 2023 00:35:00 GMT [source]

The software segment was the largest segment and was valued at USD 1,881.55 million in 2017. Some of the main applications of this software across enterprises include content creation and customer service automation. Another prime example of AI-based software is StyleGAN which utilizes machine learning to generate realistic human faces and has wide applications in the fashion and beauty industry to generate virtual models for clothing and makeup. Runway is also another AI-based tool that is used by designers and artists to create new designs and artwork.


We could even soon witness a famous actress licence her image to a production company, which then uses a generative AI model to do the actual acting in an advertisement. The presence of tech players in Europe and Asia-Pacific creates lucrative growth potential for the market in the area. During the projection period, the Asia Pacific region is expected to develop at the highest CAGR. This is due to continuous mounting demand from end-user industries in emerging economies such as China and India, as well as the development of technology infrastructure and government initiatives. The report forecasts market growth by revenue at global, regional & country levels and provides an analysis of the latest trends and growth opportunities from 2017 to 2027. Sustained Category LeadershipThe best Generative AI companies can generate a sustainable competitive advantage by executing relentlessly on the flywheel between user engagement/data and model performance.

Oracle Brings Generative AI Capabilities to Healthcare -September … – Marketscreener.com

Oracle Brings Generative AI Capabilities to Healthcare -September ….

Posted: Mon, 18 Sep 2023 12:19:03 GMT [source]

North America is estimated to contribute 66% to the growth of the global market during the forecast period. Technavio’s analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period. Some of the key industries which are transformed due to the development of the generative AI market include the health sector and financial sector. For instance, AI-powered tools are widely utilized across companies to give personalized investment advice to clients. Hence, such wide applications of AI-based tools across enterprises are expected to drive the global generative AI market growth during the forecast period.

Financial Services & Investing Overview

Yakov Livshits
Founder of the DevEducation project
A prolific businessman and investor, and the founder of several large companies in Israel, the USA and the UAE, Yakov’s corporation comprises over 2,000 employees all over the world. He graduated from the University of Oxford in the UK and Technion in Israel, before moving on to study complex systems science at NECSI in the USA. Yakov has a Masters in Software Development.

As businesses adapt to the changing landscape, they are exploring innovative ways to leverage virtual worlds and enhance productivity. Companies are creating virtual offices, meeting spaces, and training simulations within these digital environments, enabling remote teams to collaborate seamlessly. Employees can participate in virtual conferences, attend training sessions, and even work on projects together, regardless of their physical locations. Ethical Issues related to data privacy is a major restraint for revenue growth of the global generative AI market. Qualitative and quantitative analysis of vendors has been conducted to help clients understand the wider business environment as well as the strengths and weaknesses of key market players. Data is qualitatively analyzed to categorize vendors as pure play, category-focused, industry-focused, and diversified; it is quantitatively analyzed to categorize vendors as dominant, leading, strong, tentative, and weak.

generative ai market

The analysts have presented the various facets of the market with a particular focus on identifying the key industry influencers. The data thus presented is comprehensive, reliable, and the result of extensive research, both primary and secondary. Form Factor Today, Generative AI apps largely exist as plugins in existing software ecosystems. Code completions happen in your IDE; image generations happen in Figma or Photoshop; even Discord bots are the vessel to inject generative AI into digital/social communities.

Generative AI Market: Global Industry Trends, Share, Size, Growth, Opportunity and Forecast 2023-2028

Generative AI is well on the way to becoming not just faster and cheaper, but better in some cases than what humans create by hand. Every industry that requires humans to create original work—from social media to gaming, advertising to architecture, coding to graphic design, product design to law, marketing to sales—is up for reinvention. The dream is that generative AI brings the marginal cost of creation and knowledge work down towards zero, generating vast labor productivity and economic value—and commensurate market cap. This raises concerns about data privacy, as large datasets might contain sensitive information about individuals. Additionally, the use of AI-generated content in potentially harmful ways, such as deepfakes, has sparked ethical debates and regulatory scrutiny.

information is then
combined with the data collected to provide a complete picture of the market. Macro-economic factor analysis
is also carried
out to understand the impact of external factors on the market. Finally, country-level data analysis is
performed to
understand the market dynamics in specific regions and countries. Generative AI models can generate stunning visuals, including graphics, images, art forms and videos. Marketers can leverage these AI-generated visuals to enhance their storytelling, create eye-catching social media posts and produce visually engaging presentations.

A rise in fake medical care and pseudo-imagination as well as increasing banking frauds will enable North America to dominate the industry over the forecast period. The presence of major companies in the U.S., such as Meta, Microsoft, and Google LLC, as well as industry professionals is likely to fuel expansion in the regional market. The demand for AI-generated content in industries including Yakov Livshits media & entertainment and healthcare as well as the accessibility to vast amounts of data for training generative models is an additional factor driving the regional industry growth. In terms of end-use, media & entertainment category registered the highest revenue share in 2022 due to the major use of generative AI to create and develop attractive and better advertisement campaigns.

generative ai market

These models have been used to create synthetic images for various purposes, including art, design, and entertainment. Numerous applications have helped GANs to accumulate a massive market share in the generative AI market. GANs have found applications in numerous domains and industries, making them highly versatile.

  • Readily prepared video scripts are of great help in reducing the required time for creating videos.
  • Some of the main applications of this software across enterprises include content creation and customer service automation.
  • As businesses adapt to the changing landscape, they are exploring innovative ways to leverage virtual worlds and enhance productivity.
  • It is advisable for businesses to stay updated on the current technologies and leverage their benefits.
  • AI’s rapid growth can increase energy demands and carbon emissions, especially as Generative AI requires significant computing power and data centers.

Generative AI technologies, such as natural language processing and image synthesis, played a vital role in drug discovery, vaccine development, medical research, and data analysis. Furthermore, the shift to remote work led to an increased focus on automation and AI-driven tools to boost productivity and efficiency. This rise in demand and adoption of Generative AI applications resulted in market expansion and increased investment in AI research and development. Consequently, the pandemic accelerated the growth and utilization of Generative AI technologies across various sectors, ushering in new opportunities and advancements in the field. In the secondary research process, various sources were referred to for identifying and collecting information for this study. Secondary sources included annual reports, press releases, and investor presentations of companies; white papers, journals, and certified publications; and articles from recognized authors, directories, and databases.

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