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Global Generative AI Market Size and Forecast by Component, Deployment Model, Business Function, Technique, End User, and Region: 2019-2032

  June 2024   | Format: PDF DataSheet |   Pages: 400+ | Type: Sub-Industry Report |   

 

GLOBAL GENERATIVE AI MARKET GROWTH AND PERFORMANCE

Global Generative AI Market

Key Takeaways:

  • The global generative AI market size is estimated to reach US$ 165.30 billion in 2024, witnessing a YoY growth of 73.7%.
  • Overall market is projected to experience a significant upsurge in market revenue, reaching US$ 1,346.59 billion by the end of 2032.
  • In terms of growth, the market is anticipated to expand at a CAGR of 30.0% between 2024 and 2032.
  • The market is expected to witness an absolute dollar opportunity of US$ 1,181.29 billion between 2024 and 2032.
  • Among the components segment in the generative AI market, the hardware segment to dominate the market, with an expected market value of US$ 107.26 billion in 2024.
    • Software segment is forecasted to expand at a CAGR of 40.55% during the projection period (2024-2032). Among the diverse regions, the Asia Pacific generative AI market takes the lead, projecting a market value of US$ 82.34 billion in 2024. The fastest growing market among region is Asia Pacific, experiencing a CAGR of 32.17%.

“From revolutionizing healthcare diagnostics to optimizing IT operations, enhancing energy efficiency, streamlining manufacturing, modernizing transportation, and empowering the public sector, generative AI is the game-changer driving unprecedented advancements across every industry. “ 

GENERATIVE AI MARKET OUTLOOK

The continuous advancements in generative AI technology have marked a pivotal shift in the economic landscape of AI, empowering machines to create novel content or data that was beyond reach earlier. Further, GenAI holds promising opportunities for even greater innovation and impact across industries such as healthcare, BFSI, retail, and entertainment, shaping a new era of possibility and efficiency. According to our recent analysis, generative AI solutions are increasingly gaining traction in the healthcare sector. For instance, 30% of nursing tasks can be automated using advanced tools. Further, over 35% of new drug manufacturers could use GenAI tools by 2027. Additionally, 80% are interested in digital self-service for pre-visit tasks. With the responsible and ethical use of generative AI technologies being promoted by associations such as the International Association for Artificial Intelligence and Generative Technologies, it is apparent that the industry is poised for sustained growth and development. This is projected to drive the growth of the generative AI market throughout the forecast period.

Unprecedented Growth and Economic Impact of the Generative AI Industry

The generative AI market is witnessing unprecedented growth, driven by key advancements such as OpenAI’s ChatGPT and Nvidia’s enhanced revenue projections. With Nvidia's stock soaring over 30%, major tech firms developing large language models (LLMs) are significantly outperforming the broader market. This surge underscores the transformative potential of generative AI, which excels in creating diverse content formats using natural language prompts.

Industry experts highlight that this "Software 3.0" era enables businesses to leverage powerful AI models without extensive training data, drastically enhancing efficiency and reducing costs. As generative AI technology integrates into various sectors, including legal, data analytics, and media, its economic impact is projected to be profound, potentially boosting global GDP by 7% over the next decade. For investors, this presents a golden opportunity to capitalize on foundational AI technologies and supporting infrastructure, positioning themselves at the forefront of a market poised for expansive growth.

The Transformative Rise of Generative AI in Enterprise Applications

DataCube’s analysis highlights the transformative potential of critical Generative AI technologies, including Retrieval-Augmented Generation (RAG), foundation models, large language models, model hubs, and generative AI-enabled applications. According to DataCube, the landscape of enterprise AI usage is poised for a significant shift. By 2032, it is projected that over 85% of enterprises will have integrated generative AI APIs or models, and/or deployed GenAI-enabled applications in their production environments. This marks a substantial increase in generative AI adoption as compared to that in 2023. This rapid adoption underscores the growing importance of generative AI technologies in driving innovation and operational efficiency across various industries. Enterprises are recognizing the value of these advanced AI tools in enhancing decision-making, automating processes, and creating new business opportunities, positioning GenAI as a critical component of the future digital enterprise.

The generative AI application market stands out as the most rapidly expanding segment of the ecosystem, offering substantial value-creation opportunities. Both incumbent tech companies and new market entrants can capitalize on this growth. Companies that leverage specialized or proprietary data to fine-tune their applications can gain a significant competitive edge. This data-driven customization allows for the development of more effective and targeted solutions, enhancing competitive advantage.

Future of Generative AI Market

Generative AI has quickly progressed since the launch of ChatGPT in late 2022, with substantial developments occurring frequently. By March 2023, the technology had achieved six significant advancements, including innovative customer relationship management solutions and enhanced support for the financial services sector. These rapid iterations underscore the long-term efforts in advanced machine learning that are now coming to fruition, driving transformative changes across various industries.

Generative AI tools are rapidly expanding to cover a wide range of specific use cases, capable of generating written, visual, audio, and coded content. Businesses are increasingly developing applications tailored to specific industries and functions, which are expected to offer greater value than more general solutions in the near future. Moreover, the impact of generative AI will vary depending on the specific business functions and revenue scale within each industry. While marketing and sales will experience substantial benefits across nearly all sectors, industries like high-tech and banking will gain even more from generative AI's ability to speed up software development.

Generative AI represents significant progress, yet traditional advanced analytics and machine learning tools remain dominant in task optimization and continue to expand their applications across various sectors. Organizations during digital and AI transformations should monitor generative AI developments without overlooking the value and capabilities of existing AI tools. Though, generative AI offers exciting possibilities, it also carries significant risks. It can generate biased, inaccurate, or copyright-infringing content. Organizations must carefully consider these reputational and legal risks before fully integrating generative AI tools into their operations.

GENERATIVE AI COMPETITIVE LANDSCAPE

As generative AI systems are developed and deployed, a new ecosystem is taking shape to support the training and utilization of this transformative technology. While it may seem similar to a traditional AI ecosystem, there is a critical distinction with the introduction of foundation models. Talking more about the AI ecosystem scenario, major cloud providers, unsurprisingly, offer the most comprehensive platforms for running generative AI workloads and have preferential access to the necessary hardware and chips. While specialized cloud challengers may emerge, gaining market share will be challenging, especially in the near future, without support from large enterprises seeking to reduce their dependence on hyperscalers.

Dominance and Strategic Advancements in the Generative AI Market

In the generative AI market, the dominance of specialized AI processor providers is increasing. NVIDIA and Google rule chip design, with Taiwan Semiconductor Manufacturing Company Limited (TSMC) producing the majority of accelerator chips. This concentration presents high barriers to entry for new players, as start-up costs for research and development are substantial. Traditional hardware designers must acquire specialized skills, knowledge, and computational capabilities to effectively serve the generative AI market.

Moreover, the strengths of major players such as OpenAI and others, exemplify their influence and contribution to the soaring revenue in the generative AI market size.  Leading companies in the generative AI market are strategically advancing their AI infrastructure. For instance, Microsoft, in collaboration with NVIDIA, introduced powerful technologies such as NVIDIA Grace Blackwell GB200 and NVIDIA Quantum-X800 InfiniBand networking to Azure, enabling trillion-parameter foundation models for various AI tasks. Further, they're enhancing healthcare and life sciences with cloud, AI, and supercomputing technologies, facilitating rapid innovation across clinical research and care delivery. Additionally, Microsoft Azure will host NVIDIA Omniverse Cloud APIs, fostering data interoperability, collaboration, and visualization for industrial applications. Finally, NVIDIA GPUs and Triton Inference Server are integrated into Microsoft Copilot for real-time contextualized intelligence, while NVIDIA NIM inference microservices are coming to Azure AI, streamlining AI deployments for enhanced productivity.

Key Developments in the Generative AI Market

  • In June 2024, Hitachi Ltd. and Microsoft Corp. announced a multibillion-dollar collaboration over the next three years to accelerate social innovation through generative AI. Under this initiative, Hitachi will integrate Microsoft Cloud, Azure OpenAI Service, Dynamics 365, Copilot for Microsoft 365, and GitHub Copilot into Lumada solutions, aiming to deliver innovative solutions and improved outcomes for the energy, mobility, and other industries.
  • In May 2024, Temenos launched its Responsible Generative AI solutions within its AI-enhanced banking platform. These secure solutions integrate with Temenos Core and Financial Crime Mitigation (FCM), transforming banks' data interactions to enhance productivity and profitability, resulting in significant ROI.
  • In May 22, 2024, Tata Consultancy Services (TCS) entered extended collaboration with Google Cloud and introduced its latest offering, TCS Generative AI. This initiative utilizes Google Cloud’s generative AI services to develop and implement bespoke business solutions, empowering clients to leverage this innovative technology for expedited growth and transformation.
  • In November, 2023, Amazon Web Services (AWS) and NVIDIA announced an expansion of their strategic collaboration to enhance generative AI infrastructure, software, and services. This partnership combines NVIDIA's latest multi-node systems with next-generation GPUs, CPUs, and AI software, and AWS's advanced virtualization, security, and scalability solutions, including the Nitro System, Elastic Fabric Adapter (EFA), and UltraCluster. This integrated technology is designed to optimize the training of foundation models and development of generative AI applications.
    • In May 2023, Wipro and Google Cloud entered partnership to integrate generative AI throughout Wipro's service offerings. This collaboration aims to harness AI's potential to drive innovation and improve service delivery for Wipro's clients.

GENERATIVE AI INDUSTRY COVERAGE

Analysis Period

2019 – 2032

Actual Data

2019 – 2023

Base Year

2023

Estimated Year

2024

CAGR Period

2024 – 2032

Research Scope

Component
  • Hardware
  • Software
  • Service

Deployment Model
  • On-premise Solutions
  • Cloud-based Solutions
  • Hybrid Solutions

Business Function
  • Marketing and sales
  • Customer operations
  • Product R&D
  • Software engineering
  • Supply chain and operations
  • Risk and legal
  • Strategy and finance
  • Corporate IT
  • Talent and organization

Technique
  • Generative Modelling Techniques
  • Text-Based Techniques
  • Code-Based Techniques

End User
  • IT and Telecom
  • Media and Entertainment
  • Energy and Power
  • Transportation and Logistics
  • Healthcare
  • BFSI
  • Retail
  • Manufacturing
  • Public Sector
  • Other

Regions & Countries Covered

North America
  • US
  • Canada
  • Mexico

Western Europe
  • UK
  • Germany
  • France
  • Italy
  • Spain
  • Benelux
  • Nordics
  • Rest of Western Europe

Eastern Europe
  • Russia
  • Poland
  • Rest of Eastern Europe

Asia Pacific
  • Japan
  • Australia
  • China
  • South Korea
  • India
  • Malaysia
  • Hong Kong
  • Indonesia
  • New Zealand
  • Rest of Asia Pacific
  • Thailand
  • Vietnam
  • Philippines
  • Taiwan
  • Singapore
  • Rest of Asia Pacific

Latin America
  • Brazil
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    *Research Methodology: This report is based on DataCube’s proprietary 3-stage forecasting model, combining primary research, secondary data triangulation, and expert validation. [Learn more]

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