全球生成人工智慧市场分析（2023-2030）

154-page report on the enterprise Generative AI market, incl. technologies, market sizing and forecast, competitive landscape, trends, and use cases.

The ‘Generative AI Market Report 2023-2030’ is part of IoT Analytics' ongoing coverage of enterprise software technology markets. The information presented in this report is based on the results of secondary research and qualitative research, i.e., interviews with 30+ experts with experts in the field between June and November 2023. The main purpose of this document is to help our readers understand the current Generative AI landscape and potential use cases.

SAMPLE VIEW

The ‘Generative AI Market Report 2023-2030’ analyzes Data Center GPUs, Foundational models and platforms, and Gen AI services market from 2023 to 2030. It provides current market sizes and forecasts as well as market shares of the leading vendors.

• The Data Center GPU market is dominated by Nvidia with a stunning market share of 92%. AMD is the second biggest vendor being with 3%. Total spending reached $49B in 2023 up from a meager $17B in 2022. Until 2030 the market is expected to increase to nearly $160B

• The market for foundational models and Generative AI platforms is much more fragmented. Open AI is the current market leader with a 39% market share and its close ally and investor Microsoft is following with 30%. Spending is already at $3B in 2023 and expected to reach $92B in 2030.

• Many companies tried to define their Generative AI strategy in 2023 and vendors of Gen AI services realized revenue of $3.2B this year alone. Accenture is leading the pack with a 6% market share. The company tries to position itself as the GenAI service provider with a planned investment of $3B.

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What is Generative AI?

A deep learning technique that is capable of generating text, images, or other media, using models that learn the patterns and structure of their input training data and then generate new data that has similar characteristics.

What is a Data Center GPU?

The market segment for data center GPUs refers to specialized graphics processing units designed to handle the extensive computational demands of modern data centers. These GPUs are engineered to accelerate a variety of complex workloads, including high-performance computing, DL, ML, and large-scale graphics processing tasks. The market does not include spending on CPUs, consumer grade GPUs, or TPUs. It includes GPU systems.

What are foundational models?

Foundational models are large-scale, pre-trained models that can be adapted to a wide variety of tasks without the need for training from scratch, such as language processing, image recognition, and decision-making algorithms.

What is a Generative AI platform?

Gen AI platforms refer to software that enable the management of Gen AI-related activities outside of foundational models. Notably, IoT Analytics identified six platform types: development, data management/databases, AI IaaS/GPU as-a-service, middleware and integration, MLOps, and user interface and experience (UI/UX).

What are Gen AI services?

Gen AI services represent a specialized market segment dedicated to consulting, integration, and implementation support for organizations aiming to integrate Gen AI capabilities into their strategic operations. These services are tailored to help businesses conceptualize, develop, and execute strategies that leverage Gen AI technologies for enhanced innovation, efficiency, and value creation. Services include consulting, integration, and managed services.

SAMPLE VIEW

The ‘Generative AI Market Report 2023 - 2030’ comes with a list of 270+ projects with detailed info on the company, application, involved departments, region, and industry. Most of the projects are around text generation and coding with the IT department being the industry that is furthest ahead. The software industry is clearly the early adopter while other industries such as healthcare or financial services are currently hindered by regulation in the industry.

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Questions answered:

• What is Generative AI, and what are its technological components?

• Which Generative AI use cases and applications are being prioritized by enterprises right now?

• What is the current market size for Generative AI, and what are the market shares of key players?

• How do the leading generative AI models compare?

• Why do Nvidia in GPUs and OpenAI in LLMs have such dominant positions?

• What are some of the important implementation considerations for Generative AI?

• What are the current and next trends and challenges around Generative AI?

Companies mentioned:

A selection of companies mentioned in the report.

Table of Contents

1. Executive Summary

2. Introduction

3. Enterprise strategies for Generative AI

4. Technology overview

• a) Models/LLMs
• b) Platforms
• c) Databases
• d) Compute hardware

5. Generative AI market and competitive landscape

6. Use cases and case studies

7. Implementation and adoption considerations

8. Methodology

9. About IoT Analytics