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市场调查报告书
商品编码
1904723

生成式人工智慧平台市场预测至2032年：全球分析，按组件、组织规模、部署类型、技术、最终用户和地区划分

Generative AI Platform Market Forecasts to 2032 - Global Analysis By Component (Platform Software and Services), Organization Size, Deployment Mode, Technology, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 | 商品交期: 2-3个工作天内

价格

根据 Stratistics MRC 的一项研究，全球生成式人工智慧平台市场预计到 2025 年将达到 251.5 亿美元，到 2032 年将达到 1,495 亿美元，在预测期内的复合年增长率为 29%。

云端分析是指利用云端运算资源收集、处理和分析大量数据，从而获得可执行的洞察。与传统的本地部署分析不同，云端分析采用扩充性的按需基础设施，使企业无需投资昂贵的硬体即可高效处理大型资料集。它整合了资料储存、视觉化、机器学习和即时报告等工具，兼具柔软性、成本效益和随时随地存取的便利性。企业正在利用云端分析来改善决策、优化营运、预测趋势并提升客户体验。其对协作、自动化和进阶分析的支援能力，使其成为当今数据驱动型环境中不可或缺的一部分。

云端解决方案日益普及

为了满足日益增长的云端解决方案需求，生成式人工智慧平台正越来越多地部署在云端环境中。企业更倾向于云端原生平台，因为它们在人工智慧工作负载方面具有可扩展性、柔软性和成本效益。云端部署能够快速整合到现有IT系统中，并支援分散式团队之间的即时协作。服务供应商提供的託管服务可以简化部署并降低基础架构开销。基于云端的生成式人工智慧还支援持续更新和模型改进，而无需大规模的本地投资。云端解决方案的日益普及正在推动市场成长。

资料安全和隐私问题

企业在云端环境中部署人工智慧模式时，会面临敏感资料外洩的风险。遵守 GDPR 和 HIPAA 等法规会增加管理人工智慧工作流程的复杂性。对未授权存取和滥用生成内容的担忧会减缓受监管行业的采用速度。服务提供者需要投入大量资金用于加密、监控和管治框架以降低风险。安全和隐私方面的挑战会削弱信任，并阻碍生成式人工智慧平台的广泛应用。

人工智慧和机器学习的发展

企业正在内容创作、产品设计、药物研发和客户参与等领域利用生成式人工智慧。与机器学习流程的整合正在推动预测分析，从而支持各行业的创新。生成式人工智慧平台正日益融入企业工作流程，以加速自动化和激发创造力。不断扩展的人工智慧生态系统正在推动可扩展生成式平台的需求。人工智慧和机器学习的日益普及正在为市场创造巨大的成长机会。

云端服务供应商之间竞争激烈

云端服务供应商之间的激烈竞争为生成式人工智慧平台带来了定价和差异化方面的挑战。主要企业提供的捆绑式人工智慧服务正在挤压小型供应商的利润空间。快速的创新週期加大了企业不断升级功能、保持竞争力的压力。企业在众多产品中难以抉择，导致决策延迟。小型供应商面临着被拥有整合生态系统的超大规模云端服务供应商蚕食市场份额的风险。竞争压力正在抑制盈利，并威胁市场的持续成长。

新冠疫情的感染疾病：

新冠疫情加速了数位转型，并推动了对生成式人工智慧平台的需求。一方面，预算限制延缓了传统企业大规模采用此技术。另一方面，远距办公和数位化优先策略凸显了人工智慧驱动的内容创作和自动化的必要性。行销、医疗保健和教育等行业越来越多地采用生成式人工智慧来支援虚拟互动。疫情也凸显了可扩展的云端人工智慧平台对于提升系统韧性的重要性。

预计在预测期内，平台软体细分市场将占据最大的市场份额。

在预测期内，平台软体领域预计将占据最大的市场份额，这主要得益于市场对可扩展、云端原生且能与企业工作流程无缝整合的解决方案的需求。软体平台为训练、部署和监控生成式人工智慧模式提供了一个集中式环境。企业依靠这些平台来加速自动化并降低开发复杂性。随着各行各业越来越多的组织扩大人工智慧的应用，对强大平台的需求也不断增长。与云端生态系的整合进一步增强了平台的可扩展性和可存取性。随着企业将效率和创新置于优先地位，软体平台正在推动生成式人工智慧平台市场的成长。

预计在预测期内，中小企业（SME）板块的复合年增长率将最高。

在预测期内，中小企业 (SME) 预计将实现最高成长率，这主要得益于其对价格合理的云端生成式人工智慧解决方案的日益普及。中小企业受益于计量收费模式，该模式降低了准入门槛，并支持其进行实验。生成式人工智慧可以帮助中小企业进行行销、产品设计和客户参与，而无需承担高昂的基础设施成本。云端原生平台提供柔软性和扩充性，能够满足中小企业的需求。对数位化优先策略的日益依赖进一步强化了该领域的需求。随着中小企业积极拥抱人工智慧驱动的创新，生成式人工智慧的普及正在推动市场成长。

占比最大的地区：

由于先进的云端基础设施、人工智慧的广泛应用以及企业对生成式人工智慧平台的早期投资，预计北美地区将在预测期内占据最大的市场份额。主要技术提供者的存在和成熟的数位生态系统为大规模应用提供了支援。强调创新和合规的法规环境正在推动安全人工智慧平台的普及。北美企业正优先考虑透过生成式人工智慧实现自动化和客户参与。对人工智慧驱动的内容创作的高需求进一步促进了人工智慧的应用。北美成熟的数位环境正在推动市场的持续成长。

预计年复合成长率最高的地区：

预计亚太地区在预测期内将实现最高的复合年增长率，这主要得益于新兴经济体的快速工业化、云端运算的日益普及以及政府主导的数位化倡议。中国、印度和东南亚等国家正大力投资人工智慧基础设施和生成式平台。对电子商务、金融科技和医疗保健创新日益增长的需求正在推动生成式人工智慧解决方案的普及。当地企业正在采用扩充性的平台来满足其不断增长的数位化需求。不断扩展的数位生态系统正在强化人工智慧在企业现代化进程中的作用。

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  • 公司概况
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  • 区域细分
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  • 竞争标竿分析
    • 根据主要企业的产品系列、地理覆盖范围和策略联盟进行基准分析

目录

第一章执行摘要

第二章 前言

  • 摘要
  • 相关利益者
  • 调查范围
  • 调查方法
  • 研究材料

第三章 市场趋势分析

  • 司机
  • 抑制因素
  • 机会
  • 威胁
  • 技术分析
  • 终端用户分析
  • 新兴市场
  • 新冠疫情的感染疾病

第四章 波特五力分析

  • 供应商的议价能力
  • 买方的议价能力
  • 替代品的威胁
  • 新进入者的威胁
  • 竞争对手之间的竞争

5. 全球生成式人工智慧平台市场（按组件划分）

  • 平台软体
  • 服务
    • 咨询服务
    • 整合和实施服务
    • 託管服务
    • 培训和支援服务
    • 分析和监控工具
  • 其他部件

6. 全球生成式人工智慧平台市场（依组织规模划分）

  • 中小企业
  • 大公司

7. 全球生成式人工智慧平台市场（按部署类型划分）

  • 本地部署
  • 基于云端的

8. 全球生成式人工智慧平台市场（按技术划分）

  • 自然语言处理（NLP）模型
  • 电脑视觉模型
  • 生成对抗网路（GAN）
  • 基于变压器的模型（大规模语言模型、扩散模型）
  • 多模态生成式人工智慧平台
  • 强化学习模型
  • 其他技术

9. 全球生成式人工智慧平台市场（按最终用户划分）

  • 医疗保健和生命科学
  • 零售与电子商务
  • 媒体与娱乐
  • 製造与工业设计
  • 教育/研究
  • 其他最终用户

第十章 全球生成式人工智慧平台市场（按地区划分）

  • 北美洲
    • 美国
    • 加拿大
    • 墨西哥
  • 欧洲
    • 德国
    • 英国
    • 义大利
    • 法国
    • 西班牙
    • 其他欧洲
  • 亚太地区
    • 日本
    • 中国
    • 印度
    • 澳洲
    • 纽西兰
    • 韩国
    • 其他亚太地区
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 其他南美国家
  • 中东和非洲
    • 沙乌地阿拉伯
    • 阿拉伯聯合大公国
    • 卡达
    • 南非
    • 其他中东和非洲地区

第十一章 重大进展

  • 协议、伙伴关係、合作和合资企业
  • 併购
  • 新产品发布
  • 业务拓展
  • 其他关键策略

第十二章 企业概况

  • Microsoft Corporation
  • Google LLC
  • Amazon Web Services, Inc.
  • IBM Corporation
  • OpenAI, Inc.
  • Anthropic PBC
  • Cohere Inc.
  • Stability AI Ltd.
  • Hugging Face, Inc.
  • Salesforce, Inc.
  • SAP SE
  • Oracle Corporation
  • Adobe Inc.
  • NVIDIA Corporation
  • Meta Platforms, Inc.
Product Code: SMRC32999

According to Stratistics MRC, the Global Generative AI Platform Market is accounted for $25.15 billion in 2025 and is expected to reach $149.5 billion by 2032 growing at a CAGR of 29% during the forecast period. Cloud Analytics refers to the practice of leveraging cloud computing resources to collect, process, and analyze vast amounts of data for actionable insights. Unlike traditional on-premises analytics, cloud analytics uses scalable, on-demand infrastructure, enabling organizations to handle large datasets efficiently without investing in costly hardware. It integrates tools for data storage, visualization, machine learning, and real-time reporting, providing flexibility, cost-effectiveness, and accessibility from anywhere. Businesses use cloud analytics to improve decision-making, optimize operations, predict trends, and enhance customer experiences. Its ability to support collaboration, automation, and advanced analytics makes it essential in the modern data-driven landscape.

Market Dynamics:

Driver:

Rising adoption of cloud-based solutions

Generative AI platforms are increasingly being deployed through cloud environments to meet rising adoption of cloud-based solutions. Enterprises prefer cloud-native platforms for scalability, flexibility, and cost efficiency in AI workloads. Cloud deployment enables faster integration with existing IT systems and supports real-time collaboration across distributed teams. Providers are offering managed services that simplify deployment and reduce infrastructure overhead. Cloud-based generative AI also supports continuous updates and model improvements without heavy local investment. Rising adoption of cloud-based solutions is propelling growth in the market.

Restraint:

Data security and privacy concerns

Enterprises face risks related to sensitive data exposure when deploying AI models in cloud environments. Compliance with regulations such as GDPR and HIPAA increases complexity in managing AI workflows. Concerns over unauthorized access and misuse of generated content slow adoption in regulated industries. Providers must invest heavily in encryption, monitoring, and governance frameworks to mitigate risks. Security and privacy challenges are restraining confidence and slowing widespread adoption of generative AI platforms.

Opportunity:

Growth in AI and machine learning

Enterprises are leveraging generative AI for content creation, product design, drug discovery, and customer engagement. Integration with machine learning pipelines enhances predictive analytics and supports innovation across industries. Generative AI platforms are increasingly embedded into enterprise workflows to accelerate automation and creativity. Expansion of AI ecosystems is reinforcing demand for scalable generative platforms. Growth in AI and machine learning adoption is fostering significant opportunities in the market.

Threat:

Intense competition among cloud providers

Intense competition among cloud providers is creating pricing and differentiation challenges for generative AI platforms. Major players are offering bundled AI services that reduce margins for smaller providers. Rapid innovation cycles increase pressure to continuously upgrade capabilities and maintain relevance. Enterprises face difficulty in choosing among diverse offerings which slows decision-making. Smaller vendors risk losing market share to hyperscale providers with integrated ecosystems. Competitive pressures are restraining profitability and threatening consistent growth in the market.

Covid-19 Impact:

The Covid-19 pandemic accelerated digital transformation and boosted demand for generative AI platforms. On one hand, budget constraints delayed some large-scale deployments in traditional enterprises. On the other hand, remote work and digital-first strategies highlighted the need for AI-driven content creation and automation. Generative AI was increasingly adopted in marketing, healthcare, and education to support virtual engagement. The pandemic reinforced the importance of scalable cloud-based AI platforms for resilience.

The platform software segment is expected to be the largest during the forecast period

The platform software segment is expected to account for the largest market share during the forecast period driven by demand for scalable cloud-native solutions that integrate seamlessly with enterprise workflows. Software platforms provide centralized environments for training, deployment, and monitoring of generative AI models. Enterprises rely on these platforms to accelerate automation and reduce development complexity. Demand for robust platforms is rising as organizations expand AI adoption across industries. Integration with cloud ecosystems further strengthens platform scalability and accessibility. As enterprises prioritize efficiency and innovation software platforms are accelerating growth in the generative AI platform market.

The small & medium enterprises (SMEs) segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the small & medium enterprises (SMEs) segment is predicted to witness the highest growth rate supported by rising adoption of affordable cloud-based generative AI solutions. SMEs benefit from pay-per-use models that lower entry barriers and enable experimentation. Generative AI supports SMEs in marketing, product design, and customer engagement without heavy infrastructure costs. Cloud-native platforms provide flexibility and scalability tailored to SME needs. Growing reliance on digital-first strategies is reinforcing demand in this segment. As SMEs embrace AI-driven innovation generative AI adoption is propelling growth in the market.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share driven by advanced cloud infrastructure strong AI adoption and early investment in generative platforms by enterprises. The presence of leading technology providers and mature digital ecosystems supports large-scale deployments. Regulatory emphasis on innovation and compliance drives adoption of secure AI platforms. Enterprises in North America prioritize automation and customer engagement through generative AI. High demand for AI-driven content creation further strengthens adoption. North America's mature digital landscape is fostering sustained growth in the market.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR fueled by rapid industrialization expanding cloud adoption and government-led digital initiatives across emerging economies. Countries such as China, India, and Southeast Asia are investing heavily in AI infrastructure and generative platforms. Rising demand for e-commerce, fintech, and healthcare innovation strengthens adoption of generative AI solutions. Local enterprises are deploying scalable platforms to meet growing digital needs. Expanding digital ecosystems are reinforcing the role of AI in enterprise modernization.

Key players in the market

Some of the key players in Generative AI Platform Market include Microsoft Corporation, Google LLC, Amazon Web Services, Inc., IBM Corporation, OpenAI, Inc., Anthropic PBC, Cohere Inc., Stability AI Ltd., Hugging Face, Inc., Salesforce, Inc., SAP SE, Oracle Corporation, Adobe Inc., NVIDIA Corporation and Meta Platforms, Inc.

Key Developments:

In June 2024, OpenAI completed the acquisition of Rockset, a real-time analytics database startup. This technology is being integrated to power OpenAI's retrieval infrastructure, enabling faster and more efficient data processing for enterprise clients.

In May 2024, Google acquired Cameyo, a provider of virtual application delivery solutions, to deeply integrate its technology into ChromeOS. This is a strategic move to enhance enterprise capabilities and is directly tied to Google's broader AI-powered workspace ecosystem.

Components Covered:

  • Platform Software
  • Services

Organization Sizes Covered:

  • Small & Medium Enterprises (SMEs)
  • Large Enterprises

Deployment Modes Covered:

  • On-Premise
  • Cloud-Based

Technologies Covered:

  • Natural Language Processing (NLP) Models
  • Computer Vision Models
  • Generative Adversarial Networks (GANs)
  • Transformer-Based Models (LLMs, Diffusion Models)
  • Multimodal Generative AI Platforms
  • Reinforcement Learning Models
  • Other Technologies

End Users Covered:

  • Healthcare & Life Sciences
  • Retail & E-commerce
  • Media & Entertainment
  • Manufacturing & Industrial Design
  • Education & Research
  • Other End Users

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2024, 2025, 2026, 2028, and 2032
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Technology Analysis
  • 3.7 End User Analysis
  • 3.8 Emerging Markets
  • 3.9 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global Generative AI Platform Market, By Component

  • 5.1 Introduction
  • 5.2 Platform Software
  • 5.3 Services
    • 5.3.1 Consulting Services
    • 5.3.2 Integration & Implementation Services
    • 5.3.3 Managed Services
    • 5.3.4 Training & Support Services
    • 5.3.5 Analytics & Monitoring Tools
  • 5.4 Other Components

6 Global Generative AI Platform Market, By Organization Size

  • 6.1 Introduction
  • 6.2 Small & Medium Enterprises (SMEs)
  • 6.3 Large Enterprises

7 Global Generative AI Platform Market, By Deployment Mode

  • 7.1 Introduction
  • 7.2 On-Premise
  • 7.3 Cloud-Based

8 Global Generative AI Platform Market, By Technology

  • 8.1 Introduction
  • 8.2 Natural Language Processing (NLP) Models
  • 8.3 Computer Vision Models
  • 8.4 Generative Adversarial Networks (GANs)
  • 8.5 Transformer-Based Models (LLMs, Diffusion Models)
  • 8.6 Multimodal Generative AI Platforms
  • 8.7 Reinforcement Learning Models
  • 8.8 Other Technologies

9 Global Generative AI Platform Market, By End User

  • 9.1 Introduction
  • 9.2 Healthcare & Life Sciences
  • 9.3 Retail & E-commerce
  • 9.4 Media & Entertainment
  • 9.5 Manufacturing & Industrial Design
  • 9.6 Education & Research
  • 9.7 Other End Users

10 Global Generative AI Platform Market, By Geography

  • 10.1 Introduction
  • 10.2 North America
    • 10.2.1 US
    • 10.2.2 Canada
    • 10.2.3 Mexico
  • 10.3 Europe
    • 10.3.1 Germany
    • 10.3.2 UK
    • 10.3.3 Italy
    • 10.3.4 France
    • 10.3.5 Spain
    • 10.3.6 Rest of Europe
  • 10.4 Asia Pacific
    • 10.4.1 Japan
    • 10.4.2 China
    • 10.4.3 India
    • 10.4.4 Australia
    • 10.4.5 New Zealand
    • 10.4.6 South Korea
    • 10.4.7 Rest of Asia Pacific
  • 10.5 South America
    • 10.5.1 Argentina
    • 10.5.2 Brazil
    • 10.5.3 Chile
    • 10.5.4 Rest of South America
  • 10.6 Middle East & Africa
    • 10.6.1 Saudi Arabia
    • 10.6.2 UAE
    • 10.6.3 Qatar
    • 10.6.4 South Africa
    • 10.6.5 Rest of Middle East & Africa

11 Key Developments

  • 11.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 11.2 Acquisitions & Mergers
  • 11.3 New Product Launch
  • 11.4 Expansions
  • 11.5 Other Key Strategies

12 Company Profiling

  • 12.1 Microsoft Corporation
  • 12.2 Google LLC
  • 12.3 Amazon Web Services, Inc.
  • 12.4 IBM Corporation
  • 12.5 OpenAI, Inc.
  • 12.6 Anthropic PBC
  • 12.7 Cohere Inc.
  • 12.8 Stability AI Ltd.
  • 12.9 Hugging Face, Inc.
  • 12.10 Salesforce, Inc.
  • 12.11 SAP SE
  • 12.12 Oracle Corporation
  • 12.13 Adobe Inc.
  • 12.14 NVIDIA Corporation
  • 12.15 Meta Platforms, Inc.

List of Tables

  • Table 1 Global Generative AI Platform Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global Generative AI Platform Market Outlook, By Component (2024-2032) ($MN)
  • Table 3 Global Generative AI Platform Market Outlook, By Platform Software (2024-2032) ($MN)
  • Table 4 Global Generative AI Platform Market Outlook, By Services (2024-2032) ($MN)
  • Table 5 Global Generative AI Platform Market Outlook, By Consulting Services (2024-2032) ($MN)
  • Table 6 Global Generative AI Platform Market Outlook, By Integration & Implementation Services (2024-2032) ($MN)
  • Table 7 Global Generative AI Platform Market Outlook, By Managed Services (2024-2032) ($MN)
  • Table 8 Global Generative AI Platform Market Outlook, By Training & Support Services (2024-2032) ($MN)
  • Table 9 Global Generative AI Platform Market Outlook, By Analytics & Monitoring Tools (2024-2032) ($MN)
  • Table 10 Global Generative AI Platform Market Outlook, By Other Components (2024-2032) ($MN)
  • Table 11 Global Generative AI Platform Market Outlook, By Organization Size (2024-2032) ($MN)
  • Table 12 Global Generative AI Platform Market Outlook, By Small & Medium Enterprises (SMEs) (2024-2032) ($MN)
  • Table 13 Global Generative AI Platform Market Outlook, By Large Enterprises (2024-2032) ($MN)
  • Table 14 Global Generative AI Platform Market Outlook, By Deployment Mode (2024-2032) ($MN)
  • Table 15 Global Generative AI Platform Market Outlook, By On-Premise (2024-2032) ($MN)
  • Table 16 Global Generative AI Platform Market Outlook, By Cloud-Based (2024-2032) ($MN)
  • Table 17 Global Generative AI Platform Market Outlook, By Technology (2024-2032) ($MN)
  • Table 18 Global Generative AI Platform Market Outlook, By Natural Language Processing (NLP) Models (2024-2032) ($MN)
  • Table 19 Global Generative AI Platform Market Outlook, By Computer Vision Models (2024-2032) ($MN)
  • Table 20 Global Generative AI Platform Market Outlook, By Generative Adversarial Networks (GANs) (2024-2032) ($MN)
  • Table 21 Global Generative AI Platform Market Outlook, By Transformer-Based Models (LLMs, Diffusion Models) (2024-2032) ($MN)
  • Table 22 Global Generative AI Platform Market Outlook, By Multimodal Generative AI Platforms (2024-2032) ($MN)
  • Table 23 Global Generative AI Platform Market Outlook, By Reinforcement Learning Models (2024-2032) ($MN)
  • Table 24 Global Generative AI Platform Market Outlook, By Other Technologies (2024-2032) ($MN)
  • Table 25 Global Generative AI Platform Market Outlook, By End User (2024-2032) ($MN)
  • Table 26 Global Generative AI Platform Market Outlook, By Healthcare & Life Sciences (2024-2032) ($MN)
  • Table 27 Global Generative AI Platform Market Outlook, By Retail & E-commerce (2024-2032) ($MN)
  • Table 28 Global Generative AI Platform Market Outlook, By Media & Entertainment (2024-2032) ($MN)
  • Table 29 Global Generative AI Platform Market Outlook, By Manufacturing & Industrial Design (2024-2032) ($MN)
  • Table 30 Global Generative AI Platform Market Outlook, By Education & Research (2024-2032) ($MN)
  • Table 31 Global Generative AI Platform Market Outlook, By Other End Users (2024-2032) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.