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市場調查報告書
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1904723

生成式人工智慧平台市場預測至2032年：全球分析，按組件、組織規模、部署類型、技術、最終用戶和地區分類

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個工作天內

價格

根據 Stratistics MRC 的一項研究，全球生成式人工智慧平台市場預計到 2025 年將達到 251.5 億美元，到 2032 年將達到 1,495 億美元，在預測期內的複合年成長率為 29%。

雲端分析是指利用雲端運算資源收集、處理和分析大量數據，從而獲得可執行的洞察。與傳統的本地部署分析不同，雲端分析採用擴充性的按需基礎設施，使企業無需投資昂貴的硬體即可高效處理大型資料集。它整合了資料儲存、視覺化、機器學習和即時報告等工具，兼具柔軟性、成本效益和隨時隨地存取的便利性。企業正在利用雲端分析來改善決策、最佳化營運、預測趨勢並提升客戶體驗。其對協作、自動化和進階分析的支援能力，使其成為當今數據驅動型環境中不可或缺的一部分。

雲端解決方案日益普及

為了滿足日益成長的雲端解決方案需求，生成式人工智慧平台正擴大部署在雲端環境中。企業更傾向於雲端原生平台，因為它們在人工智慧工作負載方面具有可擴展性、柔軟性和成本效益。雲端部署能夠快速整合到現有IT系統中，並支援分散式團隊之間的即時協作。服務供應商提供的託管服務可以簡化部署並降低基礎架構開銷。基於雲端的生成式人工智慧還支援持續更新和模型改進，而無需大規模的本地投資。雲端解決方案的日益普及正在推動市場成長。

資料安全和隱私問題

企業在雲端環境中部署人工智慧模式時，會面臨敏感資料外洩的風險。遵守 GDPR 和 HIPAA 等法規會增加管理人工智慧工作流程的複雜性。對未授權存取和濫用生成內容的擔憂會減緩受監管行業的採用速度。服務提供者需要投入大量資金用於加密、監控和管治框架以降低風險。安全和隱私方面的挑戰會削弱信任，並阻礙生成式人工智慧平台的廣泛應用。

人工智慧和機器學習的發展

企業正在內容創作、產品設計、藥物研發和客戶參與等領域利用生成式人工智慧。與機器學習流程的整合正在推動預測分析，從而支持各行業的創新。生成式人工智慧平台正日益融入企業工作流程，以加速自動化和激發創造力。不斷擴展的人工智慧生態系統正在推動可擴展生成式平台的需求。人工智慧和機器學習的日益普及正在為市場創造巨大的成長機會。

雲端服務供應商之間競爭激烈

雲端服務供應商之間的激烈競爭為生成式人工智慧平台帶來了定價和差異化方面的挑戰。主要企業提供的捆綁式人工智慧服務正在擠壓小型供應商的利潤空間。快速的創新週期加大了企業不斷升級功能、保持競爭力的壓力。企業在眾多產品中難以抉擇，導致決策延遲。小型供應商面臨著被擁有整合生態系統的超大規模雲端服務供應商蠶食市場佔有率的風險。競爭壓力正在抑制盈利，並威脅市場的持續成長。

新冠疫情的感染疾病：

新冠疫情加速了數位轉型，並推動了對生成式人工智慧平台的需求。一方面，預算限制延緩了傳統企業大規模採用此技術。另一方面，遠距辦公和數位化優先策略凸顯了人工智慧驅動的內容創作和自動化的必要性。行銷、醫療保健和教育等行業擴大採用生成式人工智慧來支援虛擬互動。疫情也凸顯了可擴展的雲端人工智慧平台對於提升系統韌性的重要性。

預計在預測期內，平台軟體細分市場將佔據最大的市場佔有率。

在預測期內，平台軟體領域預計將佔據最大的市場佔有率，這主要得益於市場對可擴展、雲端原生且能與企業工作流程無縫整合的解決方案的需求。軟體平台為訓練、部署和監控生成式人工智慧模式提供了一個集中式環境。企業依靠這些平台來加速自動化並降低開發複雜性。隨著各行各業越來越多的組織擴大人工智慧的應用，對強大平台的需求也不斷成長。與雲端生態系的整合進一步增強了平台的可擴展性和可存取性。隨著企業將效率和創新置於優先地位，軟體平台正在推動生成式人工智慧平台市場的成長。

預計在預測期內，中小企業（SME）板塊的複合年成長率將最高。

在預測期內，中小企業 (SME) 預計將實現最高成長率，這主要得益於其對價格合理的雲端生成式人工智慧解決方案的日益普及。中小企業受益於計量收費模式，該模式降低了准入門檻，並支持其進行實驗。生成式人工智慧可以幫助中小企業進行行銷、產品設計和客戶參與，而無需承擔高昂的基礎設施成本。雲端原生平台提供柔軟性和擴充性，能夠滿足中小企業的需求。對數位化優先策略的日益依賴進一步強化了該領域的需求。隨著中小企業積極擁抱人工智慧驅動的創新，生成式人工智慧的普及正在推動市場成長。

佔比最大的地區：

由於先進的雲端基礎設施、人工智慧的廣泛應用以及企業對生成式人工智慧平台的早期投資，預計北美地區將在預測期內佔據最大的市場佔有率。主要技術提供者的存在和成熟的數位生態系統為大規模應用提供了支援。強調創新和合規的法規環境正在推動安全人工智慧平台的普及。北美企業正優先考慮透過生成式人工智慧實現自動化和客戶參與。對人工智慧驅動的內容創作的高需求進一步促進了人工智慧的應用。北美成熟的數位環境正在推動市場的持續成長。

預計年複合成長率最高的地區：

預計亞太地區在預測期內將實現最高的複合年成長率，這主要得益於新興經濟體的快速工業化、雲端運算的日益普及以及政府主導的數位化舉措。中國、印度和東南亞等國家正大力投資人工智慧基礎設施和生成式平台。對電子商務、金融科技和醫療保健創新日益成長的需求正在推動生成式人工智慧解決方案的普及。當地企業正在採用擴充性的平台來滿足其不斷成長的數位化需求。不斷擴展的數位生態系統正在強化人工智慧在企業現代化進程中的作用。

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目錄

第1章執行摘要

第2章 前言

  • 摘要
  • 相關利益者
  • 調查範圍
  • 調查方法
  • 研究材料

第3章 市場趨勢分析

  • 促進要素
  • 抑制因素
  • 機會
  • 威脅
  • 技術分析
  • 終端用戶分析
  • 新興市場
  • 新冠疫情的感染疾病

第4章 波特五力分析

  • 供應商的議價能力
  • 買方的議價能力
  • 替代品的威脅
  • 新進入者的威脅
  • 競爭對手之間的競爭

5. 全球生成式人工智慧平台市場（按組件分類）

  • 平台軟體
  • 服務
    • 諮詢服務
    • 整合和實施服務
    • 託管服務
    • 培訓和支援服務
    • 分析和監控工具
  • 其他部件

6. 全球生成式人工智慧平台市場（依組織規模分類）

  • 中小企業
  • 主要企業

7. 全球生成式人工智慧平台市場（按部署類型分類）

  • 本地部署
  • 基於雲端的

8. 全球生成式人工智慧平台市場（按技術分類）

  • 自然語言處理（NLP）模型
  • 電腦視覺模型
  • 生成對抗網路（GAN）
  • 基於變壓器的模型（大規模語言模型、擴散模型）
  • 多模態生成式人工智慧平台
  • 強化學習模型
  • 其他技術

9. 全球生成式人工智慧平台市場（按最終用戶分類）

  • 醫療保健和生命科學
  • 零售與電子商務
  • 媒體與娛樂
  • 製造與工業設計
  • 教育/研究
  • 其他最終用戶

第10章 全球生成式人工智慧平台市場（按地區分類）

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 義大利
    • 法國
    • 西班牙
    • 其他歐洲
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳洲
    • 紐西蘭
    • 韓國
    • 其他亞太地區
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 其他南美國家
  • 中東和非洲
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 卡達
    • 南非
    • 其他中東和非洲地區

第11章 重大進展

  • 協議、夥伴關係、合作和合資企業
  • 併購
  • 新產品發布
  • 業務拓展
  • 其他關鍵策略

第12章 企業概況

  • 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.