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市場調查報告書

商品編碼

2021623

生成式人工智慧市場預測至2034年—按組件、模式、應用、最終用戶和地區分類的全球分析

Generative AI Market Forecasts to 2034 - Global Analysis By Component (Software and Services), Modality, Application, End User and By Geography

出版日期: 2026年04月17日 | 出版商:

Stratistics Market Research Consulting | 英文 | 商品交期: 2-3個工作天內

價格

簡介目錄圖表

根據 Stratistics MRC 的數據，預計到 2026 年，全球生成式人工智慧市場規模將達到 285 億美元，並在預測期內以 34.8% 的複合年成長率成長，到 2034 年將達到 3,102 億美元。

生成式人工智慧是人工智慧的一個分支，它透過分析現有資料集中的模式來產生文字、圖像、音訊和影片等新內容。與主要專注於預測和分析的傳統人工智慧不同，生成式人工智慧能夠產生類似於人類創造力的獨特結果。透過利用大規模語言模型和生成對抗網路（GAN）等技術，生成式人工智慧可以生成逼真且有意義的內容。在媒體、廣告、醫療保健和設計等領域，生成式人工智慧的應用正在不斷擴展，以提高效率、創新流程並推動創新，從根本上改變內容創作和創新工作流程。

根據麥肯錫和Gartner的預測，生成式人工智慧市場規模預計將從2022年的80億美元成長到2026年的670億美元，目前已有72%的公司實施了某種形式的生成式人工智慧。這種快速成長表明，生成式人工智慧是發展最快的技術領域之一。

對自動化內容創作的需求日益成長

對高效、經濟且高品質內容日益成長的需求正在加速生成式人工智慧（AI）的普及應用。廣告、媒體和娛樂等行業正在部署AI驅動的解決方案，以實現報導、圖片、影片和線上貼文的自動化生成。這種自動化最大限度地減少了人工投入，提高了效率，並確保了內容傳送。此外，它還能提供針對不同受眾的客製化內容，進而提升用戶參與度和品牌忠誠度。數位內容需求的激增，以及企業對擴充性創新解決方案的需求，是推動生成式AI技術在各個領域發展和應用的主要動力。

對資料隱私和安全的擔憂

生成式人工智慧依賴海量資料集，這帶來了嚴峻的隱私和安全挑戰。企業在處理敏感客戶資料和機密資訊時必須遵守 GDPR 和 CCPA 等法規。資料外洩、濫用或誤用人工智慧產生的成果等風險可能導致法律責任，並損害公司聲譽。這些資料安全隱患使得企業在全面部署生成式人工智慧解決方案時猶豫不決。解決這些問題通常需要對安全基礎設施進行額外投資，這可能導致部署延遲，並成為生成式人工智慧技術更廣泛應用的主要障礙。

醫療和生命科學領域的擴張

醫療和生命科學領域為生成式人工智慧提供了巨大的機遇，尤其是在藥物研發、診斷、醫學影像和個人化醫療方面。人工智慧系統能夠分析大量數據，從而發現模式、加速研究並最佳化治療方法。生成式人工智慧還能實現報告自動產生、建立虛擬患者模型以及為臨床試驗提供預測性見解。這些應用能夠提高效率、縮短研究週期並降低成本。隨著醫療機構擴大採用人工智慧技術，生成式人工智慧有望變革醫療和生命科學領域的病患照護模式，加速創新，並簡化營運流程。

濫用以傳播虛假訊息和深度造假

生成式人工智慧有被濫用的風險，可能被用於製造虛假新聞、欺騙性內容和逼真的深度造假媒體。惡意使用可能影響政治、金融或社會穩定，導致聲譽受損、法律糾紛和公眾信任度下降。人工智慧產生的虛假資訊的快速傳播會擾亂輿論、破壞商業和金融市場，並引發社會動盪。為了減輕這些威脅，政府和組織需要建立檢測系統並執行倫理標準。生成式人工智慧的潛在濫用風險是一個嚴峻的挑戰，它威脅著公眾信任以及人工智慧技術在各個領域的安全應用。

新冠疫情的影響：

新冠疫情顯著加速了生成式人工智慧（AI）的普及應用，各組織紛紛轉向數位化技術，以應對封鎖和遠距辦公帶來的營運挑戰。人工智慧解決方案被廣泛應用於內容生成、虛擬支援、客戶服務和業務任務自動化等領域。在醫療保健領域，生成式人工智慧輔助進行調查、診斷和預測分析，協助應對疫情帶來的挑戰。這場危機凸顯了擴充性智慧技術的價值，促使各方加大對人工智慧研發和基礎設施的投資。因此，新冠疫情起到了催化劑的作用，加速了人們對生成式人工智慧工具的認知、應用和部署，使其在全球各行各業得到廣泛應用。

在預測期內，文本細分市場預計將佔據最大的市場佔有率。

預計在預測期內，文本領域將佔據最大的市場佔有率，這主要得益於其在行銷、客戶支援、內容創作和教育工具等領域的廣泛應用。人工智慧聊天機器人、虛擬助理和自動寫作平台等解決方案因其高效性、擴充性和產生自然流暢、類人文字的能力而日益普及。企業正在採用這些工具來提高溝通、互動和工作流程的效率。與其他領域（例如圖像和影片生成）相比，文字人工智慧解決方案更易於使用且用途更廣泛，這使得文字領域成為生成式人工智慧應用的最大推動力，也是全球市場成長的主要驅動力。

在預測期內，醫療保健和生命科學產業預計將呈現最高的複合年成長率。

在預測期內，醫療保健和生命科學領域預計將呈現最高的成長率，這主要得益於人工智慧在藥物研發、診斷、個人化醫療和臨床研究等領域的廣泛應用。生成式人工智慧能夠快速分析大規模資料集，提供預測性洞察，並產生合成數據，從而提高效率並加速治療方法研發。對人工智慧解決方案的需求不斷成長，這些解決方案旨在改善患者照護、自動化行政任務並簡化醫療工作流程，從而推動市場擴張。隨著技術的持續創新和對人工智慧應用投入的不斷增加，醫療保健和生命科學領域有望成為成長最快的細分市場，在全球生成式人工智慧市場中展現出巨大的成長潛力。

市佔率最大的地區：

在整個預測期內，北美預計將保持最大的市場佔有率，這得益於其強大的技術基礎設施、眾多領先的人工智慧公司以及人工智慧在各個領域的廣泛應用。強勁的研發投入、活躍的Start-Ups公司以及政府為促進人工智慧創新而採取的舉措，都為其市場領先地位做出了貢獻。醫療保健、IT、金融和媒體等關鍵產業正在擴大使用生成式人工智慧進行自動化、內容創作和預測分析。該地區的技術成熟度、資金籌措環境和高素質的勞動力，共同使北美成為全球生成式人工智慧應用的最大驅動力，以及人工智慧主導成長和發展的中心樞紐。

複合年成長率最高的地區：

在預測期內，亞太地區預計將呈現最高的複合年成長率，這主要得益於數位化進程的加速、人工智慧投資的增加以及在醫療保健、IT、零售和汽車等行業的廣泛應用。政府的支持性舉措正在刺激人工智慧的研究和創新，而企業和Start-Ups則正在利用生成式人工智慧進行內容創作、自動化和預測分析。網際網路連接的改善、技術基礎設施的完善以及高素質的勞動力也為快速成長做出了貢獻。經濟發展、有利的政策以及不斷擴大的技術應用共同推動了亞太地區成為生成式人工智慧成長最快的區域市場，為人工智慧解決方案的全球擴張和應用提供了巨大的機會。

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所有購買此報告的客戶均可享受以下免費自訂選項之一：

企業概況
- 對其他市場參與者（最多 3 家公司）進行全面分析
- 對主要企業進行SWOT分析（最多3家公司）
區域細分
- 應客戶要求，我們提供主要國家和地區的市場估算和預測，以及複合年成長率（註：需進行可行性檢查）。
競爭性標竿分析
- 根據產品系列、地理覆蓋範圍和策略聯盟對主要企業進行基準分析。

北美洲
- 美國
- 加拿大
- 墨西哥
歐洲
- 英國
- 德國
- 法國
- 義大利
- 西班牙
- 荷蘭
- 比利時
- 瑞典
- 瑞士
- 波蘭
- 其他歐洲國家
亞太地區
- 中國
- 日本
- 印度
- 韓國
- 澳洲
- 印尼
- 泰國
- 馬來西亞
- 新加坡
- 越南
- 其他亞太國家
南美洲
- 巴西
- 阿根廷
- 哥倫比亞
- 智利
- 秘魯
- 其他南美國家
世界其他地區（RoW）
- 中東
  - 沙烏地阿拉伯
  - 阿拉伯聯合大公國
  - 卡達
  - 以色列
  - 其他中東國家
- 非洲
  - 南非
  - 埃及
  - 摩洛哥
  - 其他非洲國家

第10章戰略市場資訊

工業價值網路和供應鏈評估
空白區域和機會地圖
產品演進與市場生命週期分析
通路、經銷商和打入市場策略的評估

第11章產業趨勢與策略舉措

併購
夥伴關係、聯盟和合資企業
新產品發布和認證
擴大生產能力和投資
其他策略舉措

第12章：公司簡介

Microsoft
Google
IBM
NVIDIA
OpenAI
Anthropic
Meta
AWS
Adobe
Salesforce
Oracle
AMD
HPE
Accenture
Capgemini
Cohere
Stability AI
Midjourney

簡介目錄圖表

Product Code: SMRC34963

According to Stratistics MRC, the Global Generative AI Market is accounted for $28.5 billion in 2026 and is expected to reach $310.2 billion by 2034 growing at a CAGR of 34.8% during the forecast period. Generative AI is a branch of artificial intelligence that creates novel content like text, visuals, audio, and video by analyzing patterns in existing datasets. Unlike conventional AI that primarily predicts or analyzes, generative AI produces original outputs resembling human creativity. Utilizing technologies such as large language models and generative adversarial networks, it can generate realistic and meaningful content. Sectors including media, advertising, healthcare, and design are increasingly employing generative AI to boost efficiency, automate creative processes, and drive innovation, fundamentally transforming content creation and creative workflows.

According to McKinsey and Gartner, the generative AI market is projected to reach $67 billion by 2026, up from $8 billion in 2022, with 72% of enterprises already adopting generative AI in some form. This rapid growth underscores its position as one of the fastest-expanding technology sectors.

Market Dynamics:

Driver:

Growing demand for automated content creation

Rising requirements for efficient, affordable, and top-quality content are accelerating generative AI adoption. Industries such as advertising, media, and entertainment employ AI-powered solutions to automate the creation of articles, visuals, videos, and online posts. This automation minimizes human effort, boosts efficiency, and ensures consistent content delivery. Additionally, it enables tailored content for different audiences, enhancing interaction and brand loyalty. The surge in digital content needs, combined with businesses seeking scalable creative solutions, acts as a key driver propelling the growth and integration of generative AI technologies across multiple sectors.

Restraint:

Data privacy and security concerns

Generative AI depends on extensive datasets, which creates serious privacy and security challenges. Companies must adhere to regulations such as GDPR and CCPA when handling sensitive customer or confidential data. Risks of breaches, unauthorized use, or misuse of AI-generated outputs can result in legal consequences and harm a company's reputation. Such data security concerns make organizations hesitant to fully implement generative AI solutions. Addressing these issues often requires additional investments in secure infrastructure, which can slow adoption and act as a significant barrier to the broader integration of generative AI technologies.

Opportunity:

Expansion in healthcare and life sciences

The healthcare and life sciences sector presents immense opportunities for generative AI, particularly in drug development, diagnostics, medical imaging, and personalized care. AI systems can analyze large volumes of data to detect patterns, speed up research, and optimize treatments. Generative AI also automates reports, enables virtual patient modeling, and provides predictive insights for clinical trials. These applications enhance efficiency, cut research timelines, and reduce costs. With healthcare organizations increasingly adopting AI technologies, generative AI has the potential to transform patient treatment, accelerate innovation, and streamline operations within the medical and life sciences domain.

Threat:

Misuse for misinformation and deepfakes

Generative AI poses a risk of being used to generate fake news, deceptive content, and realistic deepfake media. Malicious use can affect politics, finance, or social stability, causing reputational harm, legal issues, and decreased public trust. The rapid spread of AI-created misinformation can sway public opinion, disrupt business or financial markets, and trigger social instability. To mitigate these threats, governments and organizations must implement detection systems and enforce ethical standards. The misuse potential of generative AI represents a serious challenge, threatening public confidence and the safe adoption of AI technologies in various sectors.

Covid-19 Impact:

The COVID-19 pandemic significantly boosted generative AI adoption as organizations turned to digital technologies to sustain operations amid lockdowns and remote working. AI-powered solutions were increasingly employed for automating content generation, virtual support, customer interactions, and operational tasks. In healthcare, generative AI supported research, diagnostics, and predictive analysis to tackle pandemic-related challenges. The crisis underscored the value of scalable and intelligent technologies, prompting higher investments in AI development and infrastructure. Consequently, COVID-19 served as a catalyst for accelerated awareness, adoption, and deployment of generative AI tools, expanding their presence across industries worldwide.

The text segment is expected to be the largest during the forecast period

The text segment is expected to account for the largest market share during the forecast period, driven by widespread use in marketing, customer support, content creation, and educational tools. Solutions like AI chatbots, virtual assistants, and automated writing platforms are popular due to their efficiency, scalability, and ability to produce natural, human-like text. Companies employ these tools to improve communication, engagement, and workflow productivity. Compared to other segments such as image or video generation, text AI solutions are more accessible and versatile, making the text segment the largest contributor to generative AI adoption and a primary factor in driving market growth globally.

The healthcare & life sciences segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the healthcare & life sciences segment is predicted to witness the highest growth rate due to growing use of AI in drug development, diagnostics, personalized medicine, and clinical research. Generative AI facilitates rapid analysis of large datasets, predictive insights, and synthetic data generation, enhancing efficiency and accelerating therapy development. Increasing demand for AI solutions to improve patient care, automate administrative work, and streamline medical workflows drives expansion. Ongoing technological innovation and rising investment in AI adoption position healthcare and life sciences as the fastest-growing segment, demonstrating significant growth potential across the global generative AI market.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share because of its robust technology infrastructure, concentration of top AI companies, and widespread AI adoption in various sectors. Strong R&D investments, vibrant startup activity, and government initiatives fostering AI innovation contribute to market leadership. Key industries such as healthcare, IT, finance, and media are increasingly using generative AI for automation, content generation, and predictive analytics. The region's technological maturity, access to capital, and skilled workforce collectively make North America the largest contributor to global generative AI adoption and a central hub for AI-driven growth and development.

Region with highest CAGR:

Over the forecast period, the Asia-Pacific region is anticipated to exhibit the highest CAGR, driven by accelerated digitalization, rising AI investments, and adoption across sectors like healthcare, IT, retail, and automotive. Supportive government initiatives encourage AI research and innovation, while companies and start-ups utilize generative AI for content generation, automation, and predictive analytics. Improvements in internet access, technological infrastructure, and skilled workforce contribute to rapid growth. Economic development, favourable policies, and increasing technology adoption collectively position Asia-Pacific as the fastest-growing regional market for generative AI, offering significant opportunities for global expansion and adoption of AI-powered solutions.

Key players in the market

Some of the key players in Generative AI Market include Microsoft, Google, IBM, NVIDIA, OpenAI, Anthropic, Meta, AWS, Adobe, Salesforce, Oracle, AMD, HPE, Accenture, Capgemini, Cohere, Stability AI and Midjourney.

Key Developments:

In March 2026, NVIDIA and Marvell Technology, Inc. announced a strategic partnership to connect Marvell to the NVIDIA AI factory and AI-RAN ecosystem through NVIDIA NVLink Fusion(TM), offering customers building on NVIDIA architectures greater choice and flexibility in developing next-generation infrastructure. The companies will also collaborate on silicon photonics technology.

In January 2026, Microsoft Corp has been awarded a $170,444,462 firm-fixed-price task order for the Cloud One Program by the U.S. Department of War. The contract will provide Microsoft Azure cloud service offerings to support the Air Force's Cloud One Program and its customers. Work on the project will be performed at Microsoft's designated facilities across the contiguous United States.

In December 2025, IBM and Confluent, Inc. announced they have entered into a definitive agreement under which IBM will acquire all of the issued and outstanding common shares of Confluent for $31 per share, representing an enterprise value of $11 billion. Confluent provides a leading open-source enterprise data streaming platform that connects processes and governs reusable and reliable data and events in real time, foundational for the deployment of AI.

Components Covered:

Software
Services

Modalities Covered:

Text
Code
Image
Video
Multimodal

Applications Covered:

Content Generation
Search & Discovery
Predictive Analytics & Simulation
Business Intelligence & Visualization
Computer Vision Applications
Natural Language Processing (NLP)
Robotics & Automation

End Users Covered:

Media & Entertainment
Gaming
Banking, Financial Services & Insurance (BFSI)
IT & Telecommunications
Healthcare & Life Sciences
Automotive & Transportation
Retail & E-Commerce
Education
Government & Public Sector

Regions Covered:

North America
- United States
- Canada
- Mexico
Europe
- United Kingdom
- Germany
- France
- Italy
- Spain
- Netherlands
- Belgium
- Sweden
- Switzerland
- Poland
- Rest of Europe
Asia Pacific
- China
- Japan
- India
- South Korea
- Australia
- Indonesia
- Thailand
- Malaysia
- Singapore
- Vietnam
- Rest of Asia Pacific
South America
- Brazil
- Argentina
- Colombia
- Chile
- Peru
- Rest of South America
Rest of the World (RoW)
- Middle East
Saudi Arabia
United Arab Emirates
Qatar
Israel
Rest of Middle East
- Africa
South Africa
Egypt
Morocco
Rest of 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 2023, 2024, 2025, 2026, 2027, 2028, 2030, 2032 and 2034
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

1 Executive Summary

1.1 Market Snapshot and Key Highlights
1.2 Growth Drivers, Challenges, and Opportunities
1.3 Competitive Landscape Overview
1.4 Strategic Insights and Recommendations

2 Research Framework

2.1 Study Objectives and Scope
2.2 Stakeholder Analysis
2.3 Research Assumptions and Limitations
2.4 Research Methodology
- 2.4.1 Data Collection (Primary and Secondary)
- 2.4.2 Data Modeling and Estimation Techniques
- 2.4.3 Data Validation and Triangulation
- 2.4.4 Analytical and Forecasting Approach

3 Market Dynamics and Trend Analysis

3.1 Market Definition and Structure
3.2 Key Market Drivers
3.3 Market Restraints and Challenges
3.4 Growth Opportunities and Investment Hotspots
3.5 Industry Threats and Risk Assessment
3.6 Technology and Innovation Landscape
3.7 Emerging and High-Growth Markets
3.8 Regulatory and Policy Environment
3.9 Impact of COVID-19 and Recovery Outlook

4 Competitive and Strategic Assessment

4.1 Porter's Five Forces Analysis
- 4.1.1 Supplier Bargaining Power
- 4.1.2 Buyer Bargaining Power
- 4.1.3 Threat of Substitutes
- 4.1.4 Threat of New Entrants
- 4.1.5 Competitive Rivalry
4.2 Market Share Analysis of Key Players
4.3 Product Benchmarking and Performance Comparison

5 Global Generative AI Market, By Component

5.1 Software
- 5.1.1 Foundation Models
- 5.1.2 APIs & SDKs
- 5.1.3 SaaS Platforms
5.2 Services
- 5.2.1 Consulting
- 5.2.2 Integration
- 5.2.3 Managed Services

6 Global Generative AI Market, By Modality

6.1 Text
6.2 Code
6.3 Image
6.4 Video
6.5 Multimodal

7 Global Generative AI Market, By Application

7.1 Content Generation
7.2 Search & Discovery
7.3 Predictive Analytics & Simulation
7.4 Business Intelligence & Visualization
7.5 Computer Vision Applications
7.6 Natural Language Processing (NLP)
7.7 Robotics & Automation

8 Global Generative AI Market, By End User

8.1 Media & Entertainment
8.2 Gaming
8.3 Banking, Financial Services & Insurance (BFSI)
8.4 IT & Telecommunications
8.5 Healthcare & Life Sciences
8.6 Automotive & Transportation
8.7 Retail & E-Commerce
8.8 Education
8.9 Government & Public Sector

9 Global Generative AI Market, By Geography

9.1 North America
- 9.1.1 United States
- 9.1.2 Canada
- 9.1.3 Mexico
9.2 Europe
- 9.2.1 United Kingdom
- 9.2.2 Germany
- 9.2.3 France
- 9.2.4 Italy
- 9.2.5 Spain
- 9.2.6 Netherlands
- 9.2.7 Belgium
- 9.2.8 Sweden
- 9.2.9 Switzerland
- 9.2.10 Poland
- 9.2.11 Rest of Europe
9.3 Asia Pacific
- 9.3.1 China
- 9.3.2 Japan
- 9.3.3 India
- 9.3.4 South Korea
- 9.3.5 Australia
- 9.3.6 Indonesia
- 9.3.7 Thailand
- 9.3.8 Malaysia
- 9.3.9 Singapore
- 9.3.10 Vietnam
- 9.3.11 Rest of Asia Pacific
9.4 South America
- 9.4.1 Brazil
- 9.4.2 Argentina
- 9.4.3 Colombia
- 9.4.4 Chile
- 9.4.5 Peru
- 9.4.6 Rest of South America
9.5 Rest of the World (RoW)
- 9.5.1 Middle East
  - 9.5.1.1 Saudi Arabia
  - 9.5.1.2 United Arab Emirates
  - 9.5.1.3 Qatar
  - 9.5.1.4 Israel
  - 9.5.1.5 Rest of Middle East
- 9.5.2 Africa
  - 9.5.2.1 South Africa
  - 9.5.2.2 Egypt
  - 9.5.2.3 Morocco
  - 9.5.2.4 Rest of Africa

10 Strategic Market Intelligence

10.1 Industry Value Network and Supply Chain Assessment
10.2 White-Space and Opportunity Mapping
10.3 Product Evolution and Market Life Cycle Analysis
10.4 Channel, Distributor, and Go-to-Market Assessment

11 Industry Developments and Strategic Initiatives

11.1 Mergers and Acquisitions
11.2 Partnerships, Alliances, and Joint Ventures
11.3 New Product Launches and Certifications
11.4 Capacity Expansion and Investments
11.5 Other Strategic Initiatives

12 Company Profiles

12.1 Microsoft
12.2 Google
12.3 IBM
12.4 NVIDIA
12.5 OpenAI
12.6 Anthropic
12.7 Meta
12.8 AWS
12.9 Adobe
12.10 Salesforce
12.11 Oracle
12.12 AMD
12.13 HPE
12.14 Accenture
12.15 Capgemini
12.16 Cohere
12.17 Stability AI
12.18 Midjourney

簡介目錄圖表

List of Tables

Table 1 Global Generative AI Market Outlook, By Region (2023-2034) ($MN)
Table 2 Global Generative AI Market Outlook, By Component (2023-2034) ($MN)
Table 3 Global Generative AI Market Outlook, By Software (2023-2034) ($MN)
Table 4 Global Generative AI Market Outlook, By Foundation Models (2023-2034) ($MN)
Table 5 Global Generative AI Market Outlook, By APIs & SDKs (2023-2034) ($MN)
Table 6 Global Generative AI Market Outlook, By SaaS Platforms (2023-2034) ($MN)
Table 7 Global Generative AI Market Outlook, By Services (2023-2034) ($MN)
Table 8 Global Generative AI Market Outlook, By Consulting (2023-2034) ($MN)
Table 9 Global Generative AI Market Outlook, By Integration (2023-2034) ($MN)
Table 10 Global Generative AI Market Outlook, By Managed Services (2023-2034) ($MN)
Table 11 Global Generative AI Market Outlook, By Modality (2023-2034) ($MN)
Table 12 Global Generative AI Market Outlook, By Text (2023-2034) ($MN)
Table 13 Global Generative AI Market Outlook, By Code (2023-2034) ($MN)
Table 14 Global Generative AI Market Outlook, By Image (2023-2034) ($MN)
Table 15 Global Generative AI Market Outlook, By Video (2023-2034) ($MN)
Table 16 Global Generative AI Market Outlook, By Multimodal (2023-2034) ($MN)
Table 17 Global Generative AI Market Outlook, By Application (2023-2034) ($MN)
Table 18 Global Generative AI Market Outlook, By Content Generation (2023-2034) ($MN)
Table 19 Global Generative AI Market Outlook, By Search & Discovery (2023-2034) ($MN)
Table 20 Global Generative AI Market Outlook, By Predictive Analytics & Simulation (2023-2034) ($MN)
Table 21 Global Generative AI Market Outlook, By Business Intelligence & Visualization (2023-2034) ($MN)
Table 22 Global Generative AI Market Outlook, By Computer Vision Applications (2023-2034) ($MN)
Table 23 Global Generative AI Market Outlook, By Natural Language Processing (NLP) (2023-2034) ($MN)
Table 24 Global Generative AI Market Outlook, By Robotics & Automation (2023-2034) ($MN)
Table 25 Global Generative AI Market Outlook, By End User (2023-2034) ($MN)
Table 26 Global Generative AI Market Outlook, By Media & Entertainment (2023-2034) ($MN)
Table 27 Global Generative AI Market Outlook, By Gaming (2023-2034) ($MN)
Table 28 Global Generative AI Market Outlook, By Banking, Financial Services & Insurance (BFSI) (2023-2034) ($MN)
Table 29 Global Generative AI Market Outlook, By IT & Telecommunications (2023-2034) ($MN)
Table 30 Global Generative AI Market Outlook, By Healthcare & Life Sciences (2023-2034) ($MN)
Table 31 Global Generative AI Market Outlook, By Automotive & Transportation (2023-2034) ($MN)
Table 32 Global Generative AI Market Outlook, By Retail & E-Commerce (2023-2034) ($MN)
Table 33 Global Generative AI Market Outlook, By Education (2023-2034) ($MN)
Table 34 Global Generative AI Market Outlook, By Government & Public Sector (2023-2034) ($MN)