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市場調查報告書

商品編碼

2021627

企業生成式人工智慧市場預測（至2034年）：按部署模式、企業規模、應用、最終用戶和地區分類的全球分析

Generative AI in Enterprises Market Forecasts to 2034 - Global Analysis By Deployment Mode (On-Premises, Cloud-Based and Hybrid), Enterprise Size, 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，全球企業生成式人工智慧市場規模將達到 76 億美元，並在預測期內以 33.4% 的複合年成長率成長，到 2034 年將達到 763 億美元。

生成式人工智慧正日益改變企業的營運方式，它簡化了內容創作流程，最佳化了決策流程，並顯著提升了整體生產力。企業正利用生成式人工智慧創建文件、視覺化圖像、軟體程式碼和預測模型，以加速創新週期並縮短產品上市時間。它還透過先進的虛擬助理和建議引擎，實現了個人化的客戶互動，同時幫助員工獲取資訊並實現日常任務的自動化。為了保持競爭優勢，企業正在行銷、設計和支援等各部門部署生成式人工智慧。

根據印度工業聯合會 (CII) 和安永會計師事務所的數據，近一半的印度公司 (47%) 已經在使用多種生成式人工智慧用例，這標誌著從試點階段到企業級部署的重大轉變。

對自動化和效率的需求日益成長

對自動化和效率日益成長的需求正推動企業採用生成式人工智慧 (AI)。透過處理文件建立、編碼和設計等重複性任務，生成式人工智慧可以減少對人工的依賴，並將錯誤降至最低。這種轉變使員工能夠專注於更具策略性的任務，從而提高生產力。自動化也有助於業務擴充性，而不會顯著增加人事費用。在競爭日益激烈的產業環境中，各組織都在投資能夠最佳化工作流程和資源利用的解決方案。生成式人工智慧已成為企業簡化營運、在快速變化的商業環境中保持強大競爭優勢的關鍵驅動力。

對資料隱私和安全的擔憂

資料保護和安全問題是企業採用生成式人工智慧的主要障礙。由於這些技術依賴海量敏感數據，因此會增加資料外洩、濫用和機密資訊外洩的風險。監管合規要求進一步加劇了複雜性並增加了成本。使用外部人工智慧平台也可能帶來額外的安全漏洞。許多組織因擔心失去對自身數據和智慧財產權的控制權而猶豫不決，導致儘管生成式人工智慧具有顯著的營運和創新優勢，但其應用仍然有限。

客戶支援自動化方面的進展

透過自動化提升客戶服務，生成式人工智慧（AI）帶來了巨大的機會。企業可以部署先進的虛擬助手，即時提供準確且與上下文相關的回复，從而加快服務速度、降低成本並提升客戶體驗。透過自動化系統處理日常諮詢，人工負責人可以專注於更複雜的問題。隨著時間的推移，這些AI工具會不斷學習並提升效能。隨著企業致力於提供高品質的客戶體驗，生成式AI提供了一種有效的方式，可以在各種通訊平台上提供個人化、持續且擴充性的支援。

資料外洩和網路攻擊的風險

網路攻擊和資料外洩風險的日益增加，對企業部署生成式人工智慧構成了嚴重威脅。由於這些系統依賴大量敏感數據，因此極易成為駭客覬覦的目標，他們試圖未授權存取這些系統。諸如提示之類的技術也可能擾亂系統運作和輸出。企業需要實施強大的安全框架，這增加了複雜性和成本。隨著網路威脅日益複雜，維護人工智慧系統的安全也變得越來越困難。這種持續存在的風險會削弱信任，並阻礙生成式人工智慧在企業營運中的廣泛應用。

新冠疫情的影響：

隨著企業向數位化和遠距辦公模式轉型，新冠疫情在加速企業採用生成式人工智慧方面發揮了至關重要的作用。各組織利用這些技術來簡化流程、改善線上客戶參與，並在不確定的環境下做出明智的決策。隨著對數位平台的依賴性增強，對人工智慧產生的內容、虛擬助理和分析洞察的需求也日益成長。儘管一些行業由於資金限制而發展滯後，但許多公司已經認知到先進技術的價值。整體而言，疫情加速了數位轉型，並展現了生成式人工智慧如何支援柔軟性、效率和業務永續營運。

在預測期內，基於雲端的細分市場預計將成為規模最大的市場。

由於其柔軟性、擴充性和較低的前期成本，預計在預測期內，基於雲端的細分市場將佔據最大的市場佔有率。企業更傾向於選擇雲端平台，因為它可以減少對昂貴硬體的需求，並提供強大的AI工具和處理能力。這些解決方案支援快速部署、定期更新，並能與現有系統無縫整合。它們還支援遠距辦公，非常適合當今的分散式辦公模式。此外，雲端服務還包含強大的安全措施和資料管理功能，從而提高了可靠性和確定性。

在預測期內，醫療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，這主要得益於醫療研究和患者照護對創新解決方案日益成長的需求。生成式人工智慧有助於分析複雜的資料集，提高診斷準確性，並加速藥物研發進程。它還能產生合成數據，並在人工智慧系統訓練過程中保障隱私。對數位醫療投資的增加以及對更有效率服務的追求，進一步推動了生成式人工智慧的應用。因此，該領域正成為企業生成式人工智慧領域成長最快的方向。

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，這得益於其先進的技術基礎設施和較高的數位化普及率。該地區的企業正積極專注於研發，以避免競爭。雲端平台、數據舉措和自動化技術的廣泛應用，使得生成式人工智慧得以在各個領域無縫整合。政府的支持和資助計畫也進一步加速了人工智慧的研發和應用。

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，這主要得益於技術的快速發展和數位化進程的推進。許多國家正在大力投資人工智慧，旨在提高效率並促進創新。雲端運算的成長、新創企業生態系統的擴張以及各行業對自動化需求的不斷成長都推動了這一趨勢。政府的支持性政策和數位轉型措施也進一步促進了人工智慧的普及應用。

免費客製化服務：

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
- 對主要公司進行SWOT分析（最多3家公司）
區域分類
- 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重點公司進行基準分析。

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、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

OpenAI
Microsoft
Google
NVIDIA
IBM
Amazon Web Services（AWS）
Anthropic
Adobe
Salesforce
Oracle
Jasper.ai
H2O.ai
Intel
Meta
Accenture
Cohere
Hugging Face
Perplexity AI

簡介目錄圖表

Product Code: SMRC34967

According to Stratistics MRC, the Global Generative AI in Enterprises Market is accounted for $7.6 billion in 2026 and is expected to reach $76.3 billion by 2034 growing at a CAGR of 33.4% during the forecast period. Generative AI is increasingly reshaping businesses by streamlining content production, strengthening decision processes, and boosting overall productivity. Companies use it to create written material, visuals, software code, and predictive models, accelerating innovation cycles and shortening product launch timelines. It enables tailored customer interactions via advanced virtual assistants and recommendation engines, while helping staff access information and automate routine tasks. Firms are embedding generative AI across departments including marketing, design, and support to stay competitive.

According to the Confederation of Indian Industry (CII) and EY, nearly half of Indian enterprises (47%) already have multiple generative AI use cases in production, marking a significant shift from pilots to enterprise-scale adoption.

Market Dynamics:

Driver:

Increasing demand for automation and efficiency

The growing need for automation and improved efficiency is pushing enterprises toward generative AI adoption. By handling repetitive tasks such as document creation, coding, and design, it lowers reliance on manual work and reduces errors. This shift enables employees to concentrate on more strategic responsibilities, enhancing productivity. Automation also supports business scalability without significantly increasing labor expenses. As industries become more competitive, organizations are investing in solutions that optimize workflows and resource usage. Generative AI stands out as a key enabler, helping companies streamline operations and sustain a strong competitive position in rapidly evolving business landscapes.

Restraint:

Data privacy and security concerns

Concerns around data protection and security are a major barrier to the adoption of generative AI in enterprises. Since these technologies rely on vast amounts of sensitive data, they increase the risk of breaches, unauthorized usage, and exposure of confidential information. Regulatory compliance requirements further complicate deployment and add to costs. Using external AI platforms can also create additional security vulnerabilities. Fear of losing control over proprietary data and intellectual property prevents many organizations from embracing generative AI fully, thereby restricting its growth even though it offers significant operational and innovation benefits.

Opportunity:

Advancements in customer support automation

Improving customer service through automation is a key opportunity enabled by generative AI. Companies can implement sophisticated virtual assistants that provide accurate and context-aware responses instantly. This leads to faster service, lower costs, and better customer experiences. Automated systems can manage routine inquiries, allowing human representatives to address more complicated problems. Over time, these AI tools learn and improve their performance. As organizations focus on delivering high-quality customer experiences, generative AI offers an effective way to provide personalized, continuous, and scalable support across various communication platforms.

Threat:

Risk of data breaches and cyberattacks

The growing risk of cyberattacks and data breaches presents a serious threat to generative AI adoption in enterprises. Since these systems depend on extensive sensitive data, they become attractive targets for hackers seeking unauthorized access. Techniques such as prompt manipulation can also disrupt system behavior and outputs. Organizations are required to implement strong security frameworks, which increases complexity and cost. As cyber threats continue to evolve in sophistication, maintaining the safety of AI systems becomes more challenging. This ongoing risk can reduce trust and hinder the broader deployment of generative AI across enterprise operations.

Covid-19 Impact:

The COVID-19 outbreak played a crucial role in boosting the adoption of generative AI across enterprises as companies transitioned to digital and remote working models. Organizations utilized these technologies to streamline processes, improve online customer engagement, and make informed decisions amid uncertainty. Growing dependence on digital platforms increased the need for AI-generated content, virtual assistants, and analytical insights. While some industries faced financial limitations that delayed investments, many businesses recognized the value of advanced technologies. In general, the pandemic accelerated digital transformation and demonstrated how generative AI can support flexibility, efficiency, and business continuity.

The cloud-based segment is expected to be the largest during the forecast period

The cloud-based segment is expected to account for the largest market share during the forecast period because of its flexibility, scalability, and lower initial costs. Businesses favor cloud platforms since they reduce the need for expensive hardware and provide access to powerful AI tools and processing capabilities. These solutions allow quick implementation, regular updates, and smooth integration with current systems. They also support remote operations, fitting well with today's distributed workforce models. Furthermore, cloud services include strong security measures and data management capabilities, enhancing trust and reliability.

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, driven by rising demand for innovative solutions in medical research and patient care. Generative AI assists in analyzing complex datasets, improving diagnostics, and speeding up drug development processes. It also enables the creation of synthetic data, ensuring privacy while training AI systems. Increasing investments in digital healthcare and the push for more efficient services are further fueling adoption. As a result, this segment is emerging as the highest-growing area within the enterprise generative AI landscape.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share, supported by advanced technology infrastructure and a high level of digital adoption. Companies in this region aктивнo focus on research and innovation to stay competitive. The extensive use of cloud platforms, data analytics, and automation enables seamless integration of generative AI across various sectors. Government support and funding initiatives further accelerate development and deployment.

Region with highest CAGR:

Over the forecast period, the Asia-Pacific region is anticipated to exhibit the highest CAGR, driven by rapid technological advancement and increasing digital adoption. Many countries are making significant investments in AI to improve efficiency and foster innovation. The growth of cloud computing, expanding start-up ecosystems, and rising need for automation across sectors contribute to this trend. Supportive government policies and digital transformation initiatives further boost adoption.

Key players in the market

Some of the key players in Generative AI in Enterprises Market include OpenAI, Microsoft, Google, NVIDIA, IBM, Amazon Web Services (AWS), Anthropic, Adobe, Salesforce, Oracle, Jasper.ai, H2O.ai, Intel, Meta, Accenture, Cohere, Hugging Face and Perplexity AI.

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 November 2025, Amazon Web Services (AWS) and OpenAI announced a multi-year, strategic partnership that provides AWS's world-class infrastructure to run and scale OpenAI's core artificial intelligence (AI) workloads starting immediately. Under this new $38 billion agreement, which will have continued growth over the next seven years, OpenAI is accessing AWS compute comprising hundreds of thousands of state-of-the-art NVIDIA GPUs, with the ability to expand to tens of millions of CPUs to rapidly scale agentic workloads.

Deployment Modes Covered:

On-Premises
Cloud-Based
Hybrid

Enterprise Sizes Covered:

Large Enterprises
SMEs

Applications Covered:

Customer Experience & Support
Content Creation & Marketing
Software Development & IT Operations
Knowledge Management
Risk & Compliance
HR & Workforce Enablement

End Users Covered:

BFSI (Banking, Financial Services, Insurance)
Healthcare & Life Sciences
Retail & E-commerce
Manufacturing & Supply Chain
IT & Telecom
Government & Public Sector
Education

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 in Enterprises Market, By Deployment Mode

5.1 On-Premises
5.2 Cloud-Based
5.3 Hybrid

6 Global Generative AI in Enterprises Market, By Enterprise Size

6.1 Large Enterprises
6.2 SMEs

7 Global Generative AI in Enterprises Market, By Application

7.1 Customer Experience & Support
7.2 Content Creation & Marketing
7.3 Software Development & IT Operations
7.4 Knowledge Management
7.5 Risk & Compliance
7.6 HR & Workforce Enablement

8 Global Generative AI in Enterprises Market, By End User

8.1 BFSI (Banking, Financial Services, Insurance)
8.2 Healthcare & Life Sciences
8.3 Retail & E-commerce
8.4 Manufacturing & Supply Chain
8.5 IT & Telecom
8.6 Government & Public Sector
8.7 Education

9 Global Generative AI in Enterprises 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 OpenAI
12.2 Microsoft
12.3 Google
12.4 NVIDIA
12.5 IBM
12.6 Amazon Web Services (AWS)
12.7 Anthropic
12.8 Adobe
12.9 Salesforce
12.10 Oracle
12.11 Jasper.ai
12.12 H2O.ai
12.13 Intel
12.14 Meta
12.15 Accenture
12.16 Cohere
12.17 Hugging Face
12.18 Perplexity AI

簡介目錄圖表

List of Tables

Table 1 Global Generative AI in Enterprises Market Outlook, By Region (2023-2034) ($MN)
Table 2 Global Generative AI in Enterprises Market Outlook, By Deployment Mode (2023-2034) ($MN)
Table 3 Global Generative AI in Enterprises Market Outlook, By On-Premises (2023-2034) ($MN)
Table 4 Global Generative AI in Enterprises Market Outlook, By Cloud-Based (2023-2034) ($MN)
Table 5 Global Generative AI in Enterprises Market Outlook, By Hybrid (2023-2034) ($MN)
Table 6 Global Generative AI in Enterprises Market Outlook, By Enterprise Size (2023-2034) ($MN)
Table 7 Global Generative AI in Enterprises Market Outlook, By Large Enterprises (2023-2034) ($MN)
Table 8 Global Generative AI in Enterprises Market Outlook, By SMEs (2023-2034) ($MN)
Table 9 Global Generative AI in Enterprises Market Outlook, By Application (2023-2034) ($MN)
Table 10 Global Generative AI in Enterprises Market Outlook, By Customer Experience & Support (2023-2034) ($MN)
Table 11 Global Generative AI in Enterprises Market Outlook, By Content Creation & Marketing (2023-2034) ($MN)
Table 12 Global Generative AI in Enterprises Market Outlook, By Software Development & IT Operations (2023-2034) ($MN)
Table 13 Global Generative AI in Enterprises Market Outlook, By Knowledge Management (2023-2034) ($MN)
Table 14 Global Generative AI in Enterprises Market Outlook, By Risk & Compliance (2023-2034) ($MN)
Table 15 Global Generative AI in Enterprises Market Outlook, By HR & Workforce Enablement (2023-2034) ($MN)
Table 16 Global Generative AI in Enterprises Market Outlook, By End User (2023-2034) ($MN)
Table 17 Global Generative AI in Enterprises Market Outlook, By BFSI (Banking, Financial Services, Insurance) (2023-2034) ($MN)
Table 18 Global Generative AI in Enterprises Market Outlook, By Healthcare & Life Sciences (2023-2034) ($MN)
Table 19 Global Generative AI in Enterprises Market Outlook, By Retail & E-commerce (2023-2034) ($MN)
Table 20 Global Generative AI in Enterprises Market Outlook, By Manufacturing & Supply Chain (2023-2034) ($MN)
Table 21 Global Generative AI in Enterprises Market Outlook, By IT & Telecom (2023-2034) ($MN)
Table 22 Global Generative AI in Enterprises Market Outlook, By Government & Public Sector (2023-2034) ($MN)
Table 23 Global Generative AI in Enterprises Market Outlook, By Education (2023-2034) ($MN)