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市场调查报告书

商品编码

1664839

MLOps 市场机会、成长动力、产业趋势分析与 2025 - 2034 年预测

MLOps Market Opportunity, Growth Drivers, Industry Trend Analysis, and Forecast 2025 - 2034

出版日期: 2024年12月02日 | 出版商:

Global Market Insights Inc. | 英文 180 Pages | 商品交期: 2-3个工作天内

价格

简介目录

2024 年全球 MLOps 市场价值为 17 亿美元，预计 2025 年至 2034 年期间复合年增长率将达到 37.4%。向云端运算的转变日益成为主要驱动力，因为云端平台提供了有效管理大量资料集和复杂机器学习工作流程所需的可扩展性和灵活性。

基于云端的 MLOps 解决方案使组织能够在多个环境中无缝部署模型。这种方法消除了对大量内部部署基础架构的需求，同时提供了增强的效能和可扩展性。透过利用这些解决方案，企业可以简化机器学习操作并以更高的效率适应不断变化的需求。

市场范围
起始年份	2024
预测年份	2025-2034
起始值	17亿美元
预测值	390亿美元
复合年增长率	37.4％

对于旨在保持竞争优势的组织来说，缩短新的机器学习模型的上市时间已经成为关键的优先事项。 MLOps 平台透过持续整合和持续部署 (CI/CD) 实现开发、测试和部署流程的自动化，从而实现这一点。这种自动化可以加速工作流程、最大限度地减少人工干预并确保模型保持可扩展且持续更新。

MLOps 市场按组件细分为平台和服务。 2024 年，平台引领市场，占据 72% 的总份额。这种主导地位源于对统一资料管道管理、模型部署、实验追踪和效能监控的端到端解决方案日益增长的需求。综合平台越来越受到寻求扩展人工智慧计画同时简化工作流程的企业的青睐。

咨询、整合和託管服务等服务也正在经历显着的成长。这些服务可协助组织克服云端迁移、基础架构最佳化和合规性要求等采用挑战。客製化指导需求的增加凸显了 MLOps 生态系统中专家支援的重要性。

根据最终用途，市场分为大型企业和中小型企业。 2024 年，大型企业占据了 64.3% 的市场份额，这得益于采用 MLOps 解决方案来优化 AI 工作流程、增强预测分析和改善治理。同时，中小企业正在迅速采用具有成本效益、用户友好的工具，以使其能够实现流程自动化并促进创新。人工智慧工具的日益普及支持了这一趋势，使得小型企业无需进行大量的基础设施投资即可实现可扩展性。

在北美，美国引领 MLOps 市场，预计到 2034 年将超过 110 亿美元。对云端基础设施和高效能运算的投资进一步推动了MLOps解决方案的采用，帮助企业改善模型营运并缩短部署时间。

报告内容

第 1 章：方法论与范围

研究设计
- 研究方法
- 资料收集方法
基础估计和计算
- 基准年计算
- 市场估计的主要趋势
预测模型
初步研究与验证
- 主要来源
- 资料探勘来源
市场定义

第 2 章：执行摘要

第 3 章：产业洞察

产业生态系统分析
- 技术提供者
- 模型开发与训练平台
- 资料管理提供者
- 模型部署和治理提供者
- 最终用户
供应商概况
利润率分析
MLOps 的用例
技术与创新格局
重要新闻及倡议
监管格局
衝击力
- 成长动力
  - 人工智慧和机器学习的采用率提高
  - 对更快模型部署的需求
  - 监理合规和模型治理
  - 云端采用和可扩展性
- 产业陷阱与挑战
  - 资料隐私和安全问题
  - 缺乏熟练的专业人员
成长潜力分析
波特的分析
PESTEL 分析

第四章：竞争格局

介绍
公司市占率分析
竞争定位矩阵
战略展望矩阵

第五章：市场估计与预测：按组件，2021 - 2034 年

主要趋势
平台
服务

第六章：市场估计与预测：依部署模式，2021 - 2034 年

主要趋势
基于云端
本地

第 7 章：市场估计与预测：依最终用途，2021 年至 2034 年

主要趋势
大型企业
中小企业

第 8 章：市场估计与预测：按垂直产业，2021 - 2034 年

主要趋势
卫生保健
零售与电子商务
製造与供应链
金融保险业协会
其他的

第 9 章：市场估计与预测：按地区，2021 - 2034 年

主要趋势
北美洲
- 我们
- 加拿大
欧洲
- 英国
- 德国
- 法国
- 西班牙
- 义大利
- 俄罗斯
- 北欧
亚太地区
- 中国
- 印度
- 日本
- 韩国
- 澳新银行
- 东南亚
拉丁美洲
- 巴西
- 墨西哥
- 阿根廷
中东及非洲
- 阿联酋
- 南非
- 沙乌地阿拉伯

第十章：公司简介

Alteryx
Amazon Web Services (AWS)
Atos
Capgemini
Cisco
Cloudera
Databricks
Google Cloud
H2O.ai
IBM
Microsoft
NVIDIA
Oracle
Red Hat
Salesforce
SAP
Siemens
TIBCO Software
VMware
Weights & Biases

简介目录

Product Code: 12478

The Global MLOps Market was valued at USD 1.7 billion in 2024 and is forecasted to grow at a robust CAGR of 37.4% from 2025 to 2034. The increasing shift towards cloud computing serves as a major driver, as cloud platforms offer the scalability and flexibility needed to manage extensive datasets and complex machine learning workflows efficiently.

Cloud-based MLOps solutions enable organizations to deploy models seamlessly across multiple environments. This approach eliminates the need for extensive on-premises infrastructure while delivering enhanced performance and scalability. By leveraging these solutions, businesses can streamline machine learning operations and adapt to evolving demands with greater efficiency.

Market Scope
Start Year	2024
Forecast Year	2025-2034
Start Value	$1.7 billion
Forecast Value	$39 billion
CAGR	37.4%

Reducing the time-to-market for new machine learning models has become a critical priority for organizations aiming to maintain a competitive edge. MLOps platforms facilitate this by automating the development, testing, and deployment processes through continuous integration and continuous deployment (CI/CD). This automation accelerates workflows, minimizes manual intervention, and ensures models remain scalable and consistently updated.

The MLOps market is segmented by components into platforms and services. Platforms led the market in 2024, capturing 72% of the total share. This dominance stems from the growing demand for end-to-end solutions that unify data pipeline management, model deployment, experiment tracking, and performance monitoring. Comprehensive platforms are increasingly favored by enterprises seeking to scale artificial intelligence initiatives while simplifying their workflows.

Services, including consulting, integration, and managed services, are also witnessing significant growth. These services assist organizations in overcoming adoption challenges such as cloud migration, infrastructure optimization, and compliance requirements. The rise in demand for tailored guidance highlights the importance of expert support in the MLOps ecosystem.

By end use, the market is categorized into Large Enterprises and SME. In 2024, Large Enterprises held a 64.3% market share, driven by the adoption of MLOps solutions to optimize AI workflows, enhance predictive analytics, and improve governance. Meanwhile, SME are rapidly embracing cost-effective, user-friendly tools that enable them to automate processes and foster innovation. The growing accessibility of AI tools supports this trend, allowing smaller businesses to achieve scalability without heavy infrastructure investments.

In North America, the United States leads the MLOps market, projected to surpass USD 11 billion by 2034. The country's strong adoption of AI and machine learning across industries such as healthcare, finance, and manufacturing underscores its pivotal role in driving market expansion. Investments in cloud infrastructure and high-performance computing further propel the adoption of MLOps solutions, helping businesses improve model operations and reduce deployment times.

Chapter 1 Methodology & Scope

1.1 Research design
- 1.1.1 Research approach
- 1.1.2 Data collection methods
1.2 Base estimates and calculations
- 1.2.1 Base year calculation
- 1.2.2 Key trends for market estimates
1.3 Forecast model
1.4 Primary research & validation
- 1.4.1 Primary sources
- 1.4.2 Data mining sources
1.5 Market definitions

Chapter 2 Executive Summary

2.1 Industry 360⁰ synopsis, 2021 - 2034

Chapter 3 Industry Insights

3.1 Industry ecosystem analysis
- 3.1.1 Technology providers
- 3.1.2 Model development and training platforms
- 3.1.3 Data management providers
- 3.1.4 Model deployment and governance providers
- 3.1.5 End users
3.2 Supplier landscape
3.3 Profit margin analysis
3.4 Use cases of MLOps
3.5 Technology & innovation landscape
3.6 Key news & initiatives
3.7 Regulatory landscape
3.8 Impact forces
- 3.8.1 Growth drivers
  - 3.8.1.1 Increased adoption of AI and machine learning
  - 3.8.1.2 Demand for faster model deployment
  - 3.8.1.3 Regulatory compliance and model governance
  - 3.8.1.4 Cloud adoption and scalability
- 3.8.2 Industry pitfalls & challenges
  - 3.8.2.1 Data privacy and security concerns
  - 3.8.2.2 Lack of skilled professionals
3.9 Growth potential analysis
3.10 Porter’s analysis
3.11 PESTEL analysis

Chapter 4 Competitive Landscape, 2024

4.1 Introduction
4.2 Company market share analysis
4.3 Competitive positioning matrix
4.4 Strategic outlook matrix

Chapter 5 Market Estimates & Forecast, By Component, 2021 - 2034 ($Mn)

5.1 Key trends
5.2 Platform
5.3 Services

Chapter 6 Market Estimates & Forecast, By Deployment Mode, 2021 - 2034 ($Mn)

6.1 Key trends
6.2 Cloud-based
6.3 On-Premises

Chapter 7 Market Estimates & Forecast, By End Use, 2021-2034 ($Mn)

7.1 Key trends
7.2 Large enterprises
7.3 SME

Chapter 8 Market Estimates & Forecast, By Vertical, 2021 - 2034 ($Mn)

8.1 Key trends
8.2 Healthcare
8.3 Retail & e-commerce
8.4 Manufacturing & supply chain
8.5 BFSI
8.6 Others

Chapter 9 Market Estimates & Forecast, By Region, 2021 - 2034 ($Mn)

9.1 Key trends
9.2 North America
- 9.2.1 U.S.
- 9.2.2 Canada
9.3 Europe
- 9.3.1 UK
- 9.3.2 Germany
- 9.3.3 France
- 9.3.4 Spain
- 9.3.5 Italy
- 9.3.6 Russia
- 9.3.7 Nordics
9.4 Asia Pacific
- 9.4.1 China
- 9.4.2 India
- 9.4.3 Japan
- 9.4.4 South Korea
- 9.4.5 ANZ
- 9.4.6 Southeast Asia
9.5 Latin America
- 9.5.1 Brazil
- 9.5.2 Mexico
- 9.5.3 Argentina
9.6 MEA
- 9.6.1 UAE
- 9.6.2 South Africa
- 9.6.3 Saudi Arabia