MLOps Market Size, Share and Growth Analysis Report - Forecast Trends and Outlook (2025-2034)

The global MLOps market size reached around USD 4.26 Billion in 2024. The market is projected to grow at a CAGR of 32.70% between 2025 and 2034 to reach nearly USD 72.13 Billion by 2034.

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Global MLOps Market Growth

By 2030, machine learning is expected to add nearly USD 13 trillion of value to the global economy by successfully enabling workers across all industries to improve their output. As per IBM, 70% of all AI workloads are currently built on a serverless programming model, which has necessitated the adoption of a DevOps culture. This is expected to favourably shape the MLOps market dynamics over the forecast period.

Conventionally, the development and implementation of AI solutions take 9-12 months, which puts large businesses behind rapidly evolving market dynamics. However, companies using MLOps have reportedly taken their projects live within 2-12 weeks of the conception of their first idea. Hence, the MLOps market development is expected to be driven by the rising focus of companies to increase productivity and speed without increasing technical debt.

The market analysis suggests that large organisations shelve 80% of their AI solutions while under development since they cease to provide any value. However, companies using MLOps practices increase value realisation by 60% and shelve a 30% lesser number of models. This can be attributed to the integration of efficacy testing and continuous monitoring models into their workflows, thereby driving the MLOps market growth.

Key Trends and Developments

Rising incidences of fraud; proliferation of LLMs; the emergence of Gen AI; and the growth of the energy and materials industry are the major factors favouring the MLOps market expansion

June 2024

Clear ML established an agreement with Carahsoft Technologies to sell its leading AI and ML solutions to the US federal and state governments. Under the agreement, Clear ML aims to expand its presence in the public sector and address government agencies' needs for MLOps and generative AI technology.

August 2023

Google introduced new upgrades to its Vertex AI platform to keep up with rapid advancements in generative AI. This includes updates for efficiently generating images, texts, and codes.

January 2023

McKinsey acquired Israel-based MLOps company Iguazio for USD 50 million to bolster the development of its QuantumBlack platform. This is expected to favourably impact the MLOps market dynamics over the forecast period.

May 2021

Google launched Vertex AI, a managed ML (machine learning) platform that accelerates the maintenance and deployment of AI models by companies. It needs almost 80% fewer code lines for training a data science model, which enables data scientists to efficiently implement MLOps.

Rising incidences of fraud

The Federal Trade Commission of the United States reported that Americans lost over USD 5.8 billion to fraud in 2021. This is expected to drive the MLOps market growth as MLOps reduces the susceptibility of financial models to data drifts and ensures better consumer protection.

Proliferation of Large Language Models (LLMs)

MLOps processes facilitate the development, deployment and maintenance of LLMs while addressing challenges surrounding bias and ensuring fairness of model outcomes. It also ensures efficient management and versioning of data science models for better reproducibility.

Emergence of Gen AI

GenAI can improve the MLOps workflow via automation of labour-intensive tasks like data preparation and cleaning, thereby enhancing the efficiency of data science models and enabling engineers and scientists to focus on relatively more strategic tasks. This can accelerate the MLOps market development.

Growth of the materials and energy industry

The use of MLOPs has prompted energy and materials companies to predict and prevent the failure of essential equipment, thereby reducing maintenance costs and ensuring employee safety.

Global MLOps Market Trends

Earlier, fraud analysts used to perform manual analysis on fraudulent transactions to build data protection rules. However, MLOps has eliminated this need in the BFSI industry, which has favourably impacted the MLOPs market dynamics. The increasing incidence of fraud incidents is expected to drive the growth of MLOps worldwide, especially in North America.

As per the US Federal Trade Commission, over 2.8 million fraud complaints were registered by American consumers, most of whom were victims of imposter scams. In 2021, it resulted in a loss of nearly USD 2.3 million to consumers, which increased from USD 1.2 billion in 2020. Online shopping fraud also increased, resulting in a loss of USD 392 million in 2021, up from USD 246 million in 2020. This is expected to facilitate the MLOPs market development over the forecast period.

Global MLOps Industry Segmentation

The EMR’s report titled “Global MLOps Market Report and Forecast 2025-2034” offers a detailed analysis of the market based on the following segments:

Market Breakup by Component:

  • Platform
  • Service
Market Breakup by Deployment Mode:
  • On-Premise
  • Cloud
Market Breakup by Organisation Size:
  • Large Enterprises
  • Small and Medium-sized Enterprises
Market Breakup by Industry Vertical:
  • BFSI
  • Manufacturing
  • IT and Telecom
  • Retail and E-commerce
  • Energy and Utility
  • Healthcare
  • Media and Entertainment
  • Others
Market Breakup by Region:
  • North America
  • Europe
  • Asia Pacific
  • Latin America
  • Middle East and Africa
Global MLOps Market Share

Based on region, the market is segmented into North America, Europe, the Asia Pacific, Latin America, and the Middle East and Africa. Over the forecast period of 2024-32, North America is estimated to grow at a CAGR of 34.8% due to the increasing adoption of AI models for upscaling business productivity and efficiency. The MLOps market revenue is rising, as MLOps platforms enable businesses to streamline the machine learning lifecycle, which enables faster deployment of data science models.

Leading Companies in the Global MLOps Market

Major players are expected to make significant investments towards adopting MLOps, thereby increasing the MLOps market revenue.

Akira AI

Akira AI was founded in 2023 and is headquartered in Dubai, UAE. It is a data infrastructure company which specialises in providing MLOps, LLMOps, ModelOps, and other platforms for responsible AI development.

Dataiku

Dataiku was founded in 2013 and is headquartered in New York, United States. It is a software development company which is engaged in designing, developing, and deploying new AI capabilities for businesses across numerous industries.

Cloudera, Inc.

Cloudera, Inc. was founded in 2008 and is headquartered in California, United States. It is a software development company which specialises in cloud computing and data engineering services.

DataRobot, Inc.

DataRobot, Inc. was founded in 2012 and is headquartered in Massachusetts, United States. It specialises in providing artificial intelligence, machine learning, data science, and time series modelling services to enterprises.

Other players included in the MLOps market report are International Business Machines Corporation, Microsoft Corporation, Alphabet Inc., Amazon Web Services, Inc., HP Development Company, L.P., and Alteryx, Inc., among others.


1 Executive Summary
1.1 Market Size 2024-2025
1.2 Market Growth 2025(F)-2034(F)
1.3 Key Demand Drivers
1.4 Key Players and Competitive Structure
1.5 Industry Best Practices
1.6 Recent Trends and Developments
1.7 Industry Outlook
2 Market Overview and Stakeholder Insights
2.1 Market Trends
2.2 Key Verticals
2.3 Key Regions
2.4 Supplier Power
2.5 Buyer Power
2.6 Key Market Opportunities and Risks
2.7 Key Initiatives by Stakeholders
3 Economic Summary
3.1 GDP Outlook
3.2 GDP Per Capita Growth
3.3 Inflation Trends
3.4 Democracy Index
3.5 Gross Public Debt Ratios
3.6 Balance of Payment (BoP) Position
3.7 Population Outlook
3.8 Urbanisation Trends
4 Country Risk Profiles
4.1 Country Risk
4.2 Business Climate
5 Global MLOps Market Analysis
5.1 Key Industry Highlights
5.2 Global MLOps Historical Market (2018-2024)
5.3 Global MLOps Market Forecast (2025-2034)
5.4 Global MLOps Market by Component
5.4.1 Platform
5.4.1.1 Historical Trend (2018-2024)
5.4.1.2 Forecast Trend (2025-2034)
5.4.2 Service
5.4.2.1 Historical Trend (2018-2024)
5.4.2.2 Forecast Trend (2025-2034)
5.5 Global MLOps Market by Deployment Mode
5.5.1 On-Premise
5.5.1.1 Historical Trend (2018-2024)
5.5.1.2 Forecast Trend (2025-2034)
5.5.2 Cloud
5.5.2.1 Historical Trend (2018-2024)
5.5.2.2 Forecast Trend (2025-2034)
5.6 Global MLOps Market by Organization Size
5.6.1 Large Enterprises
5.6.1.1 Historical Trend (2018-2024)
5.6.1.2 Forecast Trend (2025-2034)
5.6.2 Small and Medium-sized Enterprises
5.6.2.1 Historical Trend (2018-2024)
5.6.2.2 Forecast Trend (2025-2034)
5.7 Global MLOps Market by Industry Vertical
5.7.1 BFSI
5.7.1.1 Historical Trend (2018-2024)
5.7.1.2 Forecast Trend (2025-2034)
5.7.2 Manufacturing
5.7.2.1 Historical Trend (2018-2024)
5.7.2.2 Forecast Trend (2025-2034)
5.7.3 IT and Telecom
5.7.3.1 Historical Trend (2018-2024)
5.7.3.2 Forecast Trend (2025-2034)
5.7.4 Retail and E-commerce
5.7.4.1 Historical Trend (2018-2024)
5.7.4.2 Forecast Trend (2025-2034)
5.7.5 Energy and Utility
5.7.5.1 Historical Trend (2018-2024)
5.7.5.2 Forecast Trend (2025-2034)
5.7.6 Healthcare
5.7.6.1 Historical Trend (2018-2024)
5.7.6.2 Forecast Trend (2025-2034)
5.7.7 Media and Entertainment
5.7.7.1 Historical Trend (2018-2024)
5.7.7.2 Forecast Trend (2025-2034)
5.7.8 Others
5.8 Global MLOps Market by Region
5.8.1 North America
5.8.1.1 Historical Trend (2018-2024)
5.8.1.2 Forecast Trend (2025-2034)
5.8.2 Europe
5.8.2.1 Historical Trend (2018-2024)
5.8.2.2 Forecast Trend (2025-2034)
5.8.3 Asia Pacific
5.8.3.1 Historical Trend (2018-2024)
5.8.3.2 Forecast Trend (2025-2034)
5.8.4 Latin America
5.8.4.1 Historical Trend (2018-2024)
5.8.4.2 Forecast Trend (2025-2034)
5.8.5 Middle East and Africa
5.8.5.1 Historical Trend (2018-2024)
5.8.5.2 Forecast Trend (2025-2034)
6 North America MLOps Market Analysis
6.1 United States of America
6.1.1 Historical Trend (2018-2024)
6.1.2 Forecast Trend (2025-2034)
6.2 Canada
6.2.1 Historical Trend (2018-2024)
6.2.2 Forecast Trend (2025-2034)
7 Europe MLOps Market Analysis
7.1 United Kingdom
7.1.1 Historical Trend (2018-2024)
7.1.2 Forecast Trend (2025-2034)
7.2 Germany
7.2.1 Historical Trend (2018-2024)
7.2.2 Forecast Trend (2025-2034)
7.3 France
7.3.1 Historical Trend (2018-2024)
7.3.2 Forecast Trend (2025-2034)
7.4 Italy
7.4.1 Historical Trend (2018-2024)
7.4.2 Forecast Trend (2025-2034)
7.5 Others
8 Asia Pacific MLOps Market Analysis
8.1 China
8.1.1 Historical Trend (2018-2024)
8.1.2 Forecast Trend (2025-2034)
8.2 Japan
8.2.1 Historical Trend (2018-2024)
8.2.2 Forecast Trend (2025-2034)
8.3 India
8.3.1 Historical Trend (2018-2024)
8.3.2 Forecast Trend (2025-2034)
8.4 ASEAN
8.4.1 Historical Trend (2018-2024)
8.4.2 Forecast Trend (2025-2034)
8.5 Australia
8.5.1 Historical Trend (2018-2024)
8.5.2 Forecast Trend (2025-2034)
8.6 Others
9 Latin America MLOps Market Analysis
9.1 Brazil
9.1.1 Historical Trend (2018-2024)
9.1.2 Forecast Trend (2025-2034)
9.2 Argentina
9.2.1 Historical Trend (2018-2024)
9.2.2 Forecast Trend (2025-2034)
9.3 Mexico
9.3.1 Historical Trend (2018-2024)
9.3.2 Forecast Trend (2025-2034)
9.4 Others
10 Middle East and Africa MLOps Market Analysis
10.1 Saudi Arabia
10.1.1 Historical Trend (2018-2024)
10.1.2 Forecast Trend (2025-2034)
10.2 United Arab Emirates
10.2.1 Historical Trend (2018-2024)
10.2.2 Forecast Trend (2025-2034)
10.3 Nigeria
10.3.1 Historical Trend (2018-2024)
10.3.2 Forecast Trend (2025-2034)
10.4 South Africa
10.4.1 Historical Trend (2018-2024)
10.4.2 Forecast Trend (2025-2034)
10.5 Others
11 Market Dynamics
11.1 SWOT Analysis
11.1.1 Strengths
11.1.2 Weaknesses
11.1.3 Opportunities
11.1.4 Threats
11.2 Porter’s Five Forces Analysis
11.2.1 Supplier’s Power
11.2.2 Buyer’s Power
11.2.3 Threat of New Entrants
11.2.4 Degree of Rivalry
11.2.5 Threat of Substitutes
11.3 Key Indicators of Demand
11.4 Key Indicators of Price
12 Value Chain Analysis
13 Price Analysis
14 Manufacturing Process
15 Competitive Landscape
15.1 Supplier Selection
15.2 Key Global Players
15.3 Key Regional Players
15.4 Key Player Strategies
15.5 Company Profiles
15.5.1 International Business Machines Corporation
15.5.1.1 Company Overview
15.5.1.2 Product Portfolio
15.5.1.3 Demographic Reach and Achievements
15.5.1.4 Certifications
15.5.2 Microsoft Corporation
15.5.2.1 Company Overview
15.5.2.2 Product Portfolio
15.5.2.3 Demographic Reach and Achievements
15.5.2.4 Certifications
15.5.3 Alphabet Inc.
15.5.3.1 Company Overview
15.5.3.2 Product Portfolio
15.5.3.3 Demographic Reach and Achievements
15.5.3.4 Certifications
15.5.4 Amazon Web Services, Inc.
15.5.4.1 Company Overview
15.5.4.2 Product Portfolio
15.5.4.3 Demographic Reach and Achievements
15.5.4.4 Certifications
15.5.5 HP Development Company, L.P.
15.5.5.1 Company Overview
15.5.5.2 Product Portfolio
15.5.5.3 Demographic Reach and Achievements
15.5.5.4 Certifications
15.5.6 Akira AI
15.5.6.1 Company Overview
15.5.6.2 Product Portfolio
15.5.6.3 Demographic Reach and Achievements
15.5.6.4 Certifications
15.5.7 DataRobot, Inc.
15.5.7.1 Company Overview
15.5.7.2 Product Portfolio
15.5.7.3 Demographic Reach and Achievements
15.5.7.4 Certifications
15.5.8 Dataiku
15.5.8.1 Company Overview
15.5.8.2 Product Portfolio
15.5.8.3 Demographic Reach and Achievements
15.5.8.4 Certifications
15.5.9 Cloudera, Inc.
15.5.9.1 Company Overview
15.5.9.2 Product Portfolio
15.5.9.3 Demographic Reach and Achievements
15.5.9.4 Certifications
15.5.10 Alteryx, Inc.
15.5.10.1 Company Overview
15.5.10.2 Product Portfolio
15.5.10.3 Demographic Reach and Achievements
15.5.10.4 Certifications
15.5.11 Others

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