ModelOps Market Report 2026

The modelops market size has grown exponentially in recent years. It will grow from $7.97 billion in 2025 to $11.33 billion in 2026 at a compound annual growth rate (CAGR) of 42.1%. The growth in the historic period can be attributed to growth of machine learning adoption, increasing enterprise data volumes, demand for model reliability, rise of AI-driven decision making, expansion of cloud infrastructure.

The modelops market size is expected to see exponential growth in the next few years. It will grow to $45.27 billion in 2030 at a compound annual growth rate (CAGR) of 41.4%. The growth in the forecast period can be attributed to regulatory compliance for AI models, demand for real-time model updates, integration of modelops with devops, growth of autonomous systems, enterprise AI standardization. Major trends in the forecast period include automated model deployment, continuous model monitoring, model governance frameworks, scalable model lifecycle management, cross-platform model integration.

The expanding telecommunications industry is expected to drive growth in the modelops market in the coming years. The telecommunications sector provides infrastructure and services for transmitting data, voice, and video through both wired and wireless networks. Its growth is fueled by factors such as 5G deployment, cloud and edge computing, rural connectivity initiatives, and ongoing digital transformation. Modelops support the telecommunications industry by automating the deployment and management of artificial intelligence models, enhancing network performance, and improving customer experiences. For example, in February 2024, Deutsche Telekom, a Germany-based telecommunications company, reported that global telecommunications service revenue grew by 3.3% year-on-year in 2023, while average monthly mobile data consumption per user in Europe increased to 16 GB, representing a 23% annual rise. Consequently, the growth of the telecommunications industry is driving expansion in the modelops market.

Key players in the ModelOps market are emphasizing strategic collaborations to improve the scalability, governance, and operational efficiency of AI model deployment across enterprise environments. Strategic collaborations are formal partnerships between technology providers that combine complementary capabilities, allowing organizations to streamline model lifecycle management, enhance interoperability, and accelerate the transition from model development to production. For example, in July 2024, Teradata, a U.S.-based provider of cloud analytics and enterprise data platforms, announced a partnership with DataRobot, a U.S.-based enterprise AI platform, to integrate DataRobot’s AI models into Teradata’s VantageCloud and ClearScape Analytics through bring-your-own-model (BYOM) capabilities. This collaboration enables enterprises to operationalize AI models at scale directly within their data environment and strengthen end-to-end ModelOps workflows.

In January 2023, McKinsey & Company, a US-based management consulting firm, acquired Iguazio for an undisclosed amount. This acquisition aims to bolster McKinsey's data engineering and AI capabilities by integrating Iguazio's advanced data analytics platform into its consulting services. The integration allows McKinsey’s clients to make more informed decisions based on real-time data insights. Iguazio, an Israel-based software development company, specializes in machine learning operations.

Major companies operating in the modelops market are Microsoft Corporation, International Business Machines Corporation IBM, Oracle Corporation, SAS Institute Inc., Teradata Corporation, TIBCO Software Inc., C3AI Inc., Veritone Inc., H2OAI Inc., DataKitchen Inc., ModelOp Inc., Datatron Technologies Inc., Verta Inc., Superwiseai, Google LLC, Amazon Web Services AWS, DataRobot Inc., Domino Data Lab Inc., Cloudera Inc., Palantir Technologies, Altair Engineering Inc., Comet ML, Evidently AI, Seldon Technologies, Weights & Biases, Cnvrgio, Dataiku, ValohAI.

North America was the largest region in the modelops market in 2025. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the modelops market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa. The countries covered in the modelops market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Taiwan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

Tariffs have impacted the modelops market by increasing costs associated with imported data center hardware, high-performance computing systems, and networking equipment. Enterprises in north america and europe face higher infrastructure expenses when deploying large-scale model operations. Industries such as bfsI and manufacturing are particularly affected due to intensive compute requirements. At the same time, tariffs are encouraging cloud-based and regionally hosted modelops platforms that lower dependency on imported hardware.

The modelops market research report is one of a series of new reports that provides modelops market statistics, including modelops industry global market size, regional shares, competitors with a modelops market share, detailed modelops market segments, market trends and opportunities, and any further data you may need to thrive in the modelops industry. This modelops market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.

ModelOps (Model Operations) refers to the comprehensive management, deployment, monitoring, and governance of machine learning models in production. It focuses on automating and optimizing the lifecycle of models, from development to scaling and retraining, ensuring model performance, compliance, and reliability in business operations.

The main types of ModelOps include machine learning (ML) models, graph-based models, rule and heuristic models, linguistic models, agent-based models, bring-your-own models, and others. Machine learning (ML) models are algorithms that enable computers to learn from data and make predictions or decisions without explicit programming. ModelOps solutions include platforms, deployment modes, and services for various applications such as continuous integration and continuous deployment, batch scoring, governance, risk and compliance, parallelization and distributed computing, monitoring and alerting, dashboard and reporting, and model lifecycle management. These solutions serve a wide range of industries, including banking, financial services, and insurance, retail and e-commerce, healthcare and life sciences, telecommunications, IT and IT-enabled services (ITeS), energy and utilities, manufacturing, transportation and logistics, government and defense, and more.

The modelOps market includes revenues earned by entities by model creation, version control, and updates. The market value includes the value of related goods sold by the service provider or included within the service offering. Only goods and services traded between entities or sold to end consumers are included.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

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