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Global ModelOps Market Size, Share & Trends Analysis Report By Offering (Platforms, and Services), By Model, By Deployment (Cloud, and On-Premise), By Vertical, By Application, By Regional Outlook and Forecast, 2024 - 2031
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ÆäÀÌÁö Á¤º¸ : ¿µ¹® 377 Pages
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The Global ModelOps Market size is expected to reach $58.07 billion by 2031, rising at a market growth of 40.2% CAGR during the forecast period.

The North America segment garnered 36% revenue share in the market in 2023. This prominence is attributed to the region's advanced technological infrastructure, substantial investments in artificial intelligence (AI) and machine learning (ML), and the presence of numerous leading technology firms. Industries such as finance, healthcare, and retail in North America are increasingly adopting these solutions to streamline AI model deployment and management, ensuring compliance with stringent regulatory standards and enhancing operational efficiency.

Companies leverage AI and ML to optimize operations, streamline workflows, and uncover insights that drive smarter decision-making. For example, in the financial sector, artificial intelligence models are employed for the purposes of fraud detection and risk assessment. Conversely, in the retail industry, these models facilitate personalized recommendations and optimize inventory management. Hence, this combination of technological capability and operational efficiency is driving the rapid adoption of ModelOps.

Additionally, Operational efficiency has become a top priority for organizations striving to remain agile and competitive in today's fast-paced business environment. A significant challenge in attaining this efficacy resides in the management of the complexities associated with the deployment and maintenance of artificial intelligence and machine learning models within production environments. Thus, these developments aid in the expansion of the market.

However, The dearth of qualified data scientists and machine learning engineers means that organizations often lack the necessary expertise to develop robust machine learning models. This limitation leads to longer development cycles, as existing teams may be overburdened or lack specific skills required for certain projects. Moreover, without adequate ModelOps experts, deploying these models into production environments becomes challenging. Hence, this substantial lack of talent may hamper the expansion of the market.

Offering Outlook

Based on offering, the market is bifurcated into platforms and services. The services segment procured 34% revenue share in the market in 2023. The increasing complexity of AI models necessitates specialized services to manage and optimize these models effectively. Organizations focus on data-driven decision-making, which requires customized solutions tailored to specific business needs.

Model Outlook

By model, the market is divided into ML models, graph-based models, rule & heuristic models, linguistic models, agent-based models, and others. The graph-based models segment garnered 16% revenue share in the market in 2023. Social media, telecommunications, and cybersecurity use graph-based models to detect patterns, identify anomalies, and understand intricate network structures. The rising need for advanced analytics to navigate complex data relationships drives the demand for these solutions tailored to efficiently manage and operationalize graph-based models.

Deployment Outlook

On the basis of deployment, the market is classified into cloud and on-premise. The on-premise segment recorded 38% revenue share in the market in 2023. Industries such as finance, healthcare, and government, which handle sensitive and confidential information, often prefer on-premises ModelOps solutions to ensure adherence to stringent regulatory requirements and mitigate data breach risks.

Vertical Outlook

On the basis of vertical, the market is classified into BFSI, retail & e-commerce, healthcare & life sciences, manufacturing, IT & telecommunications, energy & utilities, transportation & logistics, and others. The healthcare & life sciences segment witnessed 15% revenue share in the market in 2023. The sector is increasingly adopting ModelOps to advance personalized medicine, improve diagnostic accuracy, and streamline administrative processes. The integration of AI models facilitates the analysis of complex medical data, leading to better patient outcomes and optimized treatment plans.

Application Outlook

Based on application, the market is segmented into continuous integration/continuous deployment, batch scoring, governance, risk & compliance, parallelization & distributed computing, monitoring & alerting, dashboard & reporting, model lifecycle management, and others. The batch scoring segment recorded 15% revenue share in the market in 2023. Batch scoring involves processing large volumes of data to generate predictions or insights at scheduled intervals. Industries such as finance and retail utilize batch scoring to analyze historical data for risk assessment, customer segmentation, and inventory management.

Regional Outlook

Region-wise, the market is analyzed across North America, Europe, Asia Pacific, and LAMEA. The Europe segment procured 31% revenue share in the market in 2023. This market in Europe is significantly influenced by the region's robust commitment to data privacy and regulatory compliance, as evidenced by frameworks such as the General Data Protection Regulation (GDPR). Businesses in a variety of industries, such as manufacturing, healthcare, and finance, are investing in these solutions to ensure that their AI models adhere to these strict guidelines.

Recent Strategies Deployed in the Market

List of Key Companies Profiled

Global ModelOps Market Report Segmentation

By Offering

By Model

By Deployment

By Vertical

By Application

By Geography

Table of Contents

Chapter 1. Market Scope & Methodology

Chapter 2. Market at a Glance

Chapter 3. Market Overview

Chapter 4. Competition Analysis - Global

Chapter 5. Global ModelOps Market by Offering

Chapter 6. Global ModelOps Market by Model

Chapter 7. Global ModelOps Market by Deployment

Chapter 8. Global ModelOps Market by Vertical

Chapter 9. Global ModelOps Market by Application

Chapter 10. Global ModelOps Market by Region

Chapter 11. Company Profiles

Chapter 12. Winning Imperatives of ModelOps Market

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