PUBLISHER: Grand View Research | PRODUCT CODE: 1654620
PUBLISHER: Grand View Research | PRODUCT CODE: 1654620
The global ModelOps market size was estimated at USD 5.64 billion in 2024 and is expected to grow at a CAGR of 41.3% from 2025 to 2030. Rapid AI and ML adoption across industries, needs for scalability large-scale AI deployment, cost efficiency and automation, and AI model performance monitoring are primarily drivers of the ModelOps market. ModelOps helps businesses mitigate operational risks by providing tools to detect and rectify model drift or failures before they impact critical business processes, ensuring consistent decision-making and reducing potential disruptions.
Strict regulations, in various industries such as, BFSI, and healthcare require transparent, explainable, and compliant AI models. ModelOps platforms provide governance frameworks that help businesses meet regulatory requirements, avoiding costly compliance breaches and ensuring auditability. For instance, in December 2024, ModelOp, a foremost provider of AI governance software for enterprises announced a significant surge in platform usage throughout the year. New customer acquisitions drove this growth, the adoption of generative AI, and an increasing demand for its AI portfolio intelligence and governance solutions. For the second year in a row, the company achieved substantial and sustained expansion, particularly in the healthcare, financial services, and consumer packaged goods (CPG) sectors.
ModelOps enhances the speed at which companies can move AI models from development to production. This reduction in time-to-market helps businesses quickly leverage AI-driven insights, ensuring agility in responding to market changes and customer demands. To ensure ongoing business value, ModelOps continuously monitors models for performance, drift, and bias. This proactive approach helps prevent revenue losses due to underperforming models, ensuring the consistency and accuracy of AI-driven decisions. Automating AI/ML model deployment, monitoring, and retraining reduces the need for manual intervention, leading to significant cost savings. For businesses, this means optimizing resources while maintaining high-quality AI operations.
As businesses across sectors increasingly adopt artificial intelligence (AI) and machine learning (ML) to gain competitive advantages, the need for ModelOps solutions to streamline deployment and management becomes critical. Operationalizing AI models efficiently is a top priority to ensure a faster return on investment (ROI). As companies scale their AI initiatives and deploy numerous models, ModelOps enables them to efficiently manage these models at scale, ensuring consistent performance across different environments and reducing operational costs.
Global ModelOps Market Report Segmentation
This report forecasts revenue growth at global, regional, and country levels and provides an analysis of the latest industry trends in each of the sub-segments from 2017 to 2030. For this study, Grand View Research has segmented the global ModelOps market report based on the offering, deployment, model, application, vertical, and region.