The MLOps Market size is projected to grow from USD 1.1 billion in 2022 to USD 5.9 billion by 2027, at a CAGR of 41.0% during the forecast period. The adoption rate of MLOps is increasing due to increased ability to consistently track and get insights into model performance. The enormous flexibility and administration features of MLOps enable supervision, control, management, and monitoring of thousands of models for continuous integration, continuous delivery, and continuous deployment are the key factors driving market growth.
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By component, Services segment to have highest growth rate during forecast period
Organizations worldwide are adopting MLOps solutions to empower their client engagement, brand awareness, and marketing activities. With the help of MLOps marketing platforms, organizations can easily engage audiences, communicate more efficiently, and expand their reach. MLOps solutions help enhance customer engagement by enabling rating, commenting, and sharing videos on social media. These solutions assist in measuring the impact of each video and optimizing content and distribution strategies with the help of built-in analytics. They also help enterprises launch video customer engagement programs. The effective use of MLOps solutions has helped organizations transform marketing from a cost center to a revenue function.
By vertical, Healthcare & Life Sciences segment to grow at highest CAGR during forecast period
Currently, the MLOps market is witnessing increased growth opportunities in the healthcare and life sciences vertical. This growth can be attributed to the increasing requirement of creating a digital healthcare system that is simple to convert into actionable insights. Today, many applicable health analytics processes are coming into play. For instance, healthcare providers can use patients’ data to build predictive models for various diseases and make very precise forecast. It will aid in diagnostic processes, that in turn will help to streamline patient treatment.
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Unique Features in the MLOps Market
MLOps solutions streamline the whole machine learning lifecycle by enabling end-to-end automation of workflows for data preparation, model training, deployment, monitoring, and maintenance.
By enabling the scalable and effective deployment of machine learning models across a range of environments—such as cloud, edge devices, and hybrid infrastructures—MLOps solutions guarantee optimal performance and resource efficiency.
Tracking model iterations, dependencies, and configurations is made possible by robust version control and reproducibility features in MLOps platforms, which guarantee transparency, auditability, and regulatory compliance.
Real-time tracking of model performance, drift detection, and automated retraining are made possible by advanced monitoring and governance capabilities, which also guarantee that models stay accurate, dependable, and consistent with changing data patterns and laws.
MLOps solutions improve efficiency and cross-functional cooperation by offering centralised repositories, experiment tracking, and workflow management tools to data scientists, engineers, and DevOps teams.
Major Highlights of the MLOps Market
As machine learning and artificial intelligence technologies become more widely used across businesses, the MLOps market has grown rapidly.
The need for MLOps solutions—which automate and optimise the whole machine learning lifecycle, from model training and data preparation to deployment, monitoring, and maintenance—is rising.
To enable effective collaboration between data scientists, machine learning engineers, and IT operations teams, MLOps approaches are increasingly being combined with DevOps methodologies.
Concerns about model fairness, bias, interpretability, and legal requirements are driving organisations to prioritise governance, compliance, and risk management in machine learning operations.
The scalability and performance issues that arise from deploying and managing machine learning models in production environments—particularly in cloud and edge computing environments—are the focus of MLOps solutions.
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Top Key Companies in the MLOps Market
Various globally established players such as IBM (US), Google (US), Microsoft (US), HPE (US), and Alteryx (US) are dominating the MLOps market. These players have adopted various growth strategies, such as partnerships, agreements and collaborations, new product launches and product enhancements, and acquisitions, to expand their footprint in the MLOps market.
IBM offers IBM Watson Studio, an MLOps platform. The platform enables data scientists, developers, and analysts to build, run, and manage AI models. It also offers optimizing choices for data from anywhere on the platform. In June 2021, IBM collaborated with Black & Veatch to jointly market Asset Performance Management solutions. These solutions will include remote monitoring technologies that combine artificial intelligence and near real-time data analytics to support customers in maintaining equipment and assets at peak performance and dependability.
Another important player in the MLOps market is HPE one of the world’s leading IT services and consulting company HPE is a worldwide edge-to-cloud corporation that enables an enterprise to connect, protect, analyze, and act on all of the data, from edge to cloud, to help transform, turn insights into outcomes and run digital business. The company is committed to provide an exceptional client experience. In March 2022, HPE announced it joining with BMW, the global leader in manufacturing premium automobiles and motorcycles. This partnership will help BMW to record electric test car data from throughout the world using HPE Ezmeral, providing BMW Group data.
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