MLOps Market by Component (Platform and Services), Deployment Mode (Cloud and On-premises), Organization Size (Large Enterprises and SMEs), Vertical (BFSI, Healthcare and Life Sciences, Retail and eCommerce, Telecom) and Region - Global Forecast to 2027

MLOps Market by Component (Platform and Services), Deployment Mode (Cloud and On-premises), Organization Size (Large Enterprises and SMEs), Vertical (BFSI, Healthcare and Life Sciences, Retail and eCommerce, Telecom) and Region - Global Forecast to 2027

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. Various key players in the ecosystem have led to a competitive and diverse market. Standardizing ML processes for effective teamwork, monitorability, and scalability are expected to drive the adoption of the MLOps market in the future. However, organizations are unable to embrace MLOps models due to the lack of expertise of employees. Surveys have frequently demonstrated the inadequate knowledge and abilities of the employees in enterprises, according to numerous reports and research. Organizations should prioritise and make significant investments in training and certifications to address this issue, ensuring that the workforce has the necessary understanding of MLOps models and strategies and can put those tactics into practice for effective data management.

By vertical, banking, financial services, and insurance segment to account for larger market size during forecast period

BFSI segment holds the largest market size as today’s financial institutions use large data streams to create strong ML models that are subsequently deployed for specific objectives. Banking services would require to rapidly expand ML models owing to the growing volume and complexity of data to minimize operational costs associated with data management, and handle data concerns such as transparency and governance. Banks can use MLOps to automate the process of integrating AI/ML models into the applications. MLOps can help aid in the automation of program versioning and drift, as well as the duplicability of similar findings at scale. MLOps significantly reduces the cost of AI/Ml integrations inside self-managed systems through version control, traceability, continual code checks, and CI/CD pipelines.

By organization size, SMEs segment to grow at highest CAGR during forecast period

Small and medium-sized enterprises are organizations with an employee strength of less than 1,000. SMEs make for vast majority of enterprises globally and play a significant role in most economies. Today’ only fewer SMEs have adopted MLOps platforms relative to the large enterprises’ counterparts. However, the firms underlying SMEs adopting MLOps platforms are expected to rise as this would make things faster, smarter, and easier.These organizations are focused on deploying MLOps platforms to improve competitiveness and reduce operating costs. The MLOps platforms will enable SMEs to create web apps with dashboards and other visually appealing business graphics to showcase the discovered insights.This, in turn, would enable SMEs to adopt MLOps platform and services in the near future.

Asia Pacific to register highest growth rate during forecast period

The region is expected to show potential growth over the forecast period owing to factors such as government measures encouraging AI, increased ML usage, and the creation of numerous ML start-ups in the region. The APAC MLOps market has been classified into verticals, component, deployment, and organization size. MLOps platform and services enabled businesses to swiftly discover trends and make better judgements. Companies are expediting to produce and implement ML models because of its benefits, hence increasing market growth. Several large enterprises and SMEs are looking forward to the APAC region as an opportunity for their growth.

Breakdown of primaries

The study contains various industry experts' insights, from solution vendors to Tier 1 companies. The break-up of the primaries is as follows:

By Company Type: Tier 1 – 18%, Tier 2 – 9%, and Tier 3 – 73%

By Designation: C-level – 9%, D-level – 18%, and Others – 73%

By Region: North America – 55%, Europe – 9%, Asia Pacific – 36%

The major players covered in the MLOpsreport IBM (US), Microsoft (US), Google (US), AWS (US), HPE (US), GAVS Technologies (US), DataRobot (US), Cloudera (US), Alteryx (US), Domino Data Lab (US), Valohai (US), H2O.ai (US), MLflow (Netherlands), Neptune.ai (Europe), Comet (US), SparkCognition (US), Hopsworks (Europe), Datatron (US), Weights & Biases (US), Katonic.ai (Australia), Modzy (US), Iguazio (Israel), Teliolabs (US), ClearML (Israel), Akira.AI (India), and Blaize (US). 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.

Research Coverage

The market study covers the MLOps market size across segments. It aims at estimating the market size and the growth potential across segments, including component, deployment mode, organization size, vertical, and region. The study includes an in-depth competitive analysis of the leading market players, their company profiles, key observations related to product and business offerings, recent developments, and market strategies.

Key Benefits of Buying the Report

The report will help the market leaders/new entrants with information on the closest approximations of the revenue numbers for the global MLOps market and its subsegments. This report will help stakeholders understand the competitive landscape and gain more insights to position their businesses better and plan suitable go-to-market strategies. Moreover, the report will provide insights for stakeholders to understand the pulse of the market and provide them with information on key market drivers, restraints, challenges, and opportunities.