Global Machine Learning as a Service (MlaaS) Market - Segmented by Application (Advertising and Marketing, Predictive Maintenance, Automated Network Management), Organization Size (SMB, Large Enterprises) End-User, and Region - Growth, Trends and Forecasts (2018 - 2023)
The global MLaaS market is expected to register a CAGR of about 43.46% during 2018-2023 (the forecast period), to reach a value of USD 8.315 billion, by 2023, from USD 0.932 billion, as of 2017. The scope of this report is limited to the solutions that are offered by the major market players including service providers. The regions, considered in the scope of this report, include North America, Europe, and ‘others’. The study highlights the various applications of machine learning, such as predictive maintenance, risk analytics, and fraud detection, among various others.
With advancements in the data science and artificial intelligence technologies, the performance of machine learning has accelerated at a rapid pace. Companies are now identifying the potential of this technology, and therefore, the adoption rate of the same is expected to increase over the forecast period. Companies are offering machine learning solutions on a subscription-based model, making it easier for the consumers to take the advantage of this technology. MLaaS model is expected to dominate the market, with users having an option to choose from a wide variety of solutions that are focused on different business needs. Also, factors, such as the increasing adoption of cloud-based services, IoT, and automation, and the growing need for consumer behavior analysis are expected to drive the machine learning as a service market.
However, the security concerns and a lack of skilled personnel, to use these solutions, can act as the market restraints.
Increasing Adoption of IoT and Automation
The increasing rate of adoption for IoT and automation systems in industries is expected to drive the growth of adoption rate for MLaaS. Industrial automation already has over a billion connected devices deployed. Owing to IoT, the smart and connected technologies have increased the pace of data that is being created, exponentially. Thus, industries are finding opportunities to explore this data and devise new solutions, in order to improve the existing infrastructure and operating efficiencies. For instance, MLaaS providers, such as IBM, are providing utility IoT as a solution to implement analytics roadmap in support of asset health and reliability.
Growing Demand for Predictive Maintenance Solutions to Augment the Growth
Increasing deployment of IoT and smart sensors in the industry is enabling companies to deploy predictive maintenance models and eliminate the problems and faults before they could affect the equipment. Industries are now focusing on curbing additional costs and reducing downtime by eliminating failures. The sectors of manufacturing, energy & utility, and oil & gas are projected to be the largest consumers of this solution in the coming years. Manufacturing & production industry is likely to deploy IoT, in order to monitor the existing equipment and predict faults, thus enabling prior inspection and maintenance for eliminating failure.
North America to Witness the Highest Share
The swift market penetration and presence of large companies, working on the technology, are likely to influence the market growth. However, shifting focus toward automation and deployment of new technologies, to reduce costs, are likely to drive the APAC region at a faster growth rate. Moreover, the region has witnessed a tremendous increase in the number of start-ups involved in the business, which is further fuelling the market growth.
Key Developments in the market