by Machine learning as a service (MLaaS) uses the capabilities of machine learning algorithms via an application programming interface (API) or similar abstraction layer offered by MLaaS providers. MLaaS vendors handle all computation needs, infrastructure setup, and engineering support necessary for end users to leverage machine learning capabilities in their applications. Businesses can access these services through simple API calls or web dashboards, without the need to build and maintain infrastructure that has the computational capacity for model development and implementation. Common MLaaS capabilities include data processing, predictive analytics, visualizations, and more. Healthcare organizations are widely using MLaaS to process huge volumes of patient data and generate healthcare analytics and clinical predictions. Gaming companies rely on MLaaS for predictive analytics on player sentiment, retention modeling, and personalization.
The global machine learning as a service market is estimated to be valued at US$ 10072.55 Mn in 2023 and is expected to exhibit a CAGR of 7.9% over the forecast period 2023 to 2030, as highlighted in a new report published by Coherent Market Insights.
Market Dynamics:
Rising demand for cloud-based predictive analytics is expected to flourish the machine learning as a service market over the forecast period. Businesses are relying increasingly on predictive analytics for tasks ranging from risk assessment and recommendation engines to forecasting and diagnostics. MLaaS frees up organizations from the overheads of building, maintaining and scaling machine learning infrastructure and models. This allows predictive analytics capabilities to be leveraged even by small and mid-sized businesses with no in-house data science resources. MLaaS also removes dependency on hardware or software upgrades, with vendors seamlessly handling changes under the hood. This enables organizations to focus on their core businesses and access machine learning as another cloud service. Another driver is the growing need for real-time analytics from structured and unstructured data sources like text, audio and images. MLaaS supports on-demand model training and deployment which allows faster experimentation and insights from even non-tabular datasets. Vendors with large pools of data and compute power can generate better and more customized models for end users compared to standalone deployments. This is expected to further accelerate adoption of MLaaS over the forecast period.
Segment Analysis
The Machine Learning as a Service (MLaaS) market can be segmented based on component, organization size, application, industry vertical and region. The service component segment is dominating the market currently due to the increasing adoption of machine learning services by businesses for various applications. The services component includes training & consulting services, software tool integration services and support & maintenance.
PEST Analysis
Political: Governments across countries are supporting the adoption of advanced technologies like machine learning and AI. They are introducing policies to promote research and innovations in these fields.
Economic: MLaaS solutions help businesses improve operational efficiency and reduce costs. This has a positive impact on the economy. The cost benefits are driving more organizations to adopt MLaaS.
Social: Users today expect personalized experiences powered by technologies. MLaaS helps understand customer behavior better to enhance customer experiences. It is also being used in applications that benefit society like healthcare.
Technological: Cloud platforms enable easy access to ML capabilities for businesses. Advances in deep learning techniques are improving the predictive capabilities of machine learning models. This is increasing adoption of MLaaS.
Key Takeaways
The Global Machine Learning As A Service (Mlaas) Market Size is expected to witness high growth over the forecast period of 2023 to 2030. The global machine learning as a service market is estimated to be valued at US$ 10072.55 Mn in 2023 and is expected to exhibit a CAGR of 7.9% over the forecast period 2023 to 2030.
Regional analysis: North America currently dominates the MLaaS market due to strong technological advancements and presence of major players in the region. The Asia Pacific region is anticipated to grow at the fastest pace due to increasing digitalization and rising adoption of cloud-based solutions across industries in countries like China, India.
Key players: Key players operating in the Machine Learning as a Service (MLaaS) market are BASF SE, SINOYQX, Puyang Green Yingli New Material Tech Co. Ltd, BEIJING GUOJIAN ANKE, ZHEJIANG LIN’AN YUNQING MELAMINE PLASTIC FOAM CO., PentaClick, Acoufelt, Clark Foam, Reilly Foam Corporation, Soundcoat, Festa. Major players are focused on expanding their geographic footprint and offering through strategic collaborations.
*Note:
1. Source: Coherent Market Insights, Public sources, Desk research
2. We have leveraged AI tools to mine information and compile it
Money Singh is a seasoned content writer with over four years of experience in the market research sector. Her expertise spans various industries, including food and beverages, biotechnology, chemical and materials, defense and aerospace, consumer goods, etc.
