Driven by the Adoption of IoT in Business Operations Contributing to Market Expansion, the Global Machine Learning as a Service (MLaaS) Market is forecasted to Cross US$ 30 Bn by 2028 says Ken Research Study.
Machine Learning as a Service (MLaaS) is a group of services that provide machine learning (ML) tools as a component of cloud computing solutions. MLaaS enables customers/clients to benefit from ML without the associated expense, risk, or time required to build an internal ML team. The SME segment procured a substantial revenue share in the Machine Learning as a Service Market due to the implementation of ML allowing SMEs to optimize their processes on a limited budget. AI and ML are projected to be the major technologies that allow SMEs to cut expenses on ICT and gain access to digital resources in the near future.
According to Ken Research estimates, the Global Machine Learning as a Service (MLaaS) Market – estimated to be around US$ 10 bn by 2022 is expected to grow further into a more than US$ 30 bn opportunity by 2028.
“Ken Research shares 5 key insights on this high opportunity market from its latest research study”
- Machine Learning as a Service (MLaaS) has seen Accelerated Growth with the Adoption of IoT in Business Operations
- The information technology industry is expanding as a result of social media platforms and cloud computing technologies’ rising popularity. Several organizations that offer enterprise storage solutions today frequently employ cloud computing solutions. Online data analysis utilizing cloud storage has the benefit of analyzing real-time data gathered in the cloud. Data analysis is possible at any time and from any location owing to cloud computing.
- Additionally, leveraging the cloud to use ML enables organizations to virtually access important data from linked data warehouses, reducing infrastructure and storage expenses, such as customer behavior and purchase trends. As a result of the increased use of cloud computing, the MLaaS industry is growing.
- AI systems employ ML to support reasoning, learning, and self-correction. Applications of AI include expert systems, speech recognition, and machine vision. AI is becoming popular as a result of current initiatives like big data infrastructure and cloud computing. In May 2021, Google Cloud unveiled Vertex AI, a new managed ML platform that allows users to maintain and deploy AI models based on client needs.
- Rising Adoption of Cloud-based Services Likely to Drive the Market Growth
- Increasing cloud technology integration by employing desirable delivery methods in several industry verticals enables developers to offer major cloud-based solutions to manage business operations.
- As cloud-based technologies are being widely used in different enterprises, data interchange is facilitated by the simplicity with which these connections may be established. This makes it possible to access the information within a company, increasing the latter’s cost-effectiveness.
- In April 2022, Infosys Ltd on launched Cobalt Financial Services Cloud, an industry cloud platform for enterprises to accelerate business value and innovation in the cloud across the financial services industry. Infosys Cobalt Financial Services Cloud is a secure, vertical cloud platform that enables enterprises to accelerate cloud adoption, rapidly build cloud-native business platforms, drive business agility and growth, foster innovation, and deliver a personalized customer experience.
- Lack of Skilled Consultants and Compliance Issues Affect Market Growth
- The growing use of cloud technologies and desirable delivery methods across a variety of industry verticals enables developers to create effective cloud-based business operations solutions.
- SMEs in the MLaaS business prefer cloud-based services to cut down the ML integration process. It increases an organization’s efficiency without recruiting additional staff by getting rid of repetitive work.
- However, the absence of qualified consultants, issues with compliance, and regulatory restrictions are some of the barriers that prevent this market’s growth. Therefore, market participants should work with governmental and regulatory bodies to enhance uniformity in the market environment.
- In February 2022, Appier observes that one current challenge of taking ML models to MLaaS has to do with how we currently build ML models and how we teach future ML talent to do it. Most research and development of ML models focuses on building individual models that use a set of training data (with pre-assigned features and labels) to deliver the best performance in predicting the labels of another set of data.
- The Service Segment is Likely to be the Dominant Force During the Forecast Period
- The service segment dominated the Machine Learning as a Service (MLaaS) Market and is expected to maintain its dominance during the forecast period. The market for ML services is expected to grow due to factors such as an increase in application areas and growth connected with end-use industries in developing economies. To enhance the usage of ML services, industry participants are focusing on implementing technologically advanced solutions.
- The use of ML services in the healthcare business for cancer detection, as well as checking ECG and MRI, is fuelling the market growth. Machine learning services’ benefits, such as cost reduction, demand forecasting, real-time data analysis, and increased cloud use, are projected to open up considerable prospects for the market.
- North America, the Largest Market Region Attributes Increased Spending on Defense and Key Player Presence Towards its Growth
- North America is expected to continue its dominance in the Machine Learning as a Service (MLaaS) Market during the forecast period. North American region is an early adopter of technology and innovations. It hosts the preferable infrastructure for the development of MLaaS.
- In addition, it is predicted that the market expansion during the forecast period is also attributed to rising defense spending and technological advancements in the telecommunications industry. Government regulations on data security are projected to have a significant impact on the market for ML services.
In December 2021, BigML added Image Processing to the BigML platform, a feature that enhances their offering to solve image data-driven business problems with ease of use. It labels the image data, train and evaluate models, make predictions, and automate end-to-end machine learning workflows.
For More Information, refer to below link:-
Global Automated Network Management MLaaS Market
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