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”
1. 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.
2. 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.
3. 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.
4. 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.
5. 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
Related Report
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Ken
Research
Ankur
Gupta, Head Marketing & Communications
+91-9015378249
