by Market Overview:
Machine Learning as a Service (MLaaS) refers to the usage of machine learning algorithms and artificial intelligence to build predictive models that are hosted on cloud platforms as an API service to the end users. Key application areas of MLaaS include predictive maintenance, image recognition, recommendation engines, predictive analytics, and big data analytics. It enables companies to develop, deploy and manage predictive models with minimal costs and infrastructure requirements.
Market Dynamics:
The significant growth in cloud computing adoption across various industry verticals is a major factor driving the growth of MLaaS market. According to statistics, cloud computing industry grew 31% in 2020 and cloud adoption increased among organizations of all sizes during the COVID-19 pandemic. Additionally, the shortage of in-house machine learning talent and high hiring costs of data scientists are encouraging companies to leverage MLaaS platforms to build machine learning models with limited resources. About 80% of organizations today face challenges finding qualified machine learning specialists according to a survey. This has propelled the demand for MLaaS around the world.
The global Machine Learning as a Service (MLaaS) Market Size is estimated to be valued at US$ 10,072.55 Mn in 2023 and is expected to exhibit a CAGR of 38.% over the forecast period 2023 to 2030, as highlighted in a new report published by Coherent Market Insights.
Segment Analysis
The MLaaS market can be broadly segmented into fraud detection, sales and marketing, supply chain management, predictive maintenance, and others. Among these, the fraud detection segment currently dominates the market and is expected to retain its dominance over the forecast period. This is because fraud detection enables businesses to identify fraudulent activities and prevent financial losses, thereby driving significant demand. Additionally, the rising digitization across industries has augmented online transactions and purchases, increasing the need for effective fraud detection solutions.
PEST Analysis
Political: Governments across various countries are supporting development of technologies like ML and offering subsidies to encourage adoption of innovative solutions. This is boosting investments in MLaaS.
Economic: MLaaS reduces costs for businesses associated with setting up in-house AI/ML teams and infrastructure. It offers pay-per-use pricing which is driving uptake, especially among SMEs.
Social: Growing internet and smartphone penetration has increased use of online services. Customers now expect personalized experiences from companies. MLaaS helps businesses gain insights from massive customer data to enhance customer experiences.
Technological: Advances in artificial intelligence, cloud computing, and data analytics have enabled development of sophisticated ML algorithms. MLaaS vendors are leveraging these technologies to offer advanced capabilities like deep learning and natural language processing to clients.
Key Takeaways
The global Machine Learning as a Service (MLaaS) market is expected to witness high growth, exhibiting 38% CAGR over the forecast period 2023 to 2030, due to increasing demand for boosting business efficiency and competitiveness. The market size is projected to reach US$ 110.2 Bn by 2030 from US$ 10072.55 Mn in 2023.
North America currently holds the largest share in the MLaaS market owing to rapid technological adoption and presence of major players in the region. Asia Pacific is expected to be the fastest growing regional market with countries like China and India emerging as high potential countries on the back of growing digitalization, internet connectivity, and investments in AI/ML technologies by governments.
Key players operating in the Machine Learning as a Service (MLaaS) market are H2O.ai, Google Inc., Predictron Labs Ltd, IBM Corporation, Ersatz Labs Inc., Microsoft Corporation, Yottamine Analytics, Amazon Web Services Inc., FICO, and BigML Inc. Major players are focused on developing advanced algorithmic solutions, partnering with other technology providers, and expanding into untapped regional markets to strengthen their market position.
*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.
