Ottawa, Jan. 09, 2024 (GLOBE NEWSWIRE) -- The global machine learning as a service market size accounted for USD 31.73 billion in 2023 and is expected to reach around USD 230.34 billion by 2029. The sector is driven by the accessibility of cloud-based AI, leading to its democratization.
A recent exciting development is Machine Learning as a Service (MLaaS), which allows enterprises and individuals to leverage the potential of machine learning without requiring substantial in-house resources or experience. There is no longer a need to worry about infrastructure scaling, software updates, or server maintenance due to the quicker adoption of machine learning. The MLaaS supplier handles everything. Pre-built models for typical jobs are available on many platforms, which saves time and effort. Some even offer tools that aid the user through the process, including autonomous machine learning. It pays for only the amount utilized and effortlessly modifies usage according to demands.
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MLaaS is transforming Artificial Intelligence (AI) by democratizing its capabilities and increasing its accessibility. MLaaS may assist you in utilizing machine learning's advantages for your company, regardless of size, without going over budget. It helps with various tasks, including projecting sales, churn, and equipment breakdowns. Use facial recognition, object identification, sentiment analysis, and other picture and video analysis techniques to enhance advertising targeting, suggest items, and personalize content. It helps create chatbots, deriving meaning from textual material and translating between languages.
- In November 2023, Adobe, a well-known software giant, bought Bengaluru-based Rephrase.ai, an AI-driven startup that creates videos, in its first generative AI purchase in India. The American software behemoth aims to improve and broaden its range of services by integrating Rephrase's technological stack and generative AI video features into its native film-editing platform, Creative Cloud.
- In November 2023, As part of the company's multiyear cloud migration to speed up clinical trial development and shorten the time it takes to find a cure for the disease, Merck, also known as MSD, outside of the United States and Canada, is moving a significant portion of its computer systems to AWS, according to a statement released by Amazon Web Services, Inc. (AWS), an e-commerce company.
Key Insights:
- North America led the global market with the largest market share of 39.7% in 2022.
- The solution segment is expected to dominate the market share over the forecast period.
- The large enterprises segment is expected to dominate the market during the forecast period.
- The market & advertising segment is expected to dominate the market during the forecast period.
- The retail segment is expected to capture most of the market share over the forecast period.
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Regional Stance:
North America is expected to have most of the market share in machine learning as a service over the forecast period. The creation of novel learning algorithm theories and the continuous proliferation of low-cost computing and massive data availability have propelled recent advances in machine learning. Due to the widespread use of ML-based methodologies in research, technology, and industry, a more significant amount of evidence-based decision-making is occurring across various fields, including healthcare, biomedicine, production, education, financial modelling, data governance, law enforcement, and marketing.
The present status of the machine learning as a service (MLaaS) market in the United States has reached several prominent application areas, including healthcare, cyber-security systems, agricultural sustainability, data governance, and nanotechnology.
Machine Learning as a Service Market Scope
| Report Coverage | Details | |
| Growth Rate 2023 to 2032 | CAGR of 39.3% | |
| Market Size in 2023 | USD 31.73 Billion | |
| Market Size by 2032 | USD 626.64 Billion | |
| Base Year | 2022 | |
| Forecast Period | 2023 to 2032 | |
| North America Share in 2022 | 39.7% | |
| Solution Segment Share in 2022 | 63% | |
| Segments Covered | Component, Organization Size, Application, Industry Vertical, Geography | |
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Component Insights
The solution segment is expected to dominate the machine learning as a service market share over the forecast period. Businesses, especially smaller ones, often require more excellent experience or funding to develop their ML models. Pre-built solutions are appealing because they are easier to maintain and can be implemented quickly. It is constantly growing to include increasingly specialized and industry-specific applications. They provide customized solutions to solve company issues and produce observable outcomes, such as higher productivity or income. Businesses are shifting their emphasis from testing to real-world applications as they gain experience with ML. Discovering solutions is a quick way to get significant outcomes.
- For instance, in June 2023, a memorandum of understanding (MoU) was signed by ZainTech, the one-stop shop for digital solutions inside the Zain Group, and Mastercard to develop distinctive, data-driven, and cutting-edge solutions for companies operating in the Middle East and North Africa (MENA). Through the relationship, clients' operations will be streamlined, increasing efficiency and reducing costs.
Organization Site Insights
The large enterprises segment is expected to dominate the machine learning as a service market share over the forecast period. Due to their generally more significant financial resources, large businesses can make substantial investments in machine learning infrastructure and cutting-edge technologies. Large companies frequently have specific and scalable needs. It is difficult for smaller firms to compete when MLaaS suppliers catering to significant enterprises offer tailored solutions that can handle large-scale operations. These businesses frequently possess large volumes of data their operations produce, essential for developing and refining machine learning models. Its competitive edge stems from its access to large and varied datasets.
Application Insights
The market & advertising segment is expected to capture most of the market share over the forecast period. Decision-making in the advertising and market sectors heavily relies on data. Large volumes of data may be quickly and effectively analyzed by machine learning algorithms, which can yield insightful information on customer behaviour, market trends, and the efficacy of advertising. Based on historical data, machine learning algorithms can forecast future market trends and customer behaviour. By anticipating changes in consumer preferences and modifying their methods accordingly, companies in the market and advertising area can maintain an advantage over their competitors.
- For instance, in October 2022, Google Cloud extended its collaborations with app marketing platform AppLovin and tech consulting firm HCLTech. This investment will result in enhanced support for international campaigns, a more secure online delivery environment, and fast scalability of AppLovin's platform across Google Cloud edge cache network locations. Simultaneously, AppLovin claimed that without compromising user experience, it could streamline its core computer infrastructure under consolidated GKE and cloud storage locations.
Industry Vertical Insights
The retail segment is expected to dominate the machine learning as a service market share over the forecast period. With the growth of delivery services, direct-to-consumer business models, and highly personalized online shopping, generative AI can assist retailers in further unlocking several advantages that can enhance customer service, talent transformation, and application performance.
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Market Dynamics:
Driver: Increasing adoption of cloud computing
Cloud systems provide easily scalable resources to satisfy the different computational needs of operations using machine learning. Because of its scalability, businesses can effectively manage big datasets and intricate algorithms, which promotes the creation and application of machine learning models. A large selection of pre-built machine-learning resources and services are available from cloud providers. These technologies make designing and implementing machine-learning models, such as frameworks, libraries, and platforms, easier. For companies that do not possess the knowledge or resources to develop and manage their machine-learning infrastructure, this accessibility lowers the entrance barrier.
Cloud service providers frequently provide integrated solutions, including cloud-based machine learning capabilities and other services like analytics, data storage, and application development. Organizations may more easily integrate machine learning into their operations thanks to this smooth integration, which optimizes the entire machine-learning workflow.
Restraint: Potential biases in algorithms
According to the data they are trained on, algorithms are made to recognize patterns and anticipate outcomes. On the other hand, biased training data can cause the algorithms to reinforce preexisting prejudices, producing unfair and discriminating results. Various sources, such as biased training data, biased design decisions, and the prejudices the developers harbour, can cause algorithm biases. For instance, the algorithm may inadvertently duplicate and magnify social biases in its predictions if the historical data used for training contains biases related to gender or race. Due to this, decisions about hiring, financing, and the criminal justice system may be biased.
The use of machine learning models in decision-making by businesses and organizations is expanding, which raises ethical concerns about biased algorithms. Concerns regarding AI systems' fairness, accountability, and transparency are growing among consumers, regulators, and the public. Biases put businesses providing MLaaS at risk for legal trouble and reputational and ethical issues.
Opportunity
Increasing demand for AI solutions
Machine learning solutions that are both scalable and easily accessible are becoming increasingly necessary as companies from various industries realize how disruptive AI may be. To meet this need, MLaaS vendors create cloud-based systems that let businesses apply machine learning without requiring much in-house knowledge.
Several reasons, such as the need for automation, data-driven decision-making, and the incorporation of intelligent technology into corporate processes, have contributed to the increase in demand for AI solutions. By providing cloud-based infrastructure, pre-built algorithms, and user-friendly interfaces, MLaaS providers capitalize on this trend and help organizations implement machine learning models effectively.
Browse More Insights:
- Internet of Things (IoT) Market: The global internet of things (IoT) market size was exhibited at USD 328.6 billion in 2022 and is projected to surpass around USD 2,703.52 billion by 2032, poised to grow at a projected CAGR of 23.46% from 2023 to 2032.
- Cloud Computing Market: The global cloud computing market size accounted for USD 480 billion in 2022 and it is projected to hit around USD 2,297.37 billion by 2032, growing at a CAGR of 17% from 2023 to 2032.
- Industry 4.0 Market: The global Industry 4.0 market size was valued at USD 114.01 billion in 2022 and is expected to hit USD 634.94 billion by 2032 with a registered CAGR of 18.74% from 2023 to 2032.
- Digital Transformation Market: The global digital transformation market size surpassed USD 937.20 billion in 2023 and is projected to hit around USD 7,033.01 billion by 2032, expanding at a CAGR of 25.1% from 2023 to 2032.
- Data Analytics Market: The global data analytics market size reached USD 30 billion in 2022 and is projected to hit around USD 393.35 billion by 2032, registering a CAGR of 29.4% from 2023 to 2032.
Recent Developments:
- In September 2023, the debut of EY.ai was announced by the EY organization (EY). With the confident and prudent deployment of artificial intelligence (AI), clients may revolutionize their organizations with the help of this unifying platform that blends human competencies with AI. EY.ai uses cutting-edge EY technology platforms and AI capabilities, a strong AI ecosystem and extensive expertise in strategy, transactions, risk, assurance, and tax. The US$1.4 billion in investments made by EY laid the groundwork for the EY.ai platform.
- In June 2023, with great pleasure, we announce the successful completion of our acquisition of Rehaboo Oy. EvokAI Creative Labs Inc. is a leading MedTech AI-powered firm committed to producing transformative and innovative products for the healthcare sector. The primary offering from Rehaboo is a flexible physical gamification platform that encourages an active lifestyle and good brain health in any setting. It is built on high-definition motion-sensing technology driven by artificial intelligence.
- In September 2022, Lexicala, a content provider for Language Service Providers, introduced new multilingual lexical data solutions for use in academic research and the Language Technology sector. The solutions for natural language processing (NLP) problems include expert parallel corpora, domain categorization, morphology, text annotation, and premium cross-lingual resources. All language services are provided by Lexicala, including translation, categorization, alignment, annotation, and other NLP applications.
Market Key Players
- Microsoft Corporation
- IBM Corporation
- Google LLC
- SAS Institute Inc.
- Fair Isaac Corporation (FICO)
- Hewlett Packard Enterprise Company
- Yottamine Analytics LLC
- Amazon Web Services Inc.
- BigML Inc.
- Iflowsoft Solutions Inc.
- Monkeylearn Inc.
- Sift Science Inc.
- H2O.ai Inc.
Market Segmentation
By Component
- Solution
- Services
By Organization Size
- Small and Medium-Sized Enterprises
- Large Enterprises
By Application
- Marketing & Advertising
- Fraud Detection & Risk Management
- Computer vision
- Security & Surveillance
- Predictive analytics
- Natural Language Processing
- Augmented & Virtual Reality
- Others
By Industry Vertical
- BFSI
- IT & Telecom
- Automotive
- Healthcare
- Aerospace & Defense
- Retail
- Government
- Others
By Geography
- North America
- Europe
- Asia-Pacific
- Latin America
- Middle East & Africa (MEA)
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