Global Machine Learning Market Size To Reach Around USD 302.62 billion by 2030 | CAGR of 14.91%Category: Information & Technology
The Global Machine Learning Market Size was valued at USD 14.91 billion in 2021 and is expected to reach at a compound annual growth rate (CAGR) of 38.1% from 2021 to 2030. The worldwide market is expected to reach around USD 302.62 billion by 2030. According to a research report published by Spherical Insights & Consulting. The machine learning is a process that uses artificial intelligence (AI) to provide a system the ability to automatically learn from experience and get better over time without being explicitly programmed. The development of a programme that can access data and utilize it to learn for itself is the major goal of this technology.
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An area of artificial intelligence known as machine learning allows machines to learn directly from data, experience, and examples. Machine learning enables computers to carry out certain tasks intelligently by learning from examples or data rather than by following pre-programmed rules, allowing computers to carry out complex procedures. A comprehensive repository for machines to learn from is created by the growing volume of data collected across industrial verticals. This is further supported by the quick advancements in computer processing power, which in turn improve the analytical skills of machine learning systems.
Browse key industry insights spread across 231 pages with 119 market data tables and figures & charts from the report ”Global Machine Learning Market Size By Component Type (Software, Services), By Organization Size (Small and Medium-Sized Enterprises), By Application (Fraud Detection and Risk Analytics), By End Use (Automotive, Aerospace & Defense, Retail & E-commerce, Government, Healthcare & Life Sciences, Media & Entertainment, IT & Telecommunications, BFSI, Others), By Region (North America, Europe, Asia Pacific, Middle East & Africa, and South America) – Market Size & Forecasting To 2030.“ in detail along with the table of contents. https://www.sphericalinsights.com/reports/machine-learning-market
Growing technological improvements that improve system accuracy are driving market expansion. People engage with a variety of machine learning-based systems, including voice recognition, image recognition, and recommender systems. The demand for machine learning in many systems has been spurred by the rapid improvement in image recognition technology, which has boosted the system's accuracy. For instance, in the image labelling challenge, machine learning's accuracy increased from 72% in 2010 to 96% in 2015. Machine learning has become a crucial tool in many areas, including BFSI, healthcare, and others, thanks to computers' ability to process massive amounts of data and apply it for prediction.
The machine learning market has also expanded due to the integration of machine learning in robots. Robotics has undergone numerous developments as a result of the rapid development of sensing technology and materials. The development of machine learning has enhanced robots' capacity to contribute to projects like autonomous vehicles and drones. Additionally, the market has grown as a result of the rising demand for advanced robotic systems across numerous industries, including automotive, electronics, food and beverage, and healthcare. Around 294,000 industrial robots were deployed worldwide in 2016, according to the International Federation of Robots.
The scarcity of qualified individuals with analytical ability is the main challenge most firms encounter when integrating machine learning into their business processes, and the demand for those who can monitor analytical content is even higher. Privacy issues have dominated technological development and new algorithm development since the advent of big data. The same is true for machine learning, which simply trains itself to think for itself using massive data. These are a few of the main things stopping the market from expanding.
Covid 19 Impact on Global Machine Learning Market
The Covid 19 mishaps have an effect on other industries, such as machine learning. In the midst of pandemics, some sectors grow despite the grave situation and the unsure outcome. The machine learning market was stable and had growth potential during the time of COVID 19. In contrast to several other industries, machine learning had a relatively small impact on the global market.
Global Machine Learning Market, By Component
The services segment is anticipated to experience consistent revenue growth over the projection period. By automating the process of turning data into insights, businesses can achieve a variety of objectives, such as successful customer retention, predictive modelling for anticipating customer behaviour, and 360 Degree Customer View for a deeper understanding of consumers.
Global Machine Learning Market, By Organization Size
The global machine learning market is segmented into small and medium-sized businesses and large businesses based on the size of the company. The segment of small and medium-sized businesses is anticipated to experience consistent revenue growth over the course of the projected period. Small and medium-sized organisations are increasingly using ML approaches to access digital resources and lower their Information and Communications Technology (ICT) investments. Rapid development and highly engaged SMEs have boosted their use of ML solutions and services globally as a result of growing digitization and increasing cyber risks to critical company information and data.
Global Machine Learning Market, By Application
The global machine learning market is segmented based on application into artificial intelligence, computer vision, augmented and virtual reality, natural language processing, security & surveillance, marketing & advertising, automated network management, predictive maintenance, and others. During the anticipated period, the predictive maintenance segment is anticipated to experience consistent revenue growth. Manufacturing facilities must use corrective and preventative maintenance techniques. These techniques, however, are typically expensive and ineffectual. ML helps create incredibly effective maintenance strategies. These can lower the likelihood of unexpected failures, leading to a decrease in the number of preventive maintenance projects.
Global Machine Learning Market, By End Use
The automotive, aerospace & military, retail & e-commerce, government, healthcare & life sciences, media & entertainment, IT & telecommunications, BFSI, and others segments of the global machine learning market are based on end-use. The BFSI segment is anticipated to experience consistent revenue growth over the anticipated time frame. Popular applications of machine learning in the BFSI industry include algorithmic trading, portfolio management, loan underwriting, and, most importantly, fraud detection. The system also provides continuous data assessment, which, by identifying and evaluating anomalies and subtleties, contributes to improving the accuracy of financial models and rules.
Global Machine Learning Market, By Region
During the time of forecasting, the European market is anticipated to experience consistent revenue growth. There is an increase in need for qualified personnel as the market for machine learning and AI services is expanding quickly, which is followed by swift technological improvements. The European Commission claims that legislation and regulations pertaining to AI and ML are complex. Despite the fact that the European AI business is seeing considerable revenue growth, the discrepancy between existing standards and the capabilities of new systems is making it difficult for systems to be compliant. In addition, compared to nearshore locales, European businesses are finding it harder to outsource.
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Some Recent Developments in Global Machine Learning Market
- January 2022: Amazon and Stellantis collaborated to roll out customer-focused connected experiences across millions of vehicles in order to hasten the software transition for Stellantis. The partnership is expected to alter the in-vehicle experiences of Stellantis customers and hasten the transition of the automotive industry to a software-defined sustainable future.
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