The global machine learning market size is projected to reach $152.24 billion in 2028, says a report from Fortune Business Insights.
The study says that the market stood at $11.33 billion in 2020. It is expected to project a CAGR of 38.6% during the forecast period.
The increasing requirement of digitalisation amid the pandemic, in order to maintain the social distancing regulations imposed by the government is expected to boost the demand for machine learning technologies during the upcoming years.
For instance, in April 2020, the Massachusetts Institute of Technology (MIT) researchers developed a model which utilises data from the COVID-19 pandemic that further leverages machine intelligence algorithms to detect or predict the spread of the virus and the potency of quarantine measures.
COVID-19 Regulations to Positively Affect Global Machine Learning Market Growth
The COVID-19 pandemic has affected the health condition, financial situation, and has disrupted the social system of several countries. Individuals are subjected to profit from understanding their mental health and coping with it in these unprecedented times. The government has imposed several regulations regarding the virus as well have encouraged some businesses to continue working as they do not violate the lockdown laws.
The application of artificial intelligence technology is likely to help in combating the COVID-19 pandemic. Several nations are utilising population surveillance techniques to track COVID-19 cases. For instance, South Korea is utilising these techniques involving geo-location data to trace the people affected by the virus.
Drivers and Restraints
Significant Investments in Machine Learning (ML) to Stimulate the Market Growth
The commercial usage of artificial learning is rising in developed and developing economies. Therefore, there is a fierce competition among the market players to maintain their position by funding, developing, and acquiring artificial intelligence technology based startups.
For example, Hypersonix provides AI-powered autonomous analytics platforms/solutions. KFBIO, a digital pathological system provider and Xsight Labs, create innovative developments for appliance intelligence, data analytics, and segregated storage.
On the other hand, Deepfakes generated by AI-enabled fake content are considered to breach security and pose a threat to any nation. Anyhow, the concept of allotting AI licenses can overcome this negative trait. For example, Responsible AI licenses, also known as (RAIL), authorise the software developer to issue open-source ML software with a license. This terminates the risk of illegal use of the software.
North America captured the maximum market share in 2020 and is expected to continue to further dominate the machine learning market share.
It generated $ 4.05 billion in terms of revenue. The factor boosting the growth of this region is the presence of giant R&D investors such as IBM Corporation, Amazon.com, and Oracle Corporation.
Europe is expected to project strong growth in the global market. The growth is credited to the rising usage of this technology in developing markets such as Germany and the United Kingdom, with a huge population of workers and skilled labourers.
Asia Pacific is anticipated to showcase a phenomenal growth rate in the foreseeable future.
The developing nations in this region such as China, India pose a flourished and sturdy startup ecosystem with assistance from surging skilled workforce that steers market growth across the region.
The prominent players in the market are on a constant lookout for apt opportunities to expand their business and create a strong foothold in the global market. For this, they launch products, develop solutions, and partner up with other key companies.
Largest player Google LLC launched a collection of services under the name Product Discovery Solutions for Retail. This exclusively launched solution is majorly open to all businesses and promises to solve AI and machine learning related problems. Additionally, it gives access permission to Google AI Recommendations that further uses machine learning to respond to various other factors.
