5 Industries Where Machine Learning Adoption Will Make Waves


Machine learning (ML) is believed to be one of the technologies defining the future of humanity as we see now. Improvements in Machine Learning have accelerated the demand for its adoption across industries, especially since the beginning of the pandemic. 

The global machine learning market was at $8 Billion in 2019 and is projected to rise to $117 Billion by the end of 2027 at a compound annual growth rate (CAGR) of 39%. Astonishing, right? Another significant statistic is that the budget allocation increase for machine learning adoption is as high as 25% in many companies. 

Globally, we are yet to see the full scale of advancements through ML, but here is a look at five significant industries that lead the charge.

#1 – Healthcare

The Covid pandemic has uncovered the importance of streamlining our healthcare and pharmaceutical systems and the need for better investments in the field. Machine Learning comes into play here as a promising technology that allows healthcare suppliers to effectively handle large amounts of data, process and analyze it, and produce meaningful insights into diseases and their prevention and cure. ML also helps in the advancement of drug discovery and clinical trials, reducing developmental timelines and efficient resource and cost usage. ML can also improve delivery systems in healthcare and provide advanced care at lower costs. 

#2 – Transportation

Autonomous vehicles are already a reality, and the trend is only going to rise. Machine learning and AI have significant roles to play in this transformation. Vehicles are now better connected to centralized navigation systems. These systems also provide emergency assistance and predictions to ensure the safety of passengers. Technology also enables innovation everywhere in the transportation and automotive industry, from production lines to user comfort.

#3 – Banking & Finance

The banking and financial services industry is searching for opportunities to get out of archaic systems that support them, improve customer satisfaction, and prevent threats and frauds. Improved data management, analytics, and security protocols developed with the help of machine learning can achieve the goals mentioned above and overhaul existing banking models for the future.

#4 – Manufacturing

With machine learning adoption, the manufacturing industry is transforming already. ML will be crucial in analyzing the large volumes of data produced and providing accurate results that companies need. Manufacturers will see improvements in predictive maintenance, supply chain visibility, real-time error detection, and cost reduction, among other benefits from ML. As old-school factories are shifting to smart factories, ML will herald more noteworthy advancements in the days to come.

#5 – Retail

The pandemic has affected the retail industry significantly, but there is a lot of opportunity with the adoption of technologies like machine learning. Retailers adopting ML will see significant improvements in areas such as logistics, data analysis and processing, business intelligence, and market predictions. 

VEXXHOST helps many industries navigate the current tech and growth climate with our cloud solutions. We specialize in OpenStack-based clouds, serving clients from small businesses to governmental organizations and facilitate the right environment for machine learning adoption. For many of our clients, private clouds are the preferred choice because of their highly scalable and secure nature. Our Openstack-based clouds also ensure that customers are not faced with unnecessary licensing fees or vendor lock-ins on their clouds.  

Speaking of private clouds, you can now run on a fully agile and customized cloud from VEXXHOST, with no licensing fees and smooth 2-week migration. In fact, we’re ready to put our money where our mouth is. We’re so confident in being able to save you at least 20% or more on your current cloud infrastructure expenditure that if proven wrong- we’ll give you $1,000 credit to our public cloud.   

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