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Here Is How Machine Learning is Transforming These 5 Industries

When Digital Transformation is the topic of conversation amongst CIOs, machine learning has caught everyone’s attention. With its ability to automate things and facilitate improved, data-based decision-making, machine learning has become a priority for most of the CIOs. A study found that for 53% CIOs, machine learning is a focus of digital transformation efforts. Machine learning is undoubtedly changing the enterprises operate.

Did you know that the patents of Machine learning grew at a CAGR of 34% between 2013 – 2017? This is recorded as the category that is the third-fastest patent growing category. Google, Microsoft, IBM, Intel, Facebook, LinkedIn, and Fujitsu are leading the ML patent producers.

With the volume of structured and unstructured data growing every single day and the process of computation becoming cheaper, it is no surprise that the adoption of machine learning is growing at a rapid pace. There are several examples of successful adoptions too –  Netflix saved $1 billion in a year by implementing machine learning algorithm!

Almost every sector is influenced by ML. Let’s take a look at five of the top industries that have been swayed away by the advent of machine learning. 


According to Practica, it is predicted that ML in the automotive industry would increase by 48% by the end of 2025. With increased globalization, leveraged competition, and the pressure of keeping the costs low, a shift in the trends of the market has occurred. Though a large part of the automotive industry still relies on human-made decisions, inducing machine learning promises to bring about business as well as operational transformations in the industry by boosting the accuracy of the decision imposed by a smart system. Machine learning makes personalization possible which has enabled automotive companies to create specific profiles for their users. These profiles help in not only targeted marketing but also assist in effective planning and execution of their auto maintenance needs. The other most significant impact of machine learning in the automotive industry is the incorporation of customer feedback results with greater accuracy. Companies can now study even the social media conversations and build subsystems that guide future products. That apart, ML also helps in identifying the relationships between machine failures and the underlying causes.


The changing economic dimensions and rising consumer expectations have forced the media and entertainment industry shift its outlook towards technology. This industry is betting strongly on evolving technologies and automation tools. By incorporating machine learning and automation, the entertainment industry is able to effectively tag metadata, also organize, create and categorize data rapidly and create highly personalized experiences for their consumers. Machine learning is allowing the media companies identify the topics that would interest their audience and stream the relevant content which is sure to draw audience attention. It is helping them ensure the increased value of content, lesser efforts and operational time with enhanced user experience


With the advent of machine learning, manufacturing industries are now incorporating smarter machines. Machine learning is enabling manufacturers to make sense of the large volume of data that is generated by the machines and gather actionable insights from that. These insights help them find efficient solutions for intricate problems. With the use of machine learning, manufacturers are experiencing higher production rates, efficient operations, and faster time to market. That apart, it is also helping them optimize their supply chain operations.


Did you know that the Deep Learning Machine of Google is capable of detecting breast cancer at an efficiency of 89% whereas pathologist is found to be 74% efficient? According to estimates by Forbes, by the end of 2025, digital heart health monitoring systems and sensors, when used in conjunction with machine learning, could lead to the saving of €150 billion! With such huge figures, the impact of Machine Learning in the healthcare industry is revolutionary. Healthcare is one such sector which is flooded with data. Millions of patients are treated each day for a variety of diseases and the corresponding batteries of data become difficult for humans to evaluate. With the use of machine learning, healthcare organizations can identify patterns even in the unstructured data leading to better planning, better care, and enhanced clinical decision making. Machine learning algorithms are also capable of reviewing large volumes of image datasets to quickly identify abnormalities and the areas which need attention. This helps in improving efficiency, reliability, and accuracy of medical decisions.


Machine learning is set to revolutionize the retail industry. Automated checkouts, in-store robots, conversational agents which can suggest products to consumers or answer their common questions – all these are examples of machine learning at work in retail. Machine learning is helping retailer offer highly personalized product recommendations in marketing and advertising. It allows them to dynamically optimize the product pricing based on demand, supply, and seasonality.  Using machine learning, retailers are able to optimize their inventory and make deliveries more efficient. It is also helping them predict customer behavior and deploy sales and support staff where they can be more effective.

With increasing use of machine learning, AI, and Analytics, these industries have dramatically changed the way they interact with their customers and have also transformed their operations and become more effective and efficient.  The efficiencies gained through machine learning are substantial so it does not come as a surprise that companies across various industry verticals have machine learning projects high on their corporate agenda. Through appropriate investments in the right resources and by identifying the right use cases, companies can derive real business value from machine learning.

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