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Many industries are making the most out of AI and machine learning by implementing them in all business operations.
The global economy is going through a digital transformation. Industries are redefining and automating their operations by leveraging disruptive technologies like AI and robotics. The pandemic acted as a catalyst in the rapid disruption across all the sectors. An IDC forecast revealed that by 2023, the worldwide expenditure on the technologies and services that enable digital transformation is expected to reach $2.3 trillion.
Cutting-edge technologies like artificial intelligence, robotics, and analytics extensively use machine learning and its capabilities to augment human intelligence into machines. Machine learning plays a pivotal role in industry-wide transformation and automation. According to Fortune Business Insights, the global machine learning market size is projected to reach US$ 117.19 billion by 2027. Machine learning is the basic step industries should adopt to achieve automation and digitization. Many industries benefit from machine learning. Let us look at the top three industries that are leveraging machine learning to enhance the business and services.
Healthcare
There have been drastic makeovers in the healthcare sector in recent years, especially during the pandemic healthcare industry have carried out rapid digitization. The adoption of machine learning aids healthcare providers to perform more informed diagnoses using larger databases. Machine learning along with AI improved the process of vaccine development for Covid-19 by identifying protein structures and predicting possible immune responses.
Machine learning algorithms can detect patterns in the scans and X-rays to understand any unusual change in the health condition of the patient. For example, an ML algorithm developed by Google is capable of detecting breast cancer from mammograms.
The Healthcare sector leverages machine learning in maintaining electronic health records (EHR), monitoring patient’s health status, and personalized treatments. Robotic surgeries are performed with the help of both AI and ML to enhance precision and refer from data history of previous surgeries.
With machine learning in place, healthcare providers can detect and diagnose diseases more accurately and efficiently. Apart from all these, machine learning algorithms are now considered to have the capability of predicting pandemic and epidemic outbreaks.
Retail Banking
Data is the foundation of machine learning models, which they analyze to arrive at outcomes. The retail banking sector is going through a makeover and the combination of AI and ML provides exceptional benefits to the sector. Machine learning is responsible for automating repetitive and mundane tasks in the banks thus freeing employees from huge workloads.
Personalized customer service is the major change brought in by machine learning and AI in retail banking. Optimizing customer data and analyzing them will enable the sector to identify customer behaviors and trends.
The retail banking industry leverages machine learning for better risk assessment and fraud detection. Machine learning algorithms can work with AI to perform predictive analytics with maximum accuracy and minimum human intervention. When the banks employ machine learning models, it prevents and detects similar frauds, since the systems and machines are continuously learning from the data fed into them. The recent surge in digital transactions can bring in anomalies and frauds. Machine learning can monitor online transactions and flag suspicious payments with better efficiency.
Automotive
The use of AI in the automotive industry is escalating day by day. Machine learning plays a huge role in innovating products, checking the quality, and executing predictive analytics. The sector can leverage machine learning in flagging anomalies and detecting faulty parts in the vehicle manufacturing system by feeding images to the algorithms.
Predictive maintenance is another advantage of machine learning in the automotive industry. ML models can learn from various data sets and implement insights in producing customized maintenance plans. Predictive maintenance using ML can improve customer satisfaction, product design, and safety.
As data is the food and water for these machine learning models, they can be used to streamline supply chain management in the auto industry. This will enable identify product demands, tracking transportation, and smooth flow of inventory.