The latest breakthroughs in the field of Machine Learning have sparked a revolution that no one could’ve ever imagined. As an emerging technology, it is disrupting many traditional practices followed by businesses. In fact, according to a recent report, the global market size of Machine Learning was valued at 15.44 billion USD in 2021 and it is predicted to surge from 21.17 USD billion in 2022 to 209.91 USD billion by 2029 with a compound annual growth rate (CAGR) of 38.8%. From the statistics, it is clear that the future of Machine Learning looks quite promising since it is showing no signs of slowing down in the years to come. This may be one of the reasons why Machine Learning has been the most debated topic among CIOs, CTOs, and CXOs.
Despite being a popular topic of discussion among the C-suite audience, Machine Learning is often used interchangeably with AI. However, Machine Learning is a subset of AI that enables systems to learn from data and previous experiences and make accurate predictions with little or no human intervention. Today, many big names in the industry have already started leveraging the potential of Machine Learning in their business. Besides industry titans, a large number of Startups and SMEs are also embracing Machine Learning to bring transformative changes.
Machine Learning comes with an unmatched potential to analyze large chunks of data, which in turn enables businesses to make data-driven decisions with better accuracy. Besides data analysis, Machine Learning models can help businesses streamline complex workflows and automate manual and repetitive jobs resulting in improved workforce productivity and efficiency. Simply put, Machine Learning services are actively making their way into businesses’ core operations.
3 Key Benefits of Machine Learning for Businesses
Many enterprises have already adopted Machine Learning since it offers a host of benefits to businesses. Let’s take a quick look at the key advantages of embracing Machine Learning.
1. Predicting Customer Lifetime Value
Many businesses struggle when it comes to predicting customer lifetime value since they are inundated with massive volumes of data. However, using Machine Learning models, businesses can not only process huge amounts of data they have but also extract meaningful insights out of it. Based on the derived insights, businesses can conduct customer segmentation and predict purchasing patterns and customer behaviors based on their browsing experience and buying history.
2. Work Process Automation
Another major challenge faced by businesses is data duplication and inaccuracy. With Predictive Modeling and Machine Learning models, enterprises can automate manual and repetitive tasks performed by humans resulting in reduced errors and improved work efficiency. By implementing Machine Learning, businesses can free up employees from tasks that require intense manual labor and let them invest their productive time in the activities that add value to the business.
3. Product Recommendation
Today, many eCommerce store merchants use Machine Learning models to offer the most relevant products to customers by analyzing their historical behavior. Machine Learning helps merchants improve cross-selling opportunities, which in turn, improves customer experience and sales.
Industries to Look Out for Machine Learning Disruption
Businesses are actively adopting Machine Learning (ML) models to improve customer experience, drive innovation, increase ROI, and gain a competitive edge. Let’s take a quick look at how Machine Learning will shape businesses across industry verticals in the days to come.
Banking and Finance
Businesses operating in the BFSI vertical are already using Machine Learning for fraud detection and offloading repetitive tasks to digital workers (intelligent bots). However, in the coming years, more mature use cases of Machine Learning will be explored in other critical areas such as customer sentiment analysis, investment modeling, trading, risk prevention, and more.
Future Machine Learning models will be helpful in replacing human intuition in investment forecasting and predicting stock prices. This will help traders in taking preventive measures and minimize the risk before market crashes. In fact, Osman Ali, a Portfolio Manager, Quantitative Investment Strategies at Goldman Sachs says that Machine Learning will be a robust tool in asset management. Furthermore, Machine Learning when combined with predictive analytics will also help banking and financial institutions improve transaction efficiencies.
The healthcare industry churns out large volumes of data and nearly 80% of data in the healthcare vertical is unstructured. By applying advanced Machine Learning models, healthcare providers can not only streamline the data but also make data-driven decisions on disease predictions and treatment options. In fact, physicians are actively collaborating with statisticians, data analysts, and data scientists to engineer advanced tools that will accurately predict diseases. Besides accurate disease predictions, ML models will be used in automating the drug discovery process resulting in reduced time-to-market.
More and more manufacturers are leveraging the potential of data to improve their production and assembly line – all thanks to Machine Learning. This emerging technology not only helps manufacturers in analyzing large volumes of data generated but also serves as the foundation of Industry 4.0 coupled with data connectivity and automation.
In the days to come, manufacturers will look at more mature use cases that are beyond Predictive Maintenance such as Digital Twins, Real-time Error Detection, Cost Reduction, Warehousing Efficiency, Cognitive Supply Chain Management, and Smart Manufacturing. According to a report, the global smart manufacturing market is predicted to grow at a CAGR of 8.4% from 2021 to 2026 and will reach $314.39 billion by 2026.
Machine Learning has become an integral part of businesses both large and small alike. This emerging technology has a lot to offer and can help companies in unlocking the door to many new opportunities. If you haven’t implemented Machine Learning technology in your business and want to leverage its potential, you should consider partnering with a reliable Machine Learning development solutions provider. Companies like Damco Solutions can help you successfully implement Machine Learning models tailored to your business requirements.