Implementing Artificial Intelligence and Machine Learning to tackle business challenges
Do you recall using any of these popular speech recognition systems like Apple Siri, Microsoft Cortana, Amazon Alexa? These systems make use of techniques like machine learning and deep neural network to mimic human interactions. In most of our daily tasks, we are making use of such technologies without our knowledge.
The most transformative technologies currently available are Artificial intelligence and Machine learning. These fast-evolving technologies are making a buzz and are influencing customer interactions and businesses in one way or the other. Nowadays, every business is attempting to introduce these technologies in their companies to unravel their business problems. Large corporations like Google, Amazon, and Microsoft are developing their private machine learning Platforms.
Let's get to know Artificial Intelligence and Machine Learning.
Artificial intelligence and Machine learning are the elements of Information technology that are usually interrelated with each other. Artificial intelligence enables the system to mimic human thinking. Whereas Machine learning is a part of AI that makes a machine discover and perform tasks automatically without actual programming. Both of these emerging technologies are used to create a smarter, intelligent device that is capable of thinking, responding, and solving complicated problems just like humans.
Companies that embrace these technologies can transform their business substantially and generate new avenues for business growth. Let us explore how companies are making use of AI and ML technology in different areas to solve their business problems.
Easing the manual data entry process
Manual data entry increases the probability of mistake occurrence and duplications, while automated method prevents these issues. Machine learning algorithms aids in automating the data entry process and the deployment of predictive models enhances the process by enabling machines to make accurate and data-driven decisions.
Recognizing the Spam
Machine Learning's primary feature is recognizing spam. Machines have learned to detect spam creating filters, and they can identify the junk emails and messages. The spam filters use ML to generate unique rules by themselves. Emails are now more concise, and with the ML & AI implementation, accounts are made safer, and data sharing is performed with high confidence.
Artificial intelligence and Machine learning are a tremendous benefit to the hospital and healthcare sectors. They are used to improve the health of the patient at a lower cost and help classify high-risk cases, provide suitable assessments, and recommend appropriate medicines. With AI & ML, clinical professionals who are aware of the medical and legal hurdles can manage the situation very efficiently.
Machine Learning technologies can address financial challenges by enabling frequent data assessments for analysis and identify anomalies and discrepancies to enhance model accuracy. Currently, ML in finance is used for algorithmic trading, portfolio management, fraud detection, and underwriting of loans. Future ML finance applications could include chatbots and interactive interfaces for customer care and security.
Image recognition and data visualization generate numerical or symbolic image information, as well as high-dimensional data. It includes machine learning, data analysis, database discovery, and pattern recognition. ML can recognize image patterns based on the given data. The usage of Image recognition technology is found in healthcare, campaigns, automotive(driverless cars), and other sectors.
Lifetime Value Prophecy and Customer Segregation
One of Artificial Intelligence's significant achievements is estimating the customer's lifetime value and segregating the customers accordingly. It lets business firms learn more about brand loyal customers and their preferences and introduce personalized marketing deals to generate more revenue from sales. Many business entities offer segmented exclusive sales propositions based on the data mining processes.
In the retail business, many popular e-commerce websites like Flipkart, Myntra, and Amazon use machine learning technology to recognize commodities in which the customer is interested and willing to purchase, based on the previous procurement activities. The machine learning algorithm analyzes customer behavior and their approaches to different products and focuses on grouping similar items together. The ML algorithm model facilitates the system to make recommendations to the customer and encourage them to purchase products.
It is, therefore, evident that the implementation of machine learning can solve most of the business challenges. Adopting Al and ML into the business helps boost revenue and efficiency, enhances decision-making and business automation processes, and enables enterprises to identify anomalies more quickly.