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Artificial Intelligence (AI) has come a long way from the confines of science fictions to becoming a household name in terms of ‘Hi Alexa,’ and subsequently moving towards hardcore commercial domains. Today, AI is a mainstream concept that is driving the human society towards higher heights while enjoying greater comfort, increased efficiency, and improved security. Businesses are fast taking advantage of Artificial Intelligence in general and its specialized domain Machine Learning (ML), to make disruptive changes in their operational modes and gain the competitive edge for higher returns.
Machines and gadgets are able to engage in several humanlike activities that include analyzing, sorting, planning, learning and problem solving. All of these include Artificial Intelligence and are directed to specific use in defined areas of human life and living. AI algorithms are able to make a wide latitude of decisions and act on their own even in situations unforeseen by the programmers.
Machine Learning is among the most commonly used variant of AI that is being deployed by businesses to increase operational efficacy & better returns. Machine Learning algorithms train gadgets to extract data and insights from raw data inputs to produce data-rich relevant business results. In other words, ML algorithms learn from iterative data to improve operations and enhance scalability.
Data is everywhere. But businesses need to mine the vast data, analyze the colossal volume quickly and systematically to get extract relevant data that will help improve their respective operation, generate leads, predict customer preferences, maximize sales opportunities, offer personalized experiences and increase customer satisfaction, and subsequently rake in higher revenues. Organizations of all sizes are increasingly using ML to augment business processes, make faster business decisions, and avoid probable human errors.
Studies reveal that the prime concern of AI and ML use in businesses lies in gaining the competitor advantage and its allied incentives. This is not to say that AI can transform businesses on its own, but, that it works best when complementing human efforts. AI-based technologies are fast replacing lower-rank and repetitive tasks, extending voice assistance, recognizing people and patterns for better security and more – all for the sake of better business management every day.
Machine Learning is all about extracting meaningful information from raw and unprocessed data to solve a wide spectrum of business complexities, problems, and predict complex customer behavior. Here’s a list of ways on how AI and ML are impacting businesses positively now and for the future.
Machine Learning algorithms can sift through huge unstructured data emanating from different sources, extract relevant ones to form structured analysis and give crucial information about the business. Using Business Intelligence is among the frontline uses of AI among organizations to rethink current operations, make studied decisions to improve them and apply them at points where they will positively impact the business.
Inaccurate and duplicate data errors are among the most common reasons that plague operational efficacy of businesses. Using Machine Learning predictive algorithms can help eliminate such manual error, reduce workload, cut down on operational expenses and increase overall efficiency.
ML is being extensive used by organizations and financial institutions for portfolio management, customer profile identification and verification, loan approval and underwriting, and several other related areas. Future ML algorithms are set to include chatbots that are enabled to carry out customer service, sentiment analysis while monitoring security.
Data mining that is followed by Machine Learning and database knowledge discovery, allows gadgets to produce symbolic and numeric information from images and high-dimensional data. These are being extensively used in automobile industries, healthcare sector, law enforcement departments, and a host of other agencies.
Businesses are extensively using ML to learn more about customer behavior to up revenues. Data mining and ML are helping identify customer purchase patterns, and subsequently send personalized offers and suggestions for future shopping. The entire process is based on individual customer browsing patterns, and buying history. This is something that is unthinkable to achieve manually, but the use of ML has made it an integral process of most businesses.
Seamless analysis of customer behavior, analysis of call recording and addressing them by the appropriate customer care executive can help improve customer satisfaction and take it to a different level. The process can help reduce overall costs and time that the management has to invest in customer relationship while retaining happier customers.
Regular and timely maintenance of manufacturing facilities is crucial to keep production at optimal levels. The use of ML to identify hidden patterns and provide meaningful insights helps do away with ineffective and expensive predictive maintenance. Machine Learning algorithms help reduce risks associated with unexpected failures using historical data, flexible analysis environment, workflow visualization tools and feedback loop.
With much of organizational activities and business processes happening online, increased cyber security has become a prime concern for most businesses. ML is being extensively used to solve issues concerning cyber security, build newer technologies to detect and identify unknown threats, helping draw up better security plans for organizations.
Artificial Intelligence and Machine Learning are letting humans create a knowledge-based economy that is leveraging automation for a better society. It is designing 3D experiences and more for businesses and people from across drawing-rooms and boardrooms. Overhauling business processes to running driverless trains and cars, there is an enormous amount of data to deal with that AI and its specialized branch ML is carrying out with speed and accuracy. The thrust is no longer on users finding businesses, but businesses finding the target user before others do!
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