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Business Side Of Machine Learning: How Business Leaders Are Leveraging The AI

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CIOInsider Team

Three to four decades ago, the idea of machine learning (ML) would have exhilarated the worst imagination in the minds of the people of AI taking over the planet. In today’s time, Machine Learning (ML) is so common that people barely notice it, as more of the analog world gets digitized. Just as mass production changed the way products were assembled and made, Machine Learning will improve the way businesses optimize their services and offerings. Machines may not be taking over the planet anytime soon, but machine learning certainly has done that. It is becoming less of a mysterious thing but rather a necessary up- gradation for society, to function in this globalized world. Machine Learning (ML) is based on certain algorithms which enables the AI to learn from data, without relying on rule based programming. In other words, Machine Learning is a combination of many fields such as computer science and statistics that enables the AI to analyze the data and recognise and learn patterns independently.

As the field of machine learning is increasingly becoming mainstream, companies are increasingly using ML for conducting many aspects of their business operations. To be competitive in this new decade, companies would have to be investing in data driven technologies in order to survive. Certainly, many companies have started to use AI for automating their processes. In order to achieve the maximum output companies however, must not only rely on automated bots but an efficient modern work environment is one in which both humans and AI work together. Businesses have started to realise that both humans and AI complement each other perfectly, as humans have a completely different skill set from that of an AI. The leadership,

creative and social skills of humans fits perfectly with the ability of machines to analyze gigabytes of data in the fraction of a second. Let us look at some innovative ways in which businesses are leveraging machine learning in its day-to-day operations:-

• AI assistance is being used to display complex human emotions such as sympathy and care. Consider Microsoft’s AI assistant Cortona, the bot has a confident, caring , helpful and not too bossy qualities - instilling those qualities took countless hours of research and a team comprising of novel, poets and scientists. Similarly, human trainers were needed to develop Siri, Amazon’s AI assistant.

• Many Tech. Companies like Apple and Amazon, uses AI to collect personal details of its customers as they engage with the company’s devices and apps. The aim is not only to enhance user experience but also gather valuable information regarding customer preferences and habits to take the business to the next level.

• In the manufacturing industry, robots have evolved from dangerous and dumb industrial machines to smart, context aware “cobots”. Cobot for instance can perform a repetitive task which requires heavy lifting. Hyundai has taken the Cobot concept one step further by introducing entire exoskeletons which has enabled them to do their manufacturing job with superhuman endurance and strength.

• Car manufacturing is a rigid process that involves automated steps executed by dumb robots. Mercedes however, replaced some of those machines with AI cobots in a plant in Germany to make the process more efficient and less tedious.

• For some businesses speed is the ultimate objective. One such operation is the detection of credit card frauds. Therefore, banks such as HSBC have developed an AI solution that improves the speed and accuracy of fraud detection. The AI monitors records millions of transactions daily with the help of information such as customer behaviour, IP addresses and other subtle information.

• Food delivery apps such as Swiggy and Zomato have chat bots installed in their apps to quell any customer complaints and issues. This is a cost effective measure as it does not require a team of customer service executives.

• Job search sites such as Naukri and others have AI bots that do the initial stages of hiring by searching for keywords in resumes, screening out the desired candidates for the next process of hiring.

Human machine collaboration has enabled the companies to interact with employees and customers in a novel and effective way. To take full advantage of this collaboration companies and business leaders must understand how humans can augment AI machines better, how machines can enhance human activities and most importantly change the entire business process to support this partnership.

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