By now, most executives understand that machine learning is a type of artificial intelligence — but that doesn’t mean that most executives understand how to make the best use of machine learning. Unlike other AI tools, machine learning leverages the power of algorithms to create programs that gradually improve in accuracy and quality over time. Already, there are hundreds of machine learning solutions that improve business operations, and most fall under the umbrella of one of the following five use cases:
User Behavior Analysis
Many executives would give their right arm to know exactly what their target audience is thinking — but with machine learning, business leaders can keep all limbs firmly attached. User behavior analysis involves collecting data on consumer behavior and analyzing it to provide insights related to purchasing habits, market trends, popular products and more. While it is possible to run these kinds of analyses without the help of machine learning, augmented analytics tend to be faster and more accurate, giving executives to-the-minute information that allows them more precise control over inventory management, marketing and so on.
What’s more, consumers are not the only users whose behavior can be analyzed by machine learning algorithms. Many organizations use ML-driven analytics to better understand their employees’ needs and wants, with the result of a healthier and happier workplace with higher productivity and better performance.
Not all automation falls under the umbrella of artificial intelligence. In fact, many industries have used automation for decades, long before machine learning tools were available for business use. However, machine learning can radically improve the effectiveness of almost all automated solutions, now and into the future.
Customer service tools are some of the most popular automated solutions employed by businesses, and for good reason. These tools alleviate a significant amount of pressure on customer service departments by fielding the simpler and more common queries from customers. Armed with machine learning, automated customer service solutions can channel users through customer service with greater efficiency, bringing greater satisfaction to all.
Manufacturing automation is another system that can benefit from machine learning enhancements. Machine learning algorithms can help manufacturers identify errors, deficiencies and other pain points. The result is lower expense and less waste, which is always good for business.
The more digitally mature a business is, the more important security becomes. Cybercriminals are eager to access business networks to steal valuable business data, and attack methods are becoming more complex and more difficult to avoid. Small businesses in particular are being targeted in cyberattack campaigns, so it is essential that cybersecurity is a high priority for every executive.
Though machine learning is not yet a popular tool in cybersecurity, it is almost certain to be vital in the cybersecurity strategies of the coming years. Machine learning and AI both allow cybersecurity systems to adapt quickly to the ever-shifting landscape of cyber threats. Thus, as attack methods change, a business’s security can remain strong when bolstered with algorithms that learn and improve on their own.
A business’s finances must be strong for that business to be successful. Though not every business leader is well-equipped with talent in financial management, any business leader can make good use of financial management tools driven by machine learning. Financial analytics that utilize machine learning capabilities can be applied to both simple and complex financial responsibilities. Many executives uncomfortable with machine learning begin by applying the tech to basic tasks, like predicting business expenses or performing cost analyses, but eventually, executives who come to trust machine learning will rely on tools for advanced tasks like fraud detection and algorithmic trading. The result is a better financial management system for guiding executive-level decision-making.
Finally, machine learning is uniquely qualified to provide organizations with a set of cognitive services that can improve business processes in a variety of ways. Some of the most popular cognitive services include:
● Natural language processing, in which computers can communicate with users with words and in language patterns that come naturally to humans. Natural language processing has become a must-have for customer service tools, search tools and more.
● Image recognition, in which computers are capable of deriving meaning from images. The applications for image recognition tools are nearly endless; some companies use it for product identification, others for user authentication and others for issue diagnosis.
It is a mistake to assume that machine learning is a less-powerful version of AI. In fact, more businesses can make better use of machine learning tools — but only if executives understand how to use machine learning within their existing business strategies.
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