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Top 10 Problems Machine Learning in Business Is Able to Completely Solve


Machine learning has already proven its viability – it solves more and more tasks in various fields. As technology develops, the scope of application of intelligent systems with machine learning will grow – and the farther away, the more difficult will be the problems solved with the help of data mining. In this article, we have collected ten main problems of modern business, which currently can be solved with AI computing technologies.


The Problem of Correct Prediction of Events in the Client’s Life

Machine learning enables to predict not only customer behavior patterns, but also changes in his life. Like behavioral factors, potential changes can be predicted based on the data that users leave publicly available. For example, if a person bought a car on credit, then ML algorithms are able to analyze the purchase history and predict when he needs insurance and come up with motivating product purchase.

The Problem of Predicting Unplanned Breakdowns or Downtime

It is always easier to prevent a problem than to solve it. By adhering to this principle, machine learning for enterprise is able to analyze the state of the working equipment, collect data on the latest professional development of employees and make a forecast. Thus, with the help of predictive analytics, it becomes possible to foresee equipment breakdowns leading to downtime and prevent them. This approach also allows companies to increase the equipment life due to the maintenance provided in time.


The Problem of High Risks and Winning Strategies Development

Doing business, we are constantly forced to make decisions that are going to determine the fate of our company. Even being fully aware of the pros and cons of his action, a person can not always be objective. It seems to us that we are guided by logic and common sense, but very often personal interest or other feelings dominate. With Machine learning you can only make rational decisions, analyzing and minimizing possible risks. Thus, one of the benefits of machine learning in business is the fact that it is able to build the most profitable and effective business strategy, which will be based on real indicators of growth and falls and public moods. Moreover, the amount of data analyzed will be incomprehensible to the human brain.


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ML replacing human strategy development


The Problem of Heavy Workload on Employees

Machine learning automizes monotonous tasks such as making reports or submissions, so employees get rid of routine work or tasks of the same type, which requires extreme concentration. People receive an opportunity to work on projects in a creative way and contribute to the maximum efficiency of the business. There is a widespread opinion, that robots might completely replace employees, but it is not true. Actually AI should only enhance the human force while they are working together. Such collaborative robots are called co-bots. The executive director of MIT’s Work of the Future Task Force claims that robots just enable employees to work on more complex tasks which results in upwards growth for a particular industry.


The Problem of a Large Amount of Work and Low Productivity

This problem is directly related to the previous one. When employees are forced to perform a large number of tasks in a short time, productivity drops. The same happens to the level of the customer service, profits, and reputation of the company. With machine learning technologies, it is possible to avoid this problem by outsourcing some of the tasks to the computer systems. The exact implementation of this can be such robots as “Chloe” that sells iPhone chargers and plug adapters, while human assistants can meanwhile focus on goods maintenance and repairs. Another case is with Adidas robotic plant or “Speedfactory”, where the manufacturing of textile, footwear and clothing is performed by a robotic hand which will eventually make Adidas product more affordable for everybody.


The Problem of Inefficient Customer Interaction

Chatbots that today are able to answer standard questions have already become a must-have. They significantly reduced the burden on support services. However, modern systems continue their training, and they are able to work not only with FAQs but also with problematic queries including. Such a machine learning model is able to analyze the user’s appeal with keywords, and send it to the appropriate department for processing. This contributes to a faster response to incoming requests and frees up more resources to effectively solve customers’ problems.


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The Problem of Creating Products That Would Be Perfectly Combined with Each Other and 100% Suitable for the Client

Do you remember how seamlessly Apple products interact with each other? Today, this company continues to use the advantages of machine learning for its favor. So, Apple Watch can recommend playlists from iTunes, which are ideal for the user’s heart rhythm. Thus, machine learning for enterprise can not only make recommendations about products that are relevant to the client based on predictive modeling but also give recommendations about the characteristics of new products that can be created based on the needs of the user.


Apple Leveraging Machine Learning


The Problem of the High Cost of Advertising, Its Mass Nature

If ten years ago, companies knew only the socio-demographic profile of their consumers, but today they have data on how they spend their leisure time, where they go shopping, what they buy and how much they pay for it. And it is machine learning that helps companies link this data and use it to increase advertising effectiveness. Today, machine learning in advertising performs the main function – makes advertising campaigns 100% targeted. This allows the business to distribute the advertising budget as reasonably as possible.


The Problem of Custom Content Value

Every day tons of useless content are poured into the network. Here it is possible to draw an analogy with spam letters. All that today falls into the Spam folder is just one tiny part of spam letters that freely walk around the network. One of the main benefits of machine learning and AI is the fact that this technology is able to identify spam emails and filter them. Analogously, this tool can effectively work with content, showing your users the information that they need based on their requests and other data known about them. For example, Pinterest, Yelp, Next Door, and Discuss are already using this approach. As a result, there is improved user experience and increased conversions.


The Problem of Processing, Classifying and Storing Data

All modern business is built on data that users make available intentionally or unintentionally. Machine learning technology allows you to take all this complex and immense data and describe it using a relatively simple model available for implementation in modern business systems. Machine learning in the enterprise allows you to analyze, group and classify this data while reducing the risk of errors to minimum. In this regard, the possibilities of machine learning are endless. Every company that decides to integrate these innovations will be able to organize work with the data in accordance with its business objectives.


But the most important advantage is that these systems continue to learn by the method of deep learning. That is, laying the right mechanism once, you can use it a million times without the cost of additional resources.


As far as the AI technology largely invades different areas of business, it will reduce the workload on human employees, make the produced goods more affordable and improve the overall customer experience. Nowadays automation of the workplace is a nice way to help employees become more productive in their work.


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