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Application of AI in Business

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Jose Kim is the founder of Gorilla Overview. Jose has been running Gorilla Overview and learning self-development, personal finance, and investment for the last 3 years. Jose has been creating celebrity net worth websites for the past 5 years. Currently, he is focusing on building Gorilla Overview. Jose and his team were previously working on the popular entertainment website known as "Bio Overview" which became one of the fastest-growing websites in the world. Jose doesn't use personal social media anymore, so you won't be able to find him on Instagram, or Twitter.

The use of artificial intelligence in business is slowly becoming the norm and a necessity in the competitive struggle. Today, it is a powerful tool for developing companies, solving business problems, performing deep analytics, and automating processes.

This article details how application of artificial intelligence in business helps its development and how smart technologies can be introduced into business practice.

What is artificial intelligence?

In plain English, it is the capacity of computer systems to self-learn and carry out highly specialized tasks that were previously only possible for humans. AI reproduces the intellectual behavior of humans, but it never gets tired, does not experience emotions, and does not make mistakes.

AI in business helps automate routines, process massive amounts of data, predict decisions, make reports, and form conclusions. Whereas in the past all this was done by humans, today machines are much better at this work.

Key Artificial Intelligence Technologies in Business

Machine Learning

It is an AI technique to improve the outcome of systems by learning from large databases. The key difference between machine learning and standard algorithms is adaptability and constant development. The more data and information an algorithm collects, the more accurate its analytics will be.

Examples of using machine learning in business:

  • Chatbots that advise users. Machine learning helps develop a chatbot’s knowledge base, and after 6-12 months, a virtual consultant can answer almost all questions.
  • Personalization and improving customer experience. Machine learning improves customer engagement and satisfaction. For example, offering personalized product selections based on recent purchases.
  • Checking resumes and documentation. Machine learning makes it possible to create a profile of an ideal candidate, simplify the hiring process, and speed up the analysis of resumes. As a result, the amount of routine for HR specialists is reduced.

Neural networks

The most frequent representatives of artificial intelligence in business. It is essentially a program code that processes data and imitates the work of the human brain. Neural networks have found wide application in design, marketing, copywriting, customer service, statistics, calculations, industry, and banking. They are great at writing SEO texts, translating articles, and generating all sorts of media. And at the same time, they do everything cheaper and faster.

What can the simplest and most inexpensive neural network do?

  • Writes texts based on specified keywords;
  • Creates product descriptions, titles, and meta tags;
  • Makes excerpts from texts;
  • Generates images from text descriptions;
  • Creates scripts for YouTube.

NLP (natural language processing)

A machine learning technology that gives computers the ability to understand human language. Modern companies have huge amounts of voice and text data – email correspondence, messages, social media news, video, audio, etc. NLP technology is used to process all of this and use it to the advantage of the business.

For example, NLP can recognize three basic types of emotions – positive, negative and neutral – with 95% accuracy. If predictions are to be believed, by 2025, half of online advertising will be based on this technology. Disney already determines whether viewers like content using a streaming platform. And Ping An claims to have cut financial losses on loans by 60% thanks to new algorithms.


By combining robotics and AI, businesses get robotic hotel administrators, goods pickers, and unmanned car drivers. Robots with intelligence monitor their own accuracy and performance, train, and improve themselves.

Examples of the use of robotics in business:

  • Medical robots. The most famous is the Da Vinci robotic surgeon, which is used to perform tens of thousands of complex heart and brain surgeries around the world every day.
  • Software robots, or robotization. This is software code that mimics the user’s work. In companies that use CRM, “robots” send emails, create documents according to a template, and schedule calls and meetings every day.
  • Unmanned cars. One of the brightest and most popular technologies in robotics. On the roads, robo-cars are showing impressive promise. In the future, most cars will be driven by autopilots, which will greatly improve road safety.

Implementing artificial intelligence in business practice

To briefly describe the process of implementing AI into business practice, the steps are as follows:

  1. Assessing needs and capabilities. Find out what artificial intelligence can do, and then identify problems that can be solved with it.
  2. Select the right technologies and tools. AI systems must meet business needs and objectives. Evaluate the potential financial value of implementing each individual AI technology and select the most promising and profitable one for your niche.
  3. Testing and implementation. The time to test AI depends on the complexity of the tool itself and the industry. The timeframe can range from 2-3 weeks to several months. During the testing period, monitor customer satisfaction and employee performance.

If sales and productivity are increasing, order processing time is decreasing, and feedback is improving, it means that the right AI services have been selected and implemented.

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