Artificial intelligence in marketing is a method of using customer data and AI concepts, including machine learning, to predict the next step of the consumer and meet his needs, even those that the consumer has not yet formulated. The evolution of Big data and advanced analytical solutions have enabled marketers to create a clearer picture of their target audience than ever before. It is advisable to consider in more detail the tools of artificial intelligence used by large companies for a deep understanding of consumers. Marketers are trying to understand the vast repository of data understand the root cause and likelihood of repeating certain actions, so machine learning platforms are needed to help identify trends or common events and anticipate key ideas and reactions (Ma & Sun, 2020). Machine learning can be used not only to reveal previously hidden ideas but also to teach and implement open ideas in new PR campaigns, optimizing consumer reach, focusing only on relevant users. Big data is a concept of the ability of marketers to aggregate and segment large amounts of data with minimal manual consumption. In the digital economy, there are thousands of data points attached to the target audience that can be accurately analyzed by bots to understand which message someone will like (Wirth, 2018). Marketers can then use this data to deliver the right message to the right person at the right time on the chosen channel. Numerous elements and factors are now influencing the current reality of companies in the market. They’re complicated, highly connected, and can be tough to quantify. One of the issues that managers confront is predicting the precise direction of the business or product in a small amount of time utilizing a complicated system of data sources. Many learning algorithms are meant to identify trends from a large number of inputs and assist marketers in forecasting the desired future. Suggestions are a great illustration of how AI may be used in marketing (Wirth, 2018). E-commerce sites, blogs, social networks, and media sites use artificial intelligence to analyze consumers’ online activities and recommend products and content for better conversion, as well as to spend more time on their sites. Tracking content with AI will help you better connect with visitors to specific sites and show them more relevant content. Coca-Cola is an example of a company that uses AI for business analysis. With 500 brands and a customer base in 200 countries, the company operates a huge amount of data. Experts use AI and big data technology to develop new products (Leadbeater, 2021). Cherry Sprite, for example, was launched based on data from vending machines in which customers mixed drinks to their liking. The more information is invested in the training of the chatbot, the better it performs its duties. Experts advise launching chatbots at certain points in the sales funnel. This will help you sell more and improve your conversion rates. For example, Google Play uses AI to help customers find the app they want and share their music (Wiggers, 2019). AI offers music based on past searches, time of day, and genres that people have listened to before. Hence, due to AI, marketers have the opportunity to interact with consumers at every stage of the buying and selling process, based on personalized information about the geography, demographic status, needs, preferences of consumers. AI will be able to