Artificial intelligence ( AI ) is a top priority in the industry's executive ranks, and for good reason : AI could contribute $ 15.7 trillion to the global economy by 2030. More and more online casinos are using AI data to offer a single - user gaming experience. Macau's brick - and - mortar casinos have been using artificial intelligence to identify who is losing the most money, while our own Grande Vegas Online Casino is encouraging players to play responsibly with their budgets. Other industries are catching up. Data is an advantage in alternative forms of entertainment, and there are plenty of opportunities to use data and use it to increase revenue. There are a number of ways in which data can be used in the gaming industry, both in terms of data mining and data analytics. Casinos need to maximize one thing in order to generate high gaming revenue. We've seen this in the way that Netflix is using data about how users interact with its service. By tracking the shows that its users watch, when users stop, and when they stop and combining that information with the types of shows, Netflix can decide which shows to invest in. They employ a huge team of data scientists that they employ to produce these results. Many large casinos are already using AI to minimize the likelihood of fraud and enable fair gaming trends. A recent report from technology consulting firm Capgemini SE, which surveyed companies, said that more than half of the companies it surveyed tested the use of AI for cybersecurity. AI - powered slot machines, and investing in huge teams of "data scientists" and intelligentlydeveloping AI skills. But casinos should notuse this as an excuse to avoid developing AI solutions. There are plenty of ways to reduce risk and compete with the entertainment options that are already being deployed by AI. We need to focus on areas where there is already a lot of data already being used for business decisions. Casinos have long studied player behavior and can now use advanced algorithms to obtain information about how players move on a given floor, how much win - loss ratio they behave, and what attracts them. AI can help casinos to develop ranking systems based on how long a player has been in the casino and wagering, what they have wagered, have risked money on, their net worth, or are net - worth. In the first iteration, the AI is simply used to determine what offers to send to players. But casinos should be careful not to try to immediately turn this into a big system that predicts in real - time the offers that players can make over time. The advantage of this approach is that most casinos can track the responses to their marketing offers, and can easily assess the performance of the AI and quickly adjust it for their performance. Another advantage to this is the fact that it keeps the approach in the functional language of business. AIs reflexively learn, go along with instructions, and rely on highly complex statistical models and algorithms to follow instructions and use them to do a better job the next time. As a result, we developed a system that proposes a solution that is easy to explain in the language of data science and therefore not understood by the company. Finally, focusing on one particular project avoids the need for a large number of AI systems with a lot of complexity. This solution is impractical and is not only impractical, but also expensive. By enabling existing employees, as is possible in marketing, access to the data necessary to develop an AI system, the AI project can be aligned with increasing actual business value. Firstly, it will enable the AI project to be completed in a timely manner. All too often, AI projects have vague results that are unclear for our purposes. Secondly, the project behaves as a result of artificial intelligence, which turns into entrepreneurial decisions. Casinos that are able to successfully implement AI and machine learning as part of their business plan will have a competitive advantage in finding and leveraging new growth areas. In order to boost business, casinos need to start thinking about how they will integrate AI into their entire decision making process.