Of late, while we are working on solutions around AI and helping enterprises with their AI initiatives, a common misconception caught my attention. Many people think that AI is just BI in a new packaging of GPT. Same chocolate in a new wrapper!
Let us clearly differentiate between the two concepts. Both AI and BI deal with data and decision making, but their approaches and outcomes are different. They are clearly NOT interchangeable.
Myth 1 : AI and BI are the same
Artificial intelligence as the name suggests tries to mimic human intelligence. AI refers to the science and technique of making computers understand and analyze data the way humans do. It emulates cognitive human functions of understanding, learning, judgment, predictions, solving problems, making choices, etc.
Business Intelligence on the other hand is more like a software to look into business data and analyze the same to give insights into the reality for effective decision making. Thus, while AI creates intelligent machines that can (if they are allowed to) take decisions and act, BI focuses on empowering human intelligence for decision making.
Myth 2 : AI is super intelligent and sentient, BI is dumb numbers and charts
AI is absolutely not sentient. At least, as of now. It is simply based on very complex algorithms that will always do things that it is asked to do in a way that it is programmed to do. AI does not have real general intelligence. To be fair, humans are still to completely understand raw intelligence and emotions and the exact connection between the two.
BI is more than numbers and charts. Those are just the outcomes. But essentially BI is also based on complex data models and programs that try to answer specific questions based on available data. It includes data visualization, predictive analytics, etc.
Myth 3 : Eventually AI will replace BI
BI doesn't really prescribe specific actions but only informs businesses about historical and current events. While there is a predictive side to BI, it is essentially based on historical evidence rather than futuristic reasoning.
However, BI does provide an underlying foundation for AI techniques to enhance the comprehension of the outcome of BI, predict the future and also suggest actions based on future possibilities. BI helps prepare data which AI can understand further to reveal deeper patterns and future trends.
Conclusion
While AI and BI are not the same, they do have certain common ground. While they are significantly different concepts, they are not mutually exclusive. AI encompasses a broad spectrum of technologies, including machine learning, natural language processing, computer vision, and robotics. BI, on the other hand, means analysis of business data to provide actionable insights for decision-making. BI tools collect, transform, and visualize data from diverse sources, such as databases, spreadsheets, and enterprise applications.
BI tools may lay the foundation for AI and AI will enhance the output of BI tools, making them more intuitive and actionable. We can expect to see more AI capabilities embedded within BI tools. However neither will replace the other. They will rather co-exist and together lead the digital transformation of businesses.
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