AI vs. Data Science: Differences in Technology and Use Cases

AI and data science are two very popular buzz words in IT, and for good reason. They’re two sets of technologies that often work hand in hand to boost business insights and productivity. But they have their differences in use cases. Data science is a field of study that examines large data sets with various analytics methods -- including machine learning and pattern discovery -- to extract valuable business insights, while AI refers to a computer’s ability to understand, learn from, and make decisions based on data like humans.

What processes does your business use data science or AI for? Let us know in the comments, and be sure to hit that like button, too.

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[WorldPeace-piuq]

Nice attempt to explain Data Science vs. AI, but to say that DS is restricted to statistical analysis of past data is not correct. Data Science is a broad field that includes AI and other methods of finding answers and predicting likely next steps. There is a whole area of predictive DS - for example regression analysis, we don't consider AI. I think it's not helpful to try to put hard boxes around DS and AI, but rather look at the history of the scientific domain and not separate them so strictly. Data Scientists use AI and whatever works to find answers, solve problems etc. And that toolbox is growing at a fast pace.
I find people confusing AI and ML more than with DS. You got it ML correct !