Artificial intelligence (AI) and machine learning (ML) are gaining presence in all aspects of research and data analysis. Strictly speaking, ML is a subfield of AI about the algorithms and statistical tools that allow computer systems to perform specific tasks without explicit instructions. One side effect of this evolution is an expanded interest in data driven studies including topics such as data integration, alternative scenario analysis and predictive analytics. This paper is a retrospective view of experience gained by applying statistics and analytics to a wide range of problems, with an emphasis on the past few years. It aims to show how AI and ML merge with statistics in a powerful modern analytic environment. The paper has three parts. Part I is about AI and statistics practice, Part II is about AI in Medicine and Part III is about AI in survey design and analysis. If needed, references provide more details.
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