Applied Statistics in the Era of Artificial Intelligence: A Review and Vision

IF 1.5 4区数学 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

Applied Stochastic Models in Business and Industry Pub Date : 2026-02-18 DOI:10.1002/asmb.70075

Jie Min, Xinyi Song, Simin Zheng, Caleb B. King, Xinwei Deng, Yili Hong

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引用次数: 0

Abstract

The advent of artificial intelligence (AI) technologies has significantly changed many domains, including applied statistics. This review and vision paper explores the evolving role of applied statistics in the AI era, drawing from our experiences in engineering statistics. We begin by outlining the fundamental concepts and historical developments in applied statistics and tracing the rise of AI technologies. Subsequently, we review traditional areas of applied statistics, using examples from engineering statistics to illustrate key points. We then explore emerging areas in applied statistics, driven by recent technological advancements, highlighting examples from our recent projects. The paper discusses the symbiotic relationship between AI and applied statistics, focusing on how statistical principles can be employed to study the properties of AI models and enhance AI systems. We also examine how AI can advance applied statistics in terms of modeling and analysis. In conclusion, we reflect on the future role of statisticians. Our paper aims to shed light on the transformative impact of AI on applied statistics and inspire further exploration in this dynamic field.

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人工智能时代的应用统计学：回顾与展望

人工智能（AI）技术的出现极大地改变了许多领域，包括应用统计学。这篇综述和愿景论文从我们在工程统计方面的经验出发，探讨了应用统计在人工智能时代不断发展的作用。我们首先概述应用统计学的基本概念和历史发展，并追溯人工智能技术的兴起。随后，我们回顾了应用统计的传统领域，用工程统计的例子来说明要点。然后，我们探索应用统计学的新兴领域，在最近的技术进步的推动下，突出了我们最近项目的例子。本文讨论了人工智能与应用统计学之间的共生关系，重点讨论了如何利用统计原理来研究人工智能模型的特性并增强人工智能系统。我们还研究了人工智能如何在建模和分析方面推进应用统计。最后，我们对统计学家的未来角色进行了反思。我们的论文旨在揭示人工智能对应用统计学的变革性影响，并激发这一动态领域的进一步探索。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Applied Stochastic Models in Business and Industry 数学-数学跨学科应用

CiteScore

2.70

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： ASMBI - Applied Stochastic Models in Business and Industry (formerly Applied Stochastic Models and Data Analysis) was first published in 1985, publishing contributions in the interface between stochastic modelling, data analysis and their applications in business, finance, insurance, management and production. In 2007 ASMBI became the official journal of the International Society for Business and Industrial Statistics (www.isbis.org). The main objective is to publish papers, both technical and practical, presenting new results which solve real-life problems or have great potential in doing so. Mathematical rigour, innovative stochastic modelling and sound applications are the key ingredients of papers to be published, after a very selective review process. The journal is very open to new ideas, like Data Science and Big Data stemming from problems in business and industry or uncertainty quantification in engineering, as well as more traditional ones, like reliability, quality control, design of experiments, managerial processes, supply chains and inventories, insurance, econometrics, financial modelling (provided the papers are related to real problems). The journal is interested also in papers addressing the effects of business and industrial decisions on the environment, healthcare, social life. State-of-the art computational methods are very welcome as well, when combined with sound applications and innovative models.