MODELS AND ALGORITHMS FOR ANALYZING THE IMPACT OF ARTIFICIAL INTELLIGENCE ON DECISION-MAKING PROCESSES IN BUSINESS INFORMATION SYSTEMS

Asqaraliyev Odilbek Ulug’bek o‘g‘li,Fayzullayev Shakhzod Shukhrat o‘g‘li

Authors

Asqaraliyev Odilbek Ulug’bek o‘g‘li,Fayzullayev Shakhzod Shukhrat o‘g‘li Rector of the “Tashkent Perfect University” PhD, associate professor,Assistant at the Department of Convergence of digital technologies at the University of Information Technologies in Tashkent named after Muhammad al-Khwarizmi

Keywords:

Artificial intelligence, business information systems, business decision making, decision-making processes, Big Data analytics, AI integration, AI algorithms, algorithmic optimization, decision efficiency.

Abstract

The rapid advancements in artificial intelligence have significantly transformed decision-making processes within business information systems. The study of models and algorithms for analyzing the impact of artificial intelligence on decision-making processes in business information systems focuses on how AI technologies transform decision-making by automating tasks, improving data analysis and optimizing operational efficiency. Traditional decision-making frameworks often rely on human expertise and historical data, but AI introduces advanced techniques like machine learning, neural networks and natural language processing that enable businesses to process vast amounts of real-time data, recognize patterns and predict future trends with greater precision. As AI technologies continue to advance rapidly, organizations are increasingly integrating AI into their business strategies to gain a competitive advantage. Key models include decision-support systems enhanced by machine learning, predictive analytics, and reinforcement learning algorithms. These tools enable businesses to make faster, more informed decisions by processing vast amounts of data in real-time. AI-powered systems enable businesses to process and analyze vast amounts of data efficiently, reducing human error and bias, leading to quicker and more informed decision making.

The article discusses how AI models optimize decision-making in areas and it also addresses the challenges associated with AI adoption, including data privacy concerns, the need for interpretability of AI models and the ethical considerations of automated decision-making. Through this analysis, the article provides a comprehensive overview of how AI is reshaping decision-making frameworks in business information systems and its implications for future business strategies.

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