An Overview of Virtual Assistants and Business Intelligence Chatbots
编号:166 访问权限:仅限参会人 更新:2025-12-23 13:29:28 浏览:4次 拓展类型2

报告开始:暂无开始时间(Asia/Amman)

报告时间:暂无持续时间

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摘要
In recent years, significant advances in artificial intelligence have led to a wide-ranging transformation of organizational decision-making processes and analytical systems. Virtual assistants and AI-based chatbots have emerged as one of the most important innovations in the field of business intelligence. By integrating natural language processing, machine learning, and deep learning capabilities, these technologies enable intelligent human-machine interaction, real-time data analysis, and the generation of accurate analytical insights. Findings show that the use of business intelligence chatbots can increase the operational efficiency of organizations by up to 50 percent and improve the predictive accuracy of data analysis by 35 to 50 percent; these systems facilitate access to complex data by creating a conversational and user-friendly environment and reduce the need for expert analysts. In addition, they improve managerial and strategic decision-making by increasing the speed of analysis. Despite these advantages, important challenges such as data privacy, bias in training data, limited transparency of deep learning models, and the phenomenon of AI illusions remain.
 
关键词
Virtual assistants,artificial intelligence,business intelligence,natural language processing,machine learning,data analytics
报告人
Hossein Hamidizadeh
Undergraduate studen Department of Computer, Ya. C., Islamic Azad University, Yazd, Iran

稿件作者
Hossein Hamidizadeh Department of Computer, Ya. C., Islamic Azad University, Yazd, Iran
Mohamed Hafez INTI-IU-University;Shinawatra University
Mohammad Amini Department of Computer, Ya. C., Islamic Azad University, Yazd, Iran
Yousef Sharrab Isra University
Hani Attar Zarqa University
Reza Namdari khalilabad Department of Mechanical Engineering Ya. C., Islamic Azad University, Yazd, Iran
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重要日期
  • 会议日期

    12月29日

    2025

    12月31日

    2025

  • 12月30日 2025

    报告提交截止日期

  • 12月30日 2025

    注册截止日期

  • 12月31日 2025

    初稿截稿日期

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