article · Procedia Computer Science
Artificial intelligence significantly enhances business intelligence systems by improving data analysis, automating data integration, and supporting decision-making. These intelligent systems process vast datasets to recognise patterns, extract actionable insights, automate data cleansing, and forecast emerging trends using predictive analytics. In addition, artificial intelligence delivers personalised recommendations, detects anomalies, improves data visualisation, and introduces natural language interfaces that simplify access to information. Within this context, conversational agents such as chatbots play a critical role in supporting business intelligence workflows. A structured workflow model outlines how conversational tools can assist these analytical operations, aiming to guide business systems toward higher levels of contextual autonomy, creative capability, and continual performance improvement across enterprise environments.
Modern organisations often struggle to interpret vast volumes of operational data quickly. Integrating artificial intelligence and conversational interfaces into business intelligence tools makes data exploration far more accessible to non-technical users. This enables decision-makers to uncover patterns, forecast upcoming trends, and retrieve timely business insights through straightforward conversational interaction rather than complex, manual querying.
The concepts apply to enterprise software providers and business analysts seeking more accessible reporting tools. Potential applications involve integrating conversational agents into commercial business intelligence suites to streamline data retrieval and reporting. Because the abstract presents an analytical overview and a conceptual flowchart rather than a deployed software tool, the research sits at an early conceptual stage, requiring software development and empirical testing before commercial deployment.
AI-generated from the published abstract. Always read the original work before citing.
Artificial Intelligence (AI) empowers Business Intelligence (BI) by enhancing data analysis, automating data integration, enabling predictive analytics, providing natural language interfaces, detecting anomalies, delivering personalized recommendations, and enhancing data visualization. AI-driven systems process large datasets, identify patterns, and extract valuable insights. They automate data integration, cleansing, and transformation. Predictive analytics forecasts future trends, while natural language interfaces make data access easier. This paper gives an overview of the perspectives of intelligent empowerment of BI by AI. It focuses on presenting the ways AI can complement or even enhance the different processes of BI systems used for driving decision-making. Therefore, contextualizing the use of AI in business empowerment, we analyzed the perspectives of making intelligent empowerment of BI based on AI. We further exhibit a flowchart showing how AI Chatbots can assist BI processes to achieve the highest level of contextual autonomy and creative capability with continual improvement.
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DOI: 10.1016/j.procs.2023.09.068
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