Special Issue(24-24): Leveraging AI and Smart Technology for Enhanced Business Intelligence in International Journal of Automation and Smart Technology | International Journal of Automation and Smart Technology

Leveraging AI and Smart Technology for Enhanced Business Intelligence

Businesses can now forecast future trends and understand historical performance by integrating AI algorithms with BI platforms, which encourages proactive initiatives. AI-driven data analytics is at the centre of this revolution. A subset of artificial intelligence called machine learning algorithms is capable of processing enormous volumes of data at previously unheard-of rates, revealing previously hidden patterns and connections. During the past few decades, business intelligence has experienced considerable development. In the past, BI systems produced insights through manual study of historical data. But real-time data processing, predictive analytics, and automated decision-making have all been made possible by the emergence of AI and smart technologies.

Predictive analytics models, for example, have the ability to predict consumer behaviour, market trends, and operational inefficiencies. This allows firms to make highly accurate data-driven decisions. This capacity is especially useful in sectors where prompt and accurate insights can have a big influence on results, like banking, healthcare, and retail. Improving customer insights is one of the most interesting uses of AI and smart technologies in business intelligence. Natural language processing (NLP) and sentiment analysis allow organisations to examine client feedback from a variety of sources, such as surveys, social media, and reviews. This makes it possible to comprehend client preferences, problems, and new trends on a deeper level. AI-driven chatbots and virtual assistants, for instance, can offer customised client interactions, enhancing pleasure and loyalty while also collecting important data for business intelligence. Smart technology, which includes edge computing and the Internet of Things (IoT), is essential for streamlining corporate processes. Real-time data is gathered by IoT devices from a variety of sources, including environmental sensors, supply chain operations, and manufacturing equipment. After that, this data is processed closer to the source, at the edge, which lowers latency and speeds up decision-making. For example, AI-powered predictive maintenance in manufacturing can detect possible equipment breakdowns before they happen, limiting downtime and cutting expenses. Another area where AI and smart technology are having a big impact is supply chain management. Supply chain data may be analysed by AI algorithms to improve logistical efficiency, estimate demand, and manage inventory levels.

Real-time visibility into the flow of commodities is made possible by smart sensors and RFID technology, which improves coordination and lowers the possibility of disruptions. Businesses can build supply chains that are more flexible and resilient, able to adjust to shifting market conditions, by utilising artificial intelligence and smart technology. Not only are AI and smart technologies useful for data analysis, but they also significantly facilitate strategic decision-making. Decision-makers may access actionable insights, data visualisations, and intuitive dashboards using advanced BI solutions with AI capabilities. These platforms have the ability to highlight key performance indicators (KPIs), create automated reports, and provide advice based on data analysis. Consequently, managers and executives are able to promptly make well-informed judgments and match their strategies to the demands of the market and the company's objectives. The business intelligence landscape is changing as a result of the integration of AI and smart technologies, which presents hitherto unseen chances for innovation and competitive advantage. We welcome contributions from a variety of fields and viewpoints, such as but not limited to: Leveraging AI and Smart Technology for Enhanced Business Intelligence.

Potential topics include but are not limited to the following:

Utilising Reciprocal Symmetry and AI to Gain Business Intelligence.
Leveraging business intelligence to achieve strategic expansion.
Business intelligence trends and possibilities related to machine learning and artificial intelligence.
Applying Business Intelligence to Promote Innovation in Cyber Security.
Optimising Business Intelligence Systems to Increase Corporate Competitiveness.
Data analysis and business intelligence using artificial intelligence.
A comparison of big data analytics with artificial intelligence and business intelligence.
Artificial intelligence and big data analytics are used to create value based on data.
Applying deep learning to improve organisational management's business intelligence.
Business intelligence and the utilisation of information in healthcare enterprises from a managerial perspective.
Employing artificial intelligence to improve supply chain efficiency.
Increasing corporate intelligence through big data analytics services.