Automated system!

According to Joe Pepparda, and John Ward (2004). The evolution of IT in organizations to date can be captured in three ‘eras’: data processing (DP), management information systems (MIS), and strategic information systems (SIS). Many investments are made in IT not for any competitive advantages but for efficiency and effectiveness reasons. IT alone is unlikely to be a source of sustainable competitive advantage. The business value derived from IT investments only emerges through business changes and innovations.

For decades, computer programs were coded manually to give a specific outcome from a certain input. By utilizing AI technique, computers may examine the complete data to identify significant patterns for making useful predictions (Aman Chandra Kaushik, and Utkarsh Raj, 2020).

The AI technologies have accelerated advancements in robotics and automation, which have significant implications on almost every aspect of businesses, and especially supply chain operations. Supply chains have widely adopted smart technologies that enable real-time automated data collection, analysis, and prediction (Ali K. Dogru, and Burcu B. Keskin, 2020).

Although AI can not really achieve intelligence, and can not fully replace human beings, its ability to receive and process information is far beyond people’s ability. Although establishing an AI management system requires manpower, material resources and time, utilization of an AI management system will improve the product quality and production efficiency, and thereby will improve the economic efficiency of furniture enterprises (Guang Jin Long et al., 2020).

Emerging artificial intelligence (AI) capabilities will likely pervade nearly all organizational contours and activities, including knowledge management. AI in supporting fundamental dimensions of KM: creation, storage and retrieval, sharing, and application of knowledge (Mohammad Hossein Jarrahi et al., 2013).

Machine intelligence is, in its essence, a prediction technology (Ajay Agrawal, et al., 2016).

REFERENCES

. Ajay Agrawal, Joshua Gans, and Avi Goldfarb (2016). The Simple Economics of Machine Intelligence. Harvard business review.

. Ali K. Dogru, and Burcu B. Keskin (2020) AI in operations management: applications, challenges and opportunities. Journal of Data, Information and Management.

. Aman Chandra Kaushik, and Utkarsh Raj (2020). AI-driven drug discovery: A boon against COVID-19?. Ai Open. 1.

. Guang Jin Long, Bai Hua Lin, Hong Xing Cai, Guang Zai Nong (2020). Developing an Artificial Intelligence (AI) Management System to Improve Product Quality and Production Efficiency in Furniture Manufacture. 3rd International Conference on Mechatronics and Intelligent Robotics (ICMIR-2019).

. Joe Pepparda, and John Ward (2004). Beyond strategic information systems: towards an IS capability. Journal of Strategic Information Systems, 13.

. Mohammad Hossein Jarrahi, David Askay, Ali Eshraghi, Preston Smith (2013). Artificial intelligence and knowledge management: A partnership between human and AI. Business Horizons (66), 87 – 99.