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Decision support systems [DSS] are becoming increasingly more critical to the daily operation of organizations. Data warehousing, an integral part of this, provides an infrastructure that enables businesses to extract, cleanse, and store vast amounts of data. The basic purpose of a data warehouse is to empower the knowledge workers with information that allows them to make decisions based on a solid foundation of fact. However, only a fraction of the needed information exists on computers; the vast majority of a firm's intellectual assets exist as knowledge in the minds of its employees. What is needed is a new generation of knowledge-enabled systems that provides the infrastructure needed to capture, cleanse, store, organize, leverage, and disseminate not only data and information but also the knowledge of the firm. The purpose of this paper is to propose, as an extension to the data warehouse model, a knowledge warehouse [KW] architecture that will not only facilitate the cap...
With the recent boom in big data and the continuous need for innovation, Artificial Intelligence is carving out a bigger place in our society. Through its computer-based capabilities, it brings new possibilities to tackle many issues within organizations. It also raises new challenges about its use and limits. This thesis aims to provide a better understanding of the role of humans and Artificial Intelligence in the organizational decision making process. The research focuses on knowledge-intensive firms. The main research question that guides our study is the following one: How can Artificial Intelligence re-design and develop the process of organizational decision making within knowledge-intensive firms? We formulated three more detailed questions to guide us: [1] What are the roles of humans and Artificial Intelligence in the decision making process? [2] How can organizational design support the decision making process through the use of Artificial Intelligence? [3] How can Artificial Intelligence help to overcome the challenges experienced by decision makers within knowledge-intensive firms and what are the new challenges that arise from the use of Artificial Intelligence in the decision making process? We adopted an interpretivist paradigm together with a qualitative study, as presented in section 3. We investigated our research topic within two big IT firms and two real estate startups that are using AI. We conducted six semi-structured interviews to enable us to gain better knowledge and in-depth understanding about the roles of humans and Artificial Intelligence in the decision making process within knowledge-intensive firms. Our review led us to the theoretical framework explained in section 2, on which we based our interviews. The results and findings that emerged from the interviews follow the same structure than the theoretical review and provide insightful information in order to answer the research question. To analyze and discuss our empirical findings that are summarized in the chapter 5 and in a chart in the appendix 4, we used the general analytical procedure for qualitative studies. The structure of chapter 5 follows the same order than the three sub questions. The thesis highlights how a deep understanding of Artificial Intelligence and its integration in the process of organizational decision making of knowledge-intensive firms enable humans to be augmented and to make smarter decisions. It appears that Artificial Intelligence is used as a decision making support rather than an autonomous decision maker, and that organizations adopt smoother and more collaborative designs in order to make the best of it within their decision making process. Artificial Intelligence is an efficient tool to deal with complex situations, whereas human capabilities seem to be more relevant in situations of uncertainty and ambiguity. Artificial Intelligence also raises new issues for organizations regarding its responsibility and acceptation by society as there is a grey area surrounding machines in front of ethics and laws. Keywords: Artificial Intelligence, Augmented humans, Decision maker, Decision making, Decision making process, Ethics, Knowledge, Knowledge-intensive firms, Organizational design, Organizational challenge, Smart decisions.
In this chapter we review the knowledge-based view on decision support and argue the emergence of a new type of intelligent decision support system — an intelligent gateway for supporting specific knowledge needs. The modern view on decision support and expert systems has shifted from considering these as purely analytical tools for assessing best-decision options to seeing them as a more comprehensive environment for supporting efficient information processing based on a good understanding of the problem context. Such intelligent decision support systems incorporate problem-domain knowledge to improve their information processing and provision capabilities. More recently, information portals have been proposed as tools for matching users’ information needs in order to enhance their decision-making ability. This chapter looks at portals as new types of intelligent decision support systems, which use problem-domain knowledge in order to improve efficiency in information provision. The main focus of the chapter is on suggesting mechanisms for implementing intelligent decision support capabilities in a healthcare portal, which seeks to deliver personalized information to support efficient decision making. BCKOnline, a healthcare portal built around breast cancer information, is described as an example of such implementation.
Artificial Intelligence [AI] is the revolutionary invention of human intelligence. Artificial Intelligence is nothing but the duplication of human in which machines are programmed to rationally think and behave like humans developed for very many purposes including business decision making, problem-solving, business data analysis and interpretation and information management. The application of AI in business endeavours decides the competitive advantage, market leadership, robust operating efficiency of corporates and other business houses. Exploiting the application of AI in the manufacturing and distribution process enables the organisations to reach the pinnacle in their business graph. Businesses are operating in the international market which is highly multifaceted and challenging to serve the world as a sole market for their products, services and their products and without the integration of technology into their business processes, they cannot assure the sustainable growth. The management of the process of transforming the raw materials into the final product is called Supply Chain Management [SCM] and the effective movement and storage of goods, services and information are called Logistics Management [LM]. This article analyses the applications of Artificial Intelligence in Supply Chain and Logistics Management [SC&LM]