Human-AI symbiosis: The best approach for AI implementation in business decision-making in complex systems

In today's business landscape, there is significant discourse surrounding the role of Artificial Intelligence (AI) in various aspects of business operations. Decision-making, in particular, is a crucial component of every business-related activity. As businesses expanded and generated massive amounts of data, it became clear that humans alone could no longer make consistently accurate decisions. Moreover, it is demonstrated that humans often rely on heuristics and cognitive biases in their decision-making, leading to suboptimal outcomes. Given today's business environment's complexity, instability, and interconnected nature, businesses possess all the characteristics of complex systems. With the aid of AI, decision-making can be significantly enhanced. Various subfields of AI, such as artificial neural networks, fuzzy logic networks, and agents, have been developed in recent years, playing a pivotal role in enabling AI-driven decision-making. Findings through using purposeful and complex systems suggest that although AI subfields in decision-making can make sound decisions, they exhibit deficiencies in complex systems where human interaction and interconnectedness across different organizational levels are present. Currently, AI technology is not equipped to address these challenges. As a result, the decision-making process should not be entirely delegated to machines and AI. This discussion gives rise to the duality of augmentation and automation. Decision-making can be categorized into three levels: operational, tactical, and strategic, ranging from structured to unstructured decisions. The analysis reveals that AI performs admirably as an assistant or replacement tool at the operational level. However, as moving towards tactical and strategic decisions, although its augmentation abilities remain somewhat consistent, its capabilities for replacement and automation diminish significantly. Consequently, AI is believed to lack the ability to automate strategic and unstructured business decisions completely

Use and effectiveness of decision support systems (DSS): Study of the Saudi private sector

In the industrialized world today, management is characterized by extensive use of computers to manage rapid change, information overload, and complex decision-making. Literature suggests that Decision Support Systems, computer packages offering information retrieval, problem-structuring models, decision alternatives, and other types of decision support, are effective extensions of human decision-making and offer substantial benefits to organizations utilizing them. In spite of overwhelmingly positive reviews for DSS, empirical literature has produced inconsistent results regarding DSS effectiveness, and definitions of “effectiveness” and of DSS itself are varied and sometimes contradictory. Distinguishing DSS from MIS (management information systems) and other types of managerial computer support has proven to be an essential part of DSS research. An additional gap in DSS research to date is that little is known about DSS use in developing countries and the potential of DSS to improve decision-making and overall organizational effectiveness. The present empirical study surveyed one member from each of Saudi Arabia\u27s largest corporations to determine to what extent DSS has been incorporated into the companies\u27 decision-making procedures. A second purpose was to determine decision-makers\u27 perceptions of the effectiveness of DSS in terms of their decision processes (time savings, availability of more alternatives, cognitive effort) as well as decision outcomes (decision accuracy and overall quality). The research revealed a high degree of use and enthusiasm for DSS, but revealed gaps in Saudi utilization of the systems. The research identified specific obstacles to more pervasive adaptation and enjoyment of benefits, including a lack of research stemming from researchers\u27 misperceptions of the private sector\u27s interest in and ability to understand Decision Support Systems

Constructing and Testing Practical Procedures for Describing a Corporate Culture: The Electric Troublemen

During the 1980s much attention was focused on trying to understand and apply the concept of corporate culture. Scholars and practitioners worked on clarifying the definition of culture as it applies to workplace settings. Scholars adapted the anthropological concepts of culture to fit within the framework of a business organization. Both scholars and practitioners attempted to investigate the cultures of many organizations throughout the business world. Scholars conducted lengthy case studies and used a mixture of qualitative and quantitative techniques. Business world practitioners conducted short studies and used mostly quantitative survey techniques. What was found was that the scholarly approach took too long to perform and the business world practitioner\u27s approach produced very little information about an organization\u27s workplace culture. This research project attempted to apply qualitative research techniques in a way that recognizes the practical limits placed on time, talent, and materials in the business world. More specifically, a model of workplace culture and a procedure for describing and profiling a corporate culture were developed and tested. The model consists of three components: one that helps to identify whether or not an organization has a healthy culture, one that describes the characteristics that make up the content of a culture, and one that classifies a culture according to categories that are useful for comparing one culture to another. The procedure consists of three qualitative data gathering techniques: observation, interview, and historical document analysis; and the analysis procedure involves processing thick description data. The model and the procedure were tested by describing and profiling the subculture of a small group of employees, known as electric troublemen, who work for the San Diego Gas and Electric Company. Data collection and analysis took approximately 360 hours to complete, resulting in a profile that is both interesting and informative

Organizational change and development : annotated and supplemental bibliography / 191

Includes bibliographical references (p. 48-80)

Decision processes in organizations

In this chapter, it is demonstrated that the concepts of leadership and organization are closely linked. A leader should initially get to know the organizational culture as well as possible. Such a culture can for example be authoritarian and conformist or innovative and progressive in nature. The assumption is that leaders are influenced by their own culture. Strategic decisions are characterized by the fact that they are new, complex and open in nature, and being able to develop a strategy is one of the most difficult tasks for a leader. Traditionally, it is primarily the top leadership in an organization that works with strategic decisions, and thus it is common that strategic issues are handled by top leadership teams. This is related to the globalization of business and to the fact that the pace of work has increased significantly. In order to exercise leadership, a leader must have access to power. A power base can be created through networking as well as by using different political tactics. However, it is important to use political tactics in order to promote the organization's interests. When a leader has built up a power base, it is essential that power is used properly. The decisions that leaders make must be ethically correct and not violate universal human values. For instance, they should not lead to negative consequences for others within or outside the organization. Evidence suggests that most leaders have the potential to develop as ethical decision makers

Trust and Distrust in Big Data Recommendation Agents

Big data technology allows for managing data from a variety of sources, in large amounts, and at a higher velocity than before, impacting several traditional systems, including recommendation agents. Along with these improvements, there are concerns about trust and distrust in RA recommendations. Much prior work on trust has been done in IS, but only a few have examined trust and distrust in the context of big data and analytics. In this vein, the purpose of this study is to study the eight antecedents of trust and distrust in recommendation agents’ cues in the context of the Big Data ecosystem using an experiment. Our study contributes to the literature by integrating big data and recommendation agent IT artifacts, expanding trust and distrust theory in the context of a big data ecosystem, and incorporating the constructs of algorithm innovativeness and process transparency

Organizational memory: the role of business intelligence to leverage the application of collective knowledge

Nowadays, the major challenge to organizations managers is that they must make appropriate decisions in a turbulent environment while it is hard to recognize whether information is good or bad, because actions resulting from wrong decisions may place the organization at risk of survive. That is why organizations managers try to avoid making wrong decisions. In order to improve this, managers should use collective knowledge and experiences shared through Organizational Memory (OM) effectively to reduce the rate of unsuccessful decision making. In this sense, Business Intelligence (BI) tools allow managers to improve the effectiveness of decision making and problem solving. In the light of these motivations, the aim of this chapter is to comprehend the role of BI systems in supporting OM effectively in real context of crowdsourcing academic initiative called CrowdUM.This work is financed by Fundos FEDER through the Programa Operacional Fatores de Competitividade - COMPETE and Fundos Nacionais through FCT – Fundação para a Ciência e Tecnologia under the Project: FCOMP-01-0124-FEDER-02267

Strengthening Organizational Performance through Integration of Systems Leadership, Participatory Communication, and Dynamic Capabilities

This dissertation seeks to include systems leadership and participatory communication as facilitators of the elements that enhance dynamic organizational capabilities to improve performance. The study employs the normative theory-building process to show how systems leadership and participatory communication can facilitate and enhance dynamic capabilities. Specifically, this dissertation offers an integrative model that combines systems leadership, participatory communication, and dynamic capabilities. The proposed integrative model is accompanied by a series of propositions that extend the dynamic capabilities theory through the integration of systems leadership and participatory communication. The potential relevance and application of the proposed model are demonstrated through multiple case examples. The study may also guide nonprofit and for-profit organizations on improving performance through leadership skills, effective communication, and enhanced dynamic capabilities. This dissertation is available in open access at AURA (https://aura.antioch.edu/) and OhioLINK ETD Center