Role of Artificial Intelligence and Business Decision Making

Prasanth, Anupama; Vadakkan, Densy John; Surendran, Priyanka; Thomas, Bindhya

doi:10.14569/ijacsa.2023.01406103

Cited by 7 publications

(4 citation statements)

References 26 publications

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“…The results show that there was an association between all the artificial intelligence components and decision making. This finding is consistent with the previous studies, which claims that artificial intelligence lead to decision making (Prasanth, et al, 2023;Ferreira & Monteiro, 2021;Jarrahi, 2018).…”

Section: Discussion Limitation and Direction For Future Researchsupporting

confidence: 94%

Navigating the Future: Artificial Intelligence's Growing Influence on Decision Making

Alzyoud

2023

ijmst

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Purpose: The purpose of this study article is to investigate the impact of AI (system capability, user behavior, training and development, and expert availability) on decision making in Bahrain telecommunications company. Theoretical framework: The deployment of AI systems has expanded tremendously in recent years, and decision making is no exception to its disruptive potential (Jones et al., 2022). AI algorithms and technologies are being used by organizations and individuals to assist and improve decision-making processes. To fully reap the benefits of AI, however, a thorough knowledge of the intricate interplay between AI and decision making is required. Design/methodology/approach: In this study, a quantitative research design is utilized since it permits statistical tools to be used to assess the association between variables. This quantitative study's research approach will be cross-sectional, with the goal of examining the role of artificial intelligence (AI) in decision making. Data were collected by questionnaire from a sample of 195 employees from a Bahraini telecommunications company. Findings: The results show that there was an association between all the artificial intelligence components and decision making. This finding is consistent with the previous studies, which claims that artificial intelligence lead to decision making (Prasanth, et al., 2023; Ferreira & Monteiro, 2021; Jarrahi, 2018). Research, Practical & Social implications: The AI has .the potential to totally revolutionize the way organizations make decisions. However, in order to preserve customer confidence and prevent unforeseen repercussions, enterprises must use AI responsibly and transparently. The use of AI for decision-making, both for businesses and consumers, is undeniably the way of the future. Originality/value: The value of the study understanding the impact of AI on decision making is becoming increasingly crucial as the technology advances. AI system integration can improve decision-making abilities, increase efficiency, reduce risks, offer access to expert information, and raise ethical concerns and obstacles in organizations.

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Section: Discussion Limitation and Direction For Future Researchsupporting

confidence: 94%

Navigating the Future: Artificial Intelligence's Growing Influence on Decision Making

Alzyoud

2023

ijmst

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“…Artificial intelligence allows for precise decision-making that offers significant time and cost savings through data collection, forecasting, and trend analysis [65]. For the last two decades, AI has greatly improved the performance of the manufacturing and service industries [66].…”

Section: ) Artificial Intelligence (Ai)mentioning

confidence: 99%

“…For the last two decades, AI has greatly improved the performance of the manufacturing and service industries [66]. AI can also be used for a wide range of tasks, such as identifying data trends to reduce market risks, improving customer service with the help of virtual assistants, and analysing large document repositories spread across numerous servers within an organization to find instances of compliance violations [65].…”

Section: ) Artificial Intelligence (Ai)mentioning

confidence: 99%

A Lean Service Conceptual Model for Digital Transformation in the Competitive Service Industry

Amin,

Wahab,

Elias

et al. 2024

IJACSA

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In today's competitive service industry, the pressure to boost productivity, cut costs, and improve service quality is immense. By integrating lean principles and digital transformation, organizations can streamline processes and reduce waste. Although various lean models have been developed for different service industry, there is no universal standard. Hence, this study aims to address this gap by proposing a Lean Service Conceptual Model through qualitative research by identifying nine types of waste and seven lean dimensions. Interviews, observations, and audio-visual materials are the data collection methods used in this study. The model aligns seamlessly with modern digital technologies such as big data, the Internet of Things, blockchain, cloud computing, and artificial intelligence, making it adaptable for service organizations to excel in the digital age. The model focuses on enhancing efficiency and effectiveness while primarily reducing waste in service operations. Due to restrictions during the pandemic and the interest expressed by the informants in participating in this study, the focus is thus made on a single case study, which may lead to biased findings. However, future studies will be performed on multiple case studies to enhance the findings. Exploring and reviewing an array of best practices, techniques, and tools available for waste reduction within organizational operations is paramount.

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“…The objective of this article is to delve into the synergy between artificial intelligence (AI) and education systems in the energy context, elucidating the transformative potential of AI in reshaping how we generate, distribute, and utilize energy resources [19]. Through the analysis of extensive datasets, AI algorithms facilitate the optimization of energy systems and enable intelligent decisionmaking processes [20]. This paper aims to showcase diverse ideas and applications where AI technologies can be harnessed to tackle energy-related challenges, paving the way for enhanced energy efficiency, waste reduction, and the promotion of sustainable practices [21].…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence Integrated Energy Education Framework. A Holistic Approach

Stecyk,

Miciuła

2024

Preprint

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This scientific article outlines the Artificial Intelligence Integrated Energy Education Framework (AI-IEEF), a transformative model designed to revolutionize energy education and management practices. The framework is organized into five distinct layers: Organizational (AI-enhanced administration systems), Financial (dynamic AI financial models), Technology (advanced simulation and modeling), Methodology (AI in curriculum development and personalized learning), and Social (AI for community engagement and impact). An expert panel used the fuzzy Delphi method to achieve consensus on twenty key factors within these layers, establishing a solid foundation for analysis. Following this, the Fuzzy Analytic Hierarchy Process (AHP) was employed to calculate precise weights for each layer and their respective factors, providing a quantitative assessment of their relative importance. These weight calculations are crucial, as they guide resource allocation and strategic decision-making to ensure the framework is optimized for the evolving needs of energy management. Furthermore, the article introduces five tailored variants of the AI-IEEF, each addressing specific aspects of energy education and offering a comprehensive approach to navigating the challenges in the field. The five variants include the Smart Campus Energy Education, Global Energy Policy Analysis, Renewable Energy Research and Development, Energy Workforce Development, and Community Engagement and Outreach variants. Each provides a distinct approach to energy education, from transforming campuses into living labs for hands-on learning to fostering international collaborations that explore the global implications of energy policy. These variants emphasize practical skills, policy analysis, and community-focused solutions, ensuring that students are well-prepared to contribute effectively to the energy sector.

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Role of Artificial Intelligence and Business Decision Making

Cited by 7 publications

References 26 publications

Navigating the Future: Artificial Intelligence's Growing Influence on Decision Making

Navigating the Future: Artificial Intelligence's Growing Influence on Decision Making

A Lean Service Conceptual Model for Digital Transformation in the Competitive Service Industry

Artificial Intelligence Integrated Energy Education Framework. A Holistic Approach

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