Abstract:Purpose
The purpose of this study is to explore the potential and growth of big data across several industries between 2016 and 2020. This study aims to analyze the behavior of interest in big data within the community and to identify areas with the greatest potential for future big data adoption.
Design/methodology/approach
This research uses Google Trends to characterize the community’s interest in big data. Community interest is measured on a scale of 0–100 from weekly observations over the past five year… Show more
“…Gartner defines big data as “high-volume and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision-making and process automation.” To put it simply, big data includes every means and practice/application that help people use and manage huge data sets. The concept of big data is heavily used in capturing trends, preferences and user behavior when people interact with various systems as well as one another (Zarezadeh et al , 2022; Del Vecchio et al , 2020; Mariani et al , 2021; Almeida, 2022; Tian et al , 2021; Simović, 2018; Sedkaoui and Khelfaoui, 2019). Big data can help companies analyze and figure out the motivations of their most important clients, while also providing ideas for the creation of new offerings (Mariani et al , 2018).…”
Purpose
The purpose of this paper is to see how critical and vital artificial intelligence (AI) and big data are in today’s world. Besides this, this paper also seeks to explore qualitative and theoretical perspectives to underscore the importance of AI and big data applications in multi-sectoral scenarios of businesses across the world. Moreover, this paper also aims at working out the scope of ontological communicative perspectives based on AI alongside emphasizing their relevance in business organizations that need to survive and sustain with a view to achieve their strategic goals.
Design/methodology/approach
This paper attempts to explore the qualitative perspectives to build a direction for strategic management via addressing the following research questions concerned with assessing the scope of ontological communicative perspectives in AI relevant to business organizations; exploring benefits of big data combined with AI in modern businesses; and underscoring the importance of AI and big data applications in multi-sectoral scenarios of businesses in today’s world. Employing bibliometric analysis along with NVivo software to do sentiment analysis, this paper attempts to develop an understanding of what happens when AI and big data are combined in businesses.
Findings
AI and big data have tremendous bearing on modern businesses. Because big data comprises enormous information of diverse sorts, AI-assisted machines, tools and devices help modern businesses process it quickly, efficiently and meaningfully. Therefore, business leaders and entrepreneurs need to focus heavily on ontological and communicative perspectives to deal with diverse range of challenges and problems particularly in the context of recent crises caused by COVID-19 pandemic.
Research limitations/implications
There is hardly any arena of human activity wherein AI and big data are not relevant. The implication of this paper is that of combining both well so that we may find answers to the difficult and challenging multi-sectoral scenarios concerning not just businesses but life at large. Moreover, automated tools based on AI such as natural language processing and speech to text also facilitate meaningful communication at various levels not just in business organizations but other fields of human activities as well.
Social implications
This paper has layered social implications, as it conceptually works out as to how strategically we may combine AI and big data to benefit modern business scenarios dealing with service providers, manufacturers, entrepreneurs, business leaders, customers and consumers. All the stakeholders are socio-culturally and contextually rooted/situated, and that is how this study becomes socially relevant.
Originality/value
This paper is an original piece of research and has been envisioned in view of the challenging business scenarios across the world today. This paper underscores the importance of strategically combining AI and big data, as they have enormous bearing on modern businesses. The insights arrived at in this paper have implications for business leaders and entrepreneurs across the globe who could focus more on ontological and communicative perspectives of AI combined with Big Data to deal with diverse range of challenges and problems that modern businesses have been facing particularly in recent times.
“…Gartner defines big data as “high-volume and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision-making and process automation.” To put it simply, big data includes every means and practice/application that help people use and manage huge data sets. The concept of big data is heavily used in capturing trends, preferences and user behavior when people interact with various systems as well as one another (Zarezadeh et al , 2022; Del Vecchio et al , 2020; Mariani et al , 2021; Almeida, 2022; Tian et al , 2021; Simović, 2018; Sedkaoui and Khelfaoui, 2019). Big data can help companies analyze and figure out the motivations of their most important clients, while also providing ideas for the creation of new offerings (Mariani et al , 2018).…”
Purpose
The purpose of this paper is to see how critical and vital artificial intelligence (AI) and big data are in today’s world. Besides this, this paper also seeks to explore qualitative and theoretical perspectives to underscore the importance of AI and big data applications in multi-sectoral scenarios of businesses across the world. Moreover, this paper also aims at working out the scope of ontological communicative perspectives based on AI alongside emphasizing their relevance in business organizations that need to survive and sustain with a view to achieve their strategic goals.
Design/methodology/approach
This paper attempts to explore the qualitative perspectives to build a direction for strategic management via addressing the following research questions concerned with assessing the scope of ontological communicative perspectives in AI relevant to business organizations; exploring benefits of big data combined with AI in modern businesses; and underscoring the importance of AI and big data applications in multi-sectoral scenarios of businesses in today’s world. Employing bibliometric analysis along with NVivo software to do sentiment analysis, this paper attempts to develop an understanding of what happens when AI and big data are combined in businesses.
Findings
AI and big data have tremendous bearing on modern businesses. Because big data comprises enormous information of diverse sorts, AI-assisted machines, tools and devices help modern businesses process it quickly, efficiently and meaningfully. Therefore, business leaders and entrepreneurs need to focus heavily on ontological and communicative perspectives to deal with diverse range of challenges and problems particularly in the context of recent crises caused by COVID-19 pandemic.
Research limitations/implications
There is hardly any arena of human activity wherein AI and big data are not relevant. The implication of this paper is that of combining both well so that we may find answers to the difficult and challenging multi-sectoral scenarios concerning not just businesses but life at large. Moreover, automated tools based on AI such as natural language processing and speech to text also facilitate meaningful communication at various levels not just in business organizations but other fields of human activities as well.
Social implications
This paper has layered social implications, as it conceptually works out as to how strategically we may combine AI and big data to benefit modern business scenarios dealing with service providers, manufacturers, entrepreneurs, business leaders, customers and consumers. All the stakeholders are socio-culturally and contextually rooted/situated, and that is how this study becomes socially relevant.
Originality/value
This paper is an original piece of research and has been envisioned in view of the challenging business scenarios across the world today. This paper underscores the importance of strategically combining AI and big data, as they have enormous bearing on modern businesses. The insights arrived at in this paper have implications for business leaders and entrepreneurs across the globe who could focus more on ontological and communicative perspectives of AI combined with Big Data to deal with diverse range of challenges and problems that modern businesses have been facing particularly in recent times.
“…Companies that leverage AI for supply chain optimization, product innovation, and data-driven decision making can improve their market positioning, both locally and globally. This, in turn, can attract foreign investments and foster economic resilience, crucial for the region's ongoing development [91][92][93].…”
This research paper delves into the pivotal role of strategic integration of artificial intelligence (AI) concepts across sustainability efforts in for-profit businesses. As organizations are increasingly starting to rely on AI-driven solutions, this study examines the profound implications of AI integration for two critical facets: impact on data management in companies and diversification of human engagement during interactions in the digital ecosystem. The main goal of this research is to analyze the AI adoption index within a sample of 240 medium and large-sized companies (therefore excluding new companies, small startups, and low-scale AI applications). Firstly, the paper scrutinizes how AI technologies enhance data management by enabling efficient data collection, analysis, and utilization. It emphasizes the importance of AI-driven data analytics in improving decision-making processes, resource optimization, and overall operational efficiency for sustainable practices. Secondly, this research explores how AI-driven personalization, omnichannel interactions, and recommendation systems significantly impact user experiences, satisfaction, and loyalty, ultimately contributing to sustainable business growth. Findings show that there are three separate profiles of companies (low, moderate, and high), distinguished by AI adoption index and other important dimensions. Future research should focus on determining preconditions for successful planning of AI adoption index improvement, using a data-driven approach.
The current business environment faces numerous new challenges closely linked to the rapid development of information and communication technologies, which influence the corporate landscape. This article focuses on exploring the possibilities of integrating artificial intelligence, as one of the key technologies of today, into the recruitment process. Its aim is to examine the potential applications of artificial intelligence across various stages of employee recruitment. To achieve this goal, the authors employed various methods and techniques, including the PICOS framework, scientific mapping, and case study analysis. The outcome of this study identifies opportunities for leveraging artificial intelligence in the employee recruitment process within corporate settings. The results reflect the current research gaps concerning the analysis of the personnel processes and conceptualizing the implementation possibilities of artificial intelligence in these processes. The contribution of this article to the academic community lies in its conceptualization, providing a foundation for further research focused on analyzing the impacts of integrating AI into recruitment processes.
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