Impact of Big Data and Artificial Intelligence on Industry: Developing a Workforce Roadmap for a Data Driven Economy

Abstract

Big Data and Artificial Intelligence (BD&AI) have become so pervasive, and the opportunities they present so transformative, that they are viewed as essential for competitive growth. Since the number of firms adopting BD&AI technologies is growing exponentially, the demand for BD&AI practitioners is also growing at a rapid rate. However, several studies indicate that there is a BD&AI talent shortage and skills gap between labor market requirements and expertise available in the current workforce. This talent shortage and skills gap are now recognized as a crucial impediment in leveraging BD&AI for economic growth at the local, national, and global levels. This research aims to identify BD&AI workforce trends, gaps, and opportunities by using bibliometric analysis and extracting insights from job posting data. The study team first conducted bibliometric research and built word cooccurrence diagrams using BD&AI related articles published in high-impact journals to determine technological changes impacting various industry domains. The team then collected job postings data and summarized the skill sets required to be competitive in industries driven by BD&AI. Finally, the study team evaluated the curricula of BD&AI programs at various colleges and universities educating the future workforce and conducted a SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis to bridge the gaps between industry needs and academic training. This multi-step research framework forecasts oncoming technological changes in various industry clusters, workforce skills that are and will be needed, and provides recommendations for a workforce development roadmap so that businesses can gain a competitive advantage through the use of BD&AI.

Artificial intelligence feasibility in construction industry

“…Governments may provide their workforce with a competitive advantage by educating, developing, and enabling access to people with sophisticated computer and analytics skills. Because AI education necessitates hands-on experience, industry and academia should work together to develop apprenticeship programs that allow students to rotate around multiple firms and learn about AI applications in a variety of sectors and job functions (Johnson et al 2021). Employers must be able to share their expertise with students through academia.…”

In search of pedagogical approaches to teaching business ethics in the era of digital transformation

“…This paper builds on research that we conducted as members of the New Jersey Big Data Alliance during December 2018 and January 2019 to develop a "New Jersey Big Data Workforce Roadmap" that could ensure a skilled workforce in the State of New Jersey is prepared for current and future technological changes (Johnson et al 2021). In this research, we examined specific technological changes, such as AI, machine learning, and large-scale automation, that are impacting New Jersey's major industry clusters (e.g., health care, logistics, food, financial services, clean energy, and advanced manufacturing), and the resultant skills needed for a competitive workforce.…”

“…Our research concluded, "most companies have not realized the full potential of these technological advances due to a number of barriers, including talent shortages. By educating, training, and facilitating access to individuals with advanced computing and analytics skill sets, New Jersey can provide a competitive advantage for its employers" (Johnson et al 2021). However, training in business ethics and applying ethical considerations through critical thinking skills was not a part of that research.…”

Organizational Structure and Artificial Intelligence. Modeling the Intraorganizational Response to the AI Contingency

“…Further implementation of technologies based on deep learning, machine learning, and other types of artificial intelligence will not necessarily eliminate existing jobs in their entirety. While some of the simpler jobs that do not require significant intellectual effort, empathy, or intuition may disappear, and new jobs related to the emerging technologies will eventually appear [20][21][22], the main tendency of the following years will be the redesign of existing jobs to accommodate technological advances.…”

“…Although several attempts were made to understand the nature of the interrelationship between AI-related technologies and the structural characteristics of an organization [20][21][22]30,39,40,46], to our knowledge, this study represents the first in its kind addressing the issue systemically across multiple dimensions of the ideal-type of a typical organizational structure. Indeed, the previous studies were mainly concerned with micro job-related issues, both vertically [20][21][22][23]25,26] and horizontally [29,31,32]. The important mesolevel variables-mainly related to the span of control, number of hierarchical levels, centralization, standardization, formalization, and incentives-have been consistently neglected by scholars.…”