TY - JOUR
T1 - Impact of Big Data and Artificial Intelligence on Industry
T2 - Developing a Workforce Roadmap for a Data Driven Economy
AU - Johnson, Marina
AU - Jain, Rashmi
AU - Brennan-Tonetta, Peggy
AU - Swartz, Ethne
AU - Silver, Deborah
AU - Paolini, Jessica
AU - Mamonov, Stanislav
AU - Hill, Chelsey
N1 - Publisher Copyright:
© 2021, Global Institute of Flexible Systems Management.
PY - 2021/9
Y1 - 2021/9
N2 - 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 co-occurrence 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.
AB - 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 co-occurrence 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.
KW - Analytics curriculum
KW - Artificial Intelligence
KW - Big Data
KW - Workforce
UR - http://www.scopus.com/inward/record.url?scp=85106508009&partnerID=8YFLogxK
U2 - 10.1007/s40171-021-00272-y
DO - 10.1007/s40171-021-00272-y
M3 - Article
AN - SCOPUS:85106508009
SN - 0972-2696
VL - 22
SP - 197
EP - 217
JO - Global Journal of Flexible Systems Management
JF - Global Journal of Flexible Systems Management
IS - 3
ER -
