The Human Side of IT: Bridging Skills Gaps in a Rapidly Changing Industry

Authors

  • Simone De Bellis Independent Researcher

Keywords:

Data privacy, Zero Trust, Cloud computing, Artificial intelligence, Cybersecurity frameworks

Abstract

The IT industry is evolving rapidly owing to factors such as the three main drivers being artificial intelligence, machine learning, and cloud computing. However, this evolution has exposed a significant challenge: the existing and widened differences between the required job competencies and the available human capital. The inequality above is called the IT skills gap and threatens prospects for innovation, productivity, and competitiveness. Such variables as outdated educational models, lack of opportunities to complete training programs, and the high technological development rate worsen the situation.

Filling this gap requires solving complex problems and focusing on cooperation between universities, companies, and governmental agencies. Accomplishments with training programs, reskilling, and cross-sector collaborations indicate the training necessary for leaders and professionals to enable them to work in the digital economy environment. However, sustaining workforce readiness is possible through embracing the culture of learning and unlearning through that accreditation.

This paper outlines the subject's significance by analyzing the difficulties arising from the lack of IT skills, the qualitative success of the case studies under consideration, and the practical recommendations for their solution. Only when human capital is properly matched to technology can stakeholders unleash the full potential of this market.

References

• Amazon Web Services. (2019). AWS Training and Certification. https://aws.amazon.com/training

• Autor, D. H. (2015). Why Are There Still So Many Jobs? The History and Future of Workplace Automation. Journal of Economic Perspectives, 29(3), 3–30. https://doi.org/10.1257/jep.29.3.3

• Brynjolfsson, E., & McAfee, A. (2014). The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies. W.W. Norton & Company.

• Cappelli, P. (2015). Skill gaps, skill shortages, and skill mismatches: Evidence and arguments for the United States. ILR Review, 68(2), 251–290. https://doi.org/10.1177/0019793914564961

• Carnevale, A. P., Smith, N., & Strohl, J. (2013). Recovery: Job Growth and Education Requirements Through 2020. Georgetown University Center on Education and the Workforce. https://cew.georgetown.edu/cew-reports/recovery-job-growth-and-education-requirements-through-2020/

• Cisco. (2017). Cisco Networking Academy. https://www.netacad.com

• Cisco Systems. (2017). The Future of Jobs: Employment, Skills, and Workforce Strategy for the Fourth Industrial Revolution. World Economic Forum. https://www.weforum.org/reports/the-future-of-jobs

• Coursera. (2018). Google IT Support Professional Certificate. https://www.coursera.org

• Dweck, C. S. (2006). Mindset: The New Psychology of Success. Random House.

• Friedman, T. L. (2005). The World Is Flat: A Brief History of the Twenty-First Century. Farrar, Straus, and Giroux.

• Gomez-Uribe, C. A., & Hunt, N. (2016). The Netflix Recommender System: Algorithms, Business Value, and Innovation. ACM Transactions on Management Information Systems, 6(4), Article 13. https://doi.org/10.1145/2843948

• IBM. (2017). IBM Skills Academy: Bridging the Digital Talent Gap. https://www.ibm.com

• Liker, J. K. (2004). The Toyota Way: 14 Management Principles from the World's Greatest Manufacturer. McGraw-Hill Education.

• Manyika, J., et al. (2017). A Future That Works: Automation, Employment, and Productivity. McKinsey Global Institute.

• Microsoft. (2020). Microsoft Global Skills Initiative.

• Pfeffer, J., & Sutton, R. I. (2000). The Knowing-Doing Gap: How Smart Companies Turn Knowledge into Action. Harvard Business Review Press. https://jeffreypfeffer.com/books/the-knowing-doing-gap/

• Schwab, K. (2016). The Fourth Industrial Revolution. Crown Business.

• W. W. Norton & Company. Publisher of The Second Machine Age by Brynjolfsson and McAfee.

• Rahaman, M. M., Rani, S., Islam, M. R., & Bhuiyan, M. M. R. (2023). Machine Learning in Business Analytics: Advancing Statistical Methods for Data-Driven Innovation. Journal of Computer Science and Technology Studies, 5(3), 104-111.

• Linkon, A. A., Noman, I. R., Islam, M. R., Bortty, J. C., Bishnu, K. K., Islam, A., ... & Abdullah, M. (2024). Evaluation of Feature Transformation and Machine Learning Models on Early Detection of Diabetes Melitus. IEEE Access.

• Sumon, M. F. I., Khan, M. A., & Rahman, A. (2023). Machine Learning for Real-Time Disaster Response and Recovery in the US. International Journal of Machine Learning Research in Cybersecurity and Artificial Intelligence, 14(1), 700-723.

Published

30-09-2024

How to Cite

Simone De Bellis. (2024). The Human Side of IT: Bridging Skills Gaps in a Rapidly Changing Industry. Well Testing Journal, 33(S2), 512–531. Retrieved from https://welltestingjournal.com/index.php/WT/article/view/120

Issue

Section

Research Articles

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