A Cross-Sector Analysis of Modern Trends in Digital Transformation

  • Authors

    • Dr. Matteo Rossi Professor, Sapienza University of Rome, Italy. Author
    • Dr. Giulia Romano Associate Professor, University of Milan, Italy. Author

    DOI:

    https://doi.org/10.67228/30715628/IJMIET-2023PII1Y3L

    Published 07-05-2023

  • Digital Transformation, Cross-Sector Analysis, Artificial Intelligence, Cloud Computing, IoT, Industry 4.0, Blockchain, Enterprise Architecture, Data Analytics, Cyber-Physical Systems, Hyper-Automation

    Issue

    Vol. 6 No. 2 (2023)

    Section

    Articles

    How to Cite

    [1]
    M. Rossi and G. Romano, “A Cross-Sector Analysis of Modern Trends in Digital Transformation”, ijmiet, vol. 6, no. 2, pp. 01–15, Jul. 2023, doi: 10.67228/30715628/IJMIET-2023PII1Y3L.

  • Abstract

    Digital transformation (DX) has matured to be a sector-neutralized technological uptake operation to a everywhere strategic urgency within industries. Rapid development of cloud computing, artificial intelligence (AI), edge computing, blockchain infrastructures, Internet of Things (IoT), robotic automation, and data-driven decision-ecosystems have transformed conventional business strategies and business environments. This paper provides a comprehensive cross-sector discussion on digital transformation currently and specifically regarding technology convergence, enterprise integration practices, socio-technical outcomes and performance. The research applies the multi approach method, involving literature synthesis, framework modelling, enterprise case study and qualitative analysis of sectors in healthcare, manufacturing, finance, transportation, education and the government sectors. The evaluation shows that pressure to digital transformation is ever more being mounting on strategic innovation, cybersecurity governance, customer centric service model and sustainability requirements. Synergy of clouds and AI, hyper-automation, intelligent platform, and predictive analytics are the most powerful technology enablers. The paper has pinpointed several significant issues such as data fragmentation, inability to achieve interoperability, skills mismatch in the workforce, constraint of the legacy infrastructure and ethical issues in AI-managed decision systems. A research methodology has been suggested as a model of systematic evaluation of technology preparedness, process reengineering, and digital maturity measurement. Outcomes indicate that there are strong relations between transformation success and the organizational capabilities, cultural preparedness, and technological agility. The synthesis is giving rise to a better comprehension of the cross-sector transformation mechanisms which should be taken into the consideration of policy makers, digital strategists as well as the enterprise architects or industry leaders. The paper ends with recommendations on the future research directions of sectoral convergence, responsible AI governance, and next generation transformation architecture that includes quantum computing systems, 6G-enabled intelligent ecosystems, and autonomous cyber-physical enterprises.

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