Enhancing IT Efficiency: Cloud, AI, and Hyper Automation Strategy - A Left Shift Optimization


  • Sandeep Kumar Chanda


The landscape of digital transformation has come a long way, and organizations are constantly seeking innovative strategies to optimize their IT functions, enhance customer experiences, and drive business growth. The advent of Cloud, AI and Hyper Automation presents a transformative opportunity for businesses, especially those in the upper mid-market segment undergoing digital transformation. This thesis explores the adoption and operationalization of these technologies through a "Shift-Left" strategy, a paradigm that emphasizes proactivity, efficiency, and customer centricity in IT services.
The research is based on qualitative analysis and aims to enhance organizational performance by leveraging advanced technologies. The aim is to garner insights into current governance practices, challenges encountered, experiences with shift-left strategies, and the perceived business value derived from digital transformation initiatives.

The Findings reveal a notable alignment between the shift-left strategy and enhanced IT function optimization, primarily facilitated by the integration of Cloud, AI, and Hyper Automation. The strategy's proactive nature allows for early detection and resolution of issues, leading to improved operational efficiency and customer satisfaction. However, challenges such as resistance to change, compatibility with existing systems, and the need for a robust governance framework are identified as potential barriers to the successful adoption of the strategy. The findings highlight the benefits and challenges associated with this strategic approach, providing valuable insights for IT professionals seeking to improve efficiency and productivity in their operations.




How to Cite

Chanda, S. K. (2024). Enhancing IT Efficiency: Cloud, AI, and Hyper Automation Strategy - A Left Shift Optimization. Global Journal of Business and Integral Security. Retrieved from https://www.gbis.ch/index.php/gbis/article/view/435