Optimization of Generative AI Efficiency: A Case Study Based on Professional Workshop Questionnaires

Authors

  • Milica Mravik Faculty of Informatics and Computing, Singidunum University, Belgrade
  • Marko Šarac Faculty of Computing and Informatics, Sinergija University, Bijeljina

DOI:

https://doi.org/10.7251/ZRSNG2526001M

Abstract

In this research, we explored the strategic optimization of Microsoft 365 Copilot by examining the transition from
theoretical readiness to practical user mastery. This research was based on a structured "Art of the Possible" (AOTP) workshop
approach, which was the key method for discovering high-impact business scenarios. By analysing quantitative and qualitative
information from an AI Workshop Questionnaire, we were able to determine the impact of specific organizational interventions
on user adoption and technical efficiency. Our results showed that successful optimization was more than just a function of
technical setup and was instead highly reliant on expertise in prompt engineering and addressing security issues, like data
oversharing. In addition, we emphasized the need for a "Crawl Walk-Run" approach and the critical role of internal
"Champions" in maintaining digital transformation. We concluded that a feedback loop between end-users and stakeholders is necessary for aligning generative AI capabilities with organizational goals.

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Published

2026-10-05