The Impact of Artificial Intelligence on Strategic Decision-Making and the Improvement of Key Performance Indicators (KPIs)

سال انتشار: 1404
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 7

نسخه کامل این مقاله ارائه نشده است و در دسترس نمی باشد

استخراج به نرم افزارهای پژوهشی:

لینک ثابت به این مقاله:

شناسه ملی سند علمی:

JR_TRANS-7-2_003

تاریخ نمایه سازی: 22 مهر 1405

چکیده مقاله:

This study investigates the structural impact of Artificial Intelligence (AI) adoption on strategic decision-making and the optimization of Key Performance Indicators (KPIs) within organizations in Tehran, employing a quantitative, survey-based design. The statistical population comprised ۳۸۴ managers and senior executives selected from Districts ۲, ۵, and ۷ of Tehran. Data were collected via a standardized questionnaire and analyzed using SPSS and Structural Equation Modeling via Partial Least Squares (PLS-SEM). The empirical findings indicate that while AI deployment exerts a positive and statistically significant effect on the "speed of decision-making" (mean: ۳.۸۰), substantial bottlenecks persist regarding "KPI improvement" (mean: ۳.۱۰) and "human resource readiness" (mean: ۲.۹۰). A comparative regional analysis revealed that District ۲ exhibits the highest echelon of digital maturity, primarily driven by a dense concentration of knowledge-based enterprises. Conversely, Districts ۵ and ۷ suffer from pronounced skill and infrastructural deficits. The study concludes that organizations in Tehran are currently navigating a "transitional phase"; although technical tools are increasingly available, the organizational culture and human competencies required to leverage their full potential have not yet matured. Consequently, driving sustainable digital transformation demands a strategic shift from a "technology-centric" to a "human-centric" paradigm. Based on these insights, the research offers operational recommendations, emphasizing the formulation of specialized upskilling programs, the cultivation of an agile organizational culture of innovation, the integration of data infrastructures, and the implementation of district-tailored regional policies. Ultimately, this study provides an actionable roadmap for executives to mitigate current systemic bottlenecks and facilitate the transition toward smart, agile organizations.

کلیدواژه ها:

نویسندگان

- -

M.Sc. in Business Administration (Strategic Management), Tehran, Iran