THE SYNERGISTIC EFFECT OF AI-DRIVEN PREDICTIVE ANALYTICS AND EMPLOYEE DIGITAL AGILITY ON STRATEGIC DECISION-MAKING SPEED

Muhammad Tariq Siddiqui; Ambreen Ashfaq; Muhammad Kamran Ashfaq; Sarim Zafar; Ariba Khan; Fatima Zafar Farooqui

Authors

Muhammad Tariq Siddiqui
Ambreen Ashfaq
Muhammad Kamran Ashfaq
Sarim Zafar
Ariba Khan
Fatima Zafar Farooqui

Keywords:

AI-Driven Predictive Analytics, Employee Digital Agility, Strategic Decision-Making Speed, Technology-Driven Firms, Organizational Synergy

Abstract

Purpose: This study investigates the synergistic effect of AI-driven predictive analytics adoption and employee digital agility on strategic decision-making speed in technology-driven firms. It specifically examines the direct relationships between these variables and the moderating role of employee digital agility.

Methodology: A quantitative, cross-sectional research design was employed using a structured survey distributed to 200 managers across technology-driven firms in Karachi, including software development, fintech, telecommunications, and e-commerce sectors. Data were analyzed using linear regression to test the hypothesized relationships.

Findings: The results revealed that employee digital agility (β = 0.325, p < 0.001) and strategic decision-making speed (β = 0.237, p = 0.002) are significant positive predictors of AI-driven predictive analytics adoption. Employee digital agility emerged as the stronger predictor, indicating that workforce proficiency in learning and leveraging digital tools is critical for successful AI analytics integration. The findings confirm that organizations combining digitally agile workforces with rapid decision-making processes are better positioned to harness predictive analytics capabilities.

Originality/Value: This study addresses a significant gap in the literature by empirically examining the synergistic interplay between human digital capabilities and organizational decision velocity in facilitating AI analytics adoption. Unlike prior research that treats technology adoption and workforce agility as parallel phenomena, this study demonstrates their joint significance, offering valuable insights for leaders in technology-driven firms. The findings suggest that strategic investments should balance technological infrastructure with workforce development to optimize AI-driven decision-making capabilities. Future research should explore longitudinal effects and additional moderating variables across diverse industry contexts.