From code to quality: How AI is transforming quality management in Algerian startups

This study examines the role of artificial intelligence in enhancing quality management practices within Algerian startups, focusing specifically on how AI-driven business intelligence contributes to competitive advantage through quality improvements in emerging market contexts. The research employs quantitative methodology, utilizing structural equation modeling (CB-SEM) to analyze data collected from 357 Algerian startups. The study implements a comprehensive measurement framework incorporating quality management practices, AI implementation status, and competitive advantage indicators, validated through confirmatory factor analysis. The analysis reveals that quality management supported by artificial intelligence has a moderate positive impact on competitive advantage (correlation coefficient 0.346, p < 0.001). Organizations implementing AI-enabled quality management systems achieved a 52.4% improvement in overall quality metrics. Customer response capability scored highest among quality dimensions (mean score 2.86), while product-market alignment showed room for improvement (mean score 2.53). The research identified three critical areas of AI integration success: quality control automation, predictive quality management, and customer response systems. The study provides actionable insights for startups in emerging markets implementing AI-driven quality management systems. The findings suggest a staged approach to technology adoption, emphasizing the importance of foundational quality management practices before advanced AI integration. Results indicate that successful implementation requires balanced investment in both technological infrastructure and organizational capabilities. While Algerian startups demonstrate awareness of and commitment to AI-enabled quality management, with 50.8% showing a positive disposition toward adoption, actual implementation remains at moderate levels. The study highlights significant opportunities for enhancement in quality management through strategic AI integration, particularly in emerging market contexts where technological infrastructure and resource constraints present unique challenges.