Evlaulating AI implementation in Kazakhstan’s industrial projects: a statistical approach

2025

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DOI 10.52821/2789-4401-2025-4-248-263
Data confidence 70 medium
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Abstract

Purpose – The research examines how artificial intelligence (AI) affects industrial project outcomes in Kazakhstan by studying cost reduction and time efficiency alongside risk management effectiveness. Methodology – Based on the data collected from publicly accessible project databases, company reports as well as expert surveys, statistical methods including descriptive statistics, regression analysis, and comparative methods such as T-tests or ANOVA, were employed to evaluate the performance of 40 industrial projects in Kazakhstan, comprising 20 AI-enabled and 20 non-AI projects from the energy, manufacturing, and infrastructure sectors. Originality / value – This research addresses the insufficient statistical analysis of AI’s impact on industrial projects in Kazakhstan, by providing quantitative evidence of its effects on key project outcomes like cost, timeline, and risk control. This study offers valuable insights for industry executives and government leaders in Kazakhstan regarding the benefits and effectiveness of AI integration in industrial projects for enhanced performance and sustainable economic expansion. Findings – The study’s findings indicate that the adoption of AI in industrial projects in Kazakhstan leads to a reduction in project costs by 10% and an acceleration of project timeframes by 15%, when compared to traditional non-AI project efforts. Furthermore, AI implementation resulted in a 40% reduction in project risks and a higher project success rate of 92% for AI-enabled projects versus 85% for non-AI projects.