Empirical insights into the reduction of operational costs through AI: A study of Jordanian companies

Objective: I investigated how artificial intelligence (AI) tools can help reduce operational costs in businesses across Jordan. I examined the specific ways AI enhances efficiency and optimises resource utilisation, ultimately impacting financial outcomes. Research Design & Methods: I utilised a qualitative research approach, employing a systematic literature review and thematic analysis to examine how AI contributes to reducing operational costs. The review consolidates findings from academic and industry sources to identify key trends. I performed thematic analysis to extract insights on AI-driven automation, cost efficiency strategies, and the challenges associated with implementation. The study does not involve primary data collection or empirical case studies. The study offers recommendations to assist businesses in optimising AI adoption. Findings: Study identified key themes on how AI reduces operational costs, Key cost-saving mechanisms include automation, predictive analytics, and resource optimisation. Sectors like manufacturing, finance, and telecommunications reduce operational costs by cutting labour costs, improving decisions, and increasing efficiency. Challenges include high costs, training gaps, and implementation risks. One must address them to ensure successful AI adoption. Findings are based on literature analysis, and not on primary data. Implications & Recommendations: The research emphasised the need for Jordanian companies to adopt AI to remain competitive and boost profitability. Businesses should invest in AI training to upskill their workforce. AI requires integrating in areas with clear, measurable benefits. Partnering with AI firms can help streamline adoption and integration. Contribution & Value Added: This study presents a structured analysis of AI-driven cost reduction, highlighting how automation, predictive analytics, and supply chain optimisation enhance operational efficiency. Unlike broader studies on AI adoption, I specifically examined cost-saving mechanisms within Jordanian businesses, tackling challenges such as high initial investment costs and workforce skill gaps. The study offers practical recommendations for businesses and policymakers, contributing to the wider discussion on AI’s role in digital transformation and financial sustainability.