Artificial Intelligence in Project Selection in Process Industries: Enhancing Prioritization, Risk Management, and Decision-Making

Sammanfattning

Artificial intelligence (AI) is increasingly applied in project selection within process industries such as oil and gas, mining, and chemical manufacturing, yet its specific impact on prioritization, risk management, and decision-making remains underexplored. This thesis addresses this gap through a qualitative study that is a systematic literature review with manual content analysis of 36 peer-reviewed articles. The findings reveal that AI enhances project selection by enabling multi-criteria evaluation, improving risk identification and mitigation, and supporting faster, data-driven decisions. Importantly, the study distinguishes between AI integration (technical embedding in organizational systems) and AI utilization (practical application and adoption), emphasizing the need for human–AI collaboration to achieve meaningful benefits. The research contributes theoretically by framing AI as both a technical enabler and a strategic decision-support tool, and practically by offering managers insights on leveraging AI to align project portfolios with corporate strategy while improving operational resilience. Future research is encouraged to validate these findings through empirical case studies and to examine in greater depth the ethical dimensions of AI-driven decision-making.