R&DE Processes With Artificial Intelligence: Mapping Applications and Impacts

Abstract

Artificial Intelligence (AI) is becoming a critical resource for Research and Development and Engineering (R&DE) within organizations, reshaping processes across sectors in a rapidly evolving technological landscape. This study systematically maps AI applications across various R&DE processes, identifying specific impacts achieved in different sectors and industries. By analyzing 2,219 business practices from the literature, the study classifies where and why AI is employed within R&DE, highlighting its role in optimizing product design, enhancing innovation, and accelerating prototyping. AI's integration into R&DE has proven valuable in addressing complexities such as cost reduction, time efficiency, and improved decision-making. Through content and cluster analysis, ten potential research areas — security, investments, mechanism, monitoring, robotics, safety, energy, innovation, experience, and prediction — are identified, illustrating how AI enhances R&DE processes and outcomes. This assessment reveals sector-specific patterns of AI adoption, such as its widespread use in automotive, construction, transportation and logistics, digital industries, and healthcare. It also uncovers opportunities for future exploration in under-represented sectors. These findings support the strategic use of AI in R&DE, positioning it as a tool for long-term growth in an increasingly competitive business landscape.