Asset standard classification using artificial intelligence

By adopting a case study methodology, the research leverages real-world data sourced from CBRE, a global leader in Commercial Real Estate (CRE) services, to evaluate the performance and potential of AI for classification systems in streamlining and standardizing asset management processes through analysis of AI driven methodologies to optimize the efficiency and accuracy of asset standard classification by processing extensive datasets from CBRE clients worldwide, ultimately improving the effectiveness of Preventive Maintenance Plans (PPM). The focus is mainly on the usage of the given data to analyse the effectiveness of Ellis AI and other AI tools with corresponding performance indicators and self-designed process methodology.