Smart Harvesting brings artificial intelligence and sophisticated automation to the process of creating comprehensive research repositories and updating researcher profiles, which saves time and reduces manual work. This technology makes it possible for institutions to showcase the work of affiliated researchers completely and accurately, in one place and across all disciplines. Matching research output to the right researcher, and ensuring you included everything, is often a complicated exercise. Smart Harvesting accomplishes this goal with unique machine learning algorithms for tackling two key tasks: matching scholars to their work; and populating the research information hub with this information at scale. For effective Smart Harvesting, machine learning identifies and assesses three main data properties: individual names; general information from the outputs; and semantic content.