Since the 1960s, research has dealt with agricultural intensification (AI) as a solution to ensure global food security. Recently, sustainable intensification (SI) has increasingly been used to describe those agricultural and farming systems that ensure adequate ecosystem service provision. Studies differ in terms of the application scales and methodologies, thus we aim to summarize the main findings from the literature on how AI and SI are assessed, from the farm to global levels. Our literature review is based on 7865 papers selected from the Web of Science database and analysed using CorText software. A further selection of 105 relevant papers was used for an in-depth full-text analysis on: i) farming systems studied; ii) related ecosystem services; iii) indicators of intensity; and iv) temporal and spatial scales of analysis. Through this two-step analysis we were able to highlight three main research gaps in the AI research indicators. Firstly, the farming systems analysed for assessing AI are often quite simplified or monoculture-oriented, and they do not take the diversity and complex organisation of farming systems into account. Secondly, these studies mainly focus on northern countries or developing countries, whereas there is a gap of knowledge in Mediterranean areas, which are the areas with a high complexity of farming systems and diversity in ecosystem services. Finally, AI is mostly assessed through nitrogen inputs and economic yield, which are used the most both at very local and global levels. Intermediate regional or local levels, which are relevant for policy implementation and local planning, are often neglected.