Wettability measurements have been the subject of interest for many researchers due to the importance of hydrocarbon production and enhanced oil recovery (EOR). Contact angle measurement is one of the industry-standard methods for measuring the surface wettability of rocks. This technique is affected by several parameters: temperature, pressure, salinity and surface roughness. There has not been an established and acceptable methodology developed to quantify their influence on angle measurements due to their complex trends. This paper reviews the impact that these parameters have on contact angle measurements and summarises their influence. The paper also acknowledges the significant knowledge gap in need of further research. Finally, this gap leads to the proposal of a novel application of artificial intelligence techniques in quantifying these parameters' effect. The application of advanced data analytics and unsupervised learning can reveal insights and analyse the coupling effect of several parameters and their impact on contact angle measurements. Further application of supervised machine learning can be used to predict the contact angle of surfaces within the variable range of testing parameters. © 2022 Inderscience Enterprises Ltd.