Internet has become an instant source of information for almost anyone. By viewing the results of search terms displayed by an Internet Search Engine (ISE), a person may decide his next course of action whether to continue using the Internet, abort or to combine it with other sources of information. The results produced by an ISE can be regarded as an index of relative availability of references. Given a list of suitable search terms, a user will firstly have to decide on the ISE to be used. Due to huge potential references available for given search terms the user has to create heuristics to choose the entries shown on the computer screen. As there are varying breadths and depths of information revealed by various Internet Search Engines (ISE's), this paper will not attempt to make a comparison among ISE's, rather will focus only on a particular search engine and ascertain the results it produces given a list of search terms. Google is chosen as a proxy, being one of the most popular ISE's. By confining to only a search engine, the study affords to control variability among ISE's should multiple ISE's be used. With the search engine placed under control, it is easy to achieve the primary objective of the study, i.e., to ascertain availability of relative breadth of sub-themes of Analytic Hierarchy Process (AHP) in Google. It is natural for user, especially researcher to be concerned with number, quantity. If there is seemingly abundant literature, one would be motivated to pursue research along the theme or sub-theme. In this study, the strength of presence of a sub-theme is measured by using two measures: (i) result of a sub-theme of AHP over the sub-theme itself, and (ii) result of the sub-theme over the total results generated for all of the thirty six sub-themes used in the search. This study controlled biasness in specifying the sub-themes of AHP by adopting the sub-themes or search terms specified by the 2013 AHP conference organizers. This decision helps make the study efficient without with it has to distill the sub-themes by surveying the AHP literature. The data for analysis was gathered by surfing Google on 26 Feb 2013 8.55 p.m.-9.26 p.m. Peninsular Malaysian time. The search results were computed to generate two types of ratios specified earlier. A composite index was created using the resulting two types of ratios which are used to classify the efficiency, hence dominance of the original results (hits). Kendall's correlation produced statistically significant correlations between the composite index and Rank of AHP specific and area results. Using indices greater than 1.000 as the base, 6 AHP specific areas occupy the top positions with ratios ranging from 19.341 to 61.574; 15 AHP specific areas occupy the second top positions with ratios ranging from 1.119 to 9.602, and 14 AHP specific areas occupy the third and last position with indices below 1.000 ranging from 0.050 to 0.894. The paper includes discussion, implications, limitations, conclusions and suggestions for further research.