Biological control of weeds involves deliberate introduction of host‐specific natural enemies into invaded range to reduce the negative impacts of invasive species. Assessing the specificity is a crucial step, as introduction of generalist natural enemies into a new territory may pose risks to the recipient communities. A mechanistic understanding of host use can provide valuable insights for the selection of specialist natural enemies, bolster confidence in non‐target risk assessment and potentially accelerate the host specificity testing process in biological control. We conducted a comprehensive analysis of studies on the genomics of host specialization with a view to examine if genomic signatures can help predict host specificity in insects. Focusing on phytophagous Lepidoptera, Coleoptera and Diptera, we compared chemosensory receptors and enzymes between “specialist” (insects with narrow host range) and “generalist” (insects with wide host range) insects. The availability of genomic data for biological control agents (natural enemies of weeds) is limited thus our analyses utilized data from pest insects and model organisms for which genomic data are available. Our findings revealed that specialists generally exhibit a lower number of chemosensory receptors and enzymes compared with their generalist counterparts. This pattern was more prominent in Coleoptera and Diptera relative to Lepidoptera. This information can be used to reject agents with large gene repertoires to potentially accelerate the risk assessment process. Similarly, confirming smaller gene repertoires in specialists could further strengthen the risk evaluation. Despite the distinctive signatures between specialists and generalists, challenges such as finite genomic data for biological control agents, ad hoc comparisons, and fewer comparative studies among congeners limit our ability to use genomic signatures to predict host specificity. A few studies have empirically compared phylogenetically closely related species, enhancing the resolution and the predictive power of genomics signatures thus suggesting the need for more targeted studies comparing congeneric specialists and generalists.