Colorectal cancer (CRC) remains one of the leading causes of cancer-related mortality worldwide, with liver metastasis (LM) being the most common site of spread. The emergence of immunotherapy has changed the landscape of cancer treatment, providing therapeutic options for the management of CRC, especially in metastatic settings. Typically, CRC with microsatellite instability-high (MSI-H) status respond more favorably than those that are microsatellite stable (MSS). However, it has been observed that the presence of LMs limits the efficacy of immunotherapy irrespective of the microsatellite instability (MSI) status, which presents unique challenges in managing CRC with LMs (CRCLM). The exact mechanisms for resistance to immunotherapy in CRCLM are poorly understood. Several factors in the liver tumor microenvironment (TME) have been linked to therapeutic failures with immunotherapy in CRCLM. Novel agents that explore and target immunosuppressive elements in the liver TME, such as the lymphocyte activation gene 3 (LAG-3) and vascular endothelial growth factor receptor (VEGFR), in combination with anti-programmed death-1/ligand-1 (PD-1/PD-L1) have been found to improve immunotherapy response in CRCLM. Machine learning-based bioinformatics may provide further understanding of the several molecular mechanisms in the liver TME that may represent potential areas for therapeutic options and precision cancer medicine. This manuscript explores the challenges associated with immunotherapy in this subset of patients, focusing on TME, immune resistance mechanisms, and potential strategies to enhance immunotherapeutic outcomes.