The selection of initial systemic treatment for advanced non-small cell lung cancer (NSCLC) depends on histological subtypes, oncogenic driver identification through genomic profiling, and programmed death-ligand 1 (PD-L1) expression quantification. The choice of first-line treatment is crucial as patients with advanced NSCLC may not have the opportunity to receive second- or later-line therapies due to the rapid progression of the disease. Current guidelines recommend pretreatment PD-L1 expression quantification evaluation prior to initiating systemic therapy in advanced NSCLC. Except for histology, PD-L1 expression, and absence of actionable driver mutations, single-agent immune checkpoint inhibitors (ICIs) are foundational first-line interventions. ICIs combined with chemotherapy or other ICIs have shown improved survival outcomes compared to ICI monotherapy. However, choosing the best option can be challenging due to limited head-to-head comparisons. Treatment decisions are often influenced by drug availability, reimbursement coverage, and patient's economic conditions. Despite the development of new ICI therapies, overall survival data seem to have plateaued, highlighting the need for sustained investigations and extensive clinical validation studies to develop novel therapies, optimize ICI combinations, and monitor adverse effects. Collaboration among data scientists, clinicians, biologists, and policymakers is essential to establish biomarkers that enhance patient selection and overall survival in NSCLC.