Evolving and novel applications of artificial intelligence in interventional oncology

Artificial intelligence (AI) is increasingly influencing clinical oncology, yet its role in interventional oncology (IO) has not advanced as rapidly, despite IO’s heavy reliance on imaging, precision, and real-time decision-making. While AI has demonstrated utility in other medical disciplines such as diagnostic radiology and medical oncology, its adoption in IO is still emerging and varies across applications. This review provides a comprehensive overview of current and emerging applications of AI across the IO workflow, including procedural planning, real-time navigation and treatment delivery, and post-procedural evaluation. It also explores system-level innovations and patient-centered tools designed to enhance workflow efficiency, documentation, education, and follow-up. These technologies hold promise for improving consistency, personalizing treatment, and enhancing safety. Although existing applications demonstrate clear clinical value, broader adoption will depend on overcoming technical, ethical, and infrastructure barriers. Addressing these challenges will require prospective validation, infrastructure development, and sustained multidisciplinary collaboration. As AI tools evolve, their potential to connect fragmented stages of care and enable adaptive, data-driven interventions may redefine IO practice. This review clarifies the current landscape, identifies key implementation barriers, and outlines priorities for future research and clinical integration.