Global spotlight editorial: Advancing treatment planning to promote equity through AI and automation in clinical medical physics

Journal of Applied Clinical Medical Physics (JACMP) is introducing a new editorial series titled Global Spotlight Editorial, aiming to highlight experts from different countries around the world, identified from the pool of top reviewers, authors, or editorial contributors for the journal. In each feature, a critical topic will be determined by the editors, and invited experts will share their professional viewpoints in an interview dialogue format. Invited experts from diverse regions and practice settings will share their professional milestones and contributions to advancing the field of patient care. This series aims to humanize the global medical physics community and inspire collaboration across borders. The first topic addressed in this editorial is “Advancing treatment planning to promote equity through Artificial Intelligence (AI) and automation.” AI deep-learning models are being developed and deployed for automated contouring and treatment planning in Radiation Oncology departments globally. However, alongside these technological advances lies a critical global challenge: ensuring that innovation translates into equitable access to high-quality radiotherapy worldwide.1 While high-resource centers are increasingly adopting AI-driven solutions, many institutions, particularly in low- and middle-income countries (LMICs) and regions affected by conflict, continue to face significant barriers, including limited infrastructure, workforce shortages, and restricted access to modern technologies.2, 3 In this context, AI and automation represent not only technological evolution but also a potential pathway to reduce disparities by standardizing workflows, improving efficiency, and supporting workforce capacity.4 At the same time, there is a risk that unequal access to advanced tools, data, and expertise could further widen the gap between well-resourced and under-resourced settings. The responsible development and implementation of AI in medical physics, therefore, requires careful consideration of scalability, validation, accessibility, and training, ensuring that these innovations are both clinically effective and globally inclusive.5 In this Global Spotlight editorial for the JACMP, we invited three internationally recognized medical physicists, Dr. Laurence Court (United States), Dr. Jianrong Dai (China), and Dr. Stefania Pallotta (Italy), to share their perspectives on the evolving role of AI and treatment planning automation in clinical practice. These experts represent diverse healthcare systems and bring complementary expertise in treatment planning, imaging, and clinical implementation of advanced technologies.