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Objectives To identify structural and systemic barriers to pathology education in low- and middle-income countries (LMICs), evaluate emerging digital and AI-driven solutions and develop consensus-based frameworks for sustainable diagnostic capacity building.Design Expert consensus-based synthesis. Qualitative synthesis of inaugural Global Pathology and Laboratory Medicine Consortium (GPALMC) summit proceedings using facilitated deliberative consensus, transcript-based thematic analysis with artificial intelligence (AI)-assisted synthesis and human oversight, triangulated with a scoping literature review.Setting University of Michigan, Ann Arbor, USA.Participants 20 multidisciplinary experts from eight countries spanning sub-Saharan Africa, North Africa, the Middle East, Latin America and North America, including pathologists, surgeons, public health officials and medical educators.Main outcome measures Identification of critical gaps in pathology training; refinement of the Residency in a Box cloud-based model with four LMIC-specific prerequisites, development of five interdependent strategic axes and policy recommendations on workforce retention, digital infrastructure and governance.Results Nearly 47% of the global population lacks access to essential diagnostics. Primary barriers include brain drain, infrastructure deficits and curricula misaligned with local disease burdens. Digital pathology and AI offer transformative potential but are hindered by high costs of ownership and a lack of diverse training datasets. Models from Ghana, Rwanda, India, Ethiopia and Nigeria confirm sustainable progress requires government ownership, phased implementation and integrated governance.Conclusions Scaling global pathology education requires a shift from donor-dependent aid towards nationally owned health system strengthening. The GPALMC framework integrates cloud-based training, bidirectional mentorship, contextualised curricula and diversified financing to close the diagnostic gap and advance health equity.