Training as corridor governance: TVET alignment, skills recognition, and status continuity in the Myanmar–Malaysia labour migration system

South–South labour migration is increasingly central to development trajectories, yet corridor governance often operates under fragmented mandates and uneven implementation capacity. In such corridors, mandatory pre-departure training is delivered late, generically, and with weak assessment—limiting its ability to shape recruitment choices, reduce intermediation dependence, or support safe navigation after arrival. Anchored in the Myanmar–Malaysia corridor, this conceptual analysis argues that training governance is amongst the most implementable cross-level levers for improving regularity and rights-protecting mobility in capacity- and coordination-constrained South–South systems, because it can be redesigned through standards, timing, delivery architecture, and recognition/portability arrangements without waiting for slower reforms in enforcement or permit regimes. Using on a structured desk review, corridor process mapping, and governance gap analysis, the paper reframes training as migration-governance infrastructure that can function as (i) a capability intervention (actionable navigation, contract comprehension, safe help-seeking), (ii) a labour-market signal shaped by technical and vocational education and training (TVET) alignment and human capital planning, and (iii) a gatekeeping node when access, assessment, and accountability are weak. We develop three testable propositions linking training design to corridor outcomes: (1) earlier, decentralised access reduces information asymmetry and reliance on brokers; (2) TVET alignment and portable skills recognition enable training to translate into labour-market value and mobility options; and (3) rights-based effectiveness requires measurable capability outcomes and follow-through institutional supports beyond information transfer. Here, “skills recognition” refers primarily to functional, employer-usable verification and portability of assessed competencies (e.g., micro-credentials), rather than formal mutual recognition. Generative AI is treated as bounded inclusion infrastructure for multilingual, low-bandwidth learning support—useful for reducing language and resource distance but governed through content validation, transparency, data minimisation, and human accountability to prevent digital gatekeeping. AI is not proposed for eligibility screening, risk scoring, or automated decision-making; its role is limited to multilingual learning support under auditable safeguards. The paper concludes with a sequenced policy toolkit for specifying “who does what” across corridor actors and an empirical agenda for testing the propositions in South–South mobility settings. To clarify what recognition/portability can mean without assuming legal unification, the paper draws on EU qualification-translation, QA, and transparency instruments as a transferable tool-layer.