Language disorders following stroke, neurodegeneration, or altered neurodevelopment markedly impair communication and quality of life. Despite advances in behavioural and neuromodulation therapies, treatment outcomes remain modest. Attempts to modulate local excitability in single brain regions have yielded limited benefits. We argue for a shift in neuromodulation for language, from interventions that target isolated regions to approaches that modulate distributed neural networks. To support this shift, we introduce the Interacting Language Network (ILN), a theoretical framework that integrates evidence for local functional specialisation with evidence for distributed processing. The ILN extends existing models by formalising how dynamic interaction between sensorimotor and heteromodal language circuits enables flexible communication. The ILN is grounded in evolutionary, neurobiological and clinical work showing that complex language abilities depend on the disproportionate expansion of association cortices and white matter pathways in humans, which enable long range communication between specialised regions. Converging findings from neurotypical and clinical populations demonstrate that although specific regions make distinct contributions to language, their function depends critically on dynamic interactions, particularly between frontal and temporo-parietal areas. The ILN delineates current knowledge about the architecture and interaction principles of the language network, identifies important gaps that impede progress, and outlines concrete avenues to advance network-based neuromodulation for language disorders. Ultimately, targeting interacting language networks rather than isolated regions holds the potential to deliver more effective and personalised treatments for individuals with language impairment.