<![CDATA[Rapid advances in neural machine translation, large language models, and speech-to-speech systems have renewed predictions that professional translators and interpreters will soon become obsolete. This conceptual paper examines whether artificial intelligence (AI) is likely to replace human language professionals between 2026 and 2036. It integrates research on translation technology, human-parity evaluation, interpreting, labour-market change, professional standards, and AI governance. The analysis separates occupation-level replacement from task-level automation and written translation from real-time interpreting. It develops a risk–routinization framework in which the suitability of AI-led, hybrid, or human-led provision depends on task predictability and the severity and reversibility of error. Four propositions follow: routine and measurable tasks are most susceptible to substitution; requirements for human oversight increase with communicative consequence; interpreting retains greater human dependence because of interactional complexity; and professional value shifts from text production toward verification, orchestration, and accountability. The paper argues that AI will absorb a substantial share of repetitive, low-risk, high-volume work and will intensify price and productivity pressures. However, it is unlikely to eliminate translation and interpreting as professions by 2036. Human expertise will remain most defensible in low-resource, culturally embedded, interactive, confidential, and high-consequence contexts. The decisive question is therefore not whether humans or machines translate better in the abstract, but how responsibility should be distributed within human-AI language-service systems.]]>
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