Optimization of English Translation Strategies in the Age of Artificial Intelligence

Abstract

The rapid development of artificial intelligence technology has profoundly changed the practical mode and theoretical paradigm of English translation. This study focuses on the optimization path of English translation strategies in the context of the AI era. The article first systematically analyzes the fundamental changes brought by AI technologies such as neural machine translation and large language models to the translation field and the accompanying core challenges, pointing out that the reshaping of human-machine relationship and quality ethical risks are the key issues at present. Then, through the comparison of traditional and modern translation strategies and the empirical analysis of existing AI-assisted strategies, it reveals the boundaries and limitations of technical efficacy. On this basis, the study proposes a dynamic hierarchical integrated AI translation strategy innovation framework and elaborates on the specific optimization implementation methods from tools, processes to skills. The research shows that the future direction of translation strategy optimization lies in building a human-machine collaborative system led by the translator’s strategic thinking and empowered by AI as a deep-enabling tool, through differentiated and refi ned task division and process design, so as to achieve comprehensive improvement in quality, efficiency and cross-cultural communication effects.