A SWOT analysis of generative AI in applied linguistics: Leveraging strengths, addressing weaknesses, seizing opportunities, and mitigating threats

Abstract

Background The integration of generative Artificial Intelligence (AI), particularly large language models (LLMs) like ChatGPT and Gemini, into the field of applied linguistics presents transformative opportunities alongside notable challenges. This study aims to evaluate the role of AI in applied linguistics through a SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis. Methods Using a sample derived from Scopus and Web of Science, we identified relevant studies by applying specific search terms. Our qualitative research design used the SWOT framework to systematically review and analyse studies, ensuring a robust synthesis of data. Results The results of our SWOT analysis revealed the following: 1) Strengths: Enhanced educational tools and resources through AI-driven personalization and interactive learning, increased efficiency and accessibility in generating educational materials, and innovative research applications leveraging semantic similarity measures and advanced linguistic analyses. 2) Weaknesses: Quality and accuracy concerns in AI-generated content, potential over-dependence on AI tools leading to diminished student creativity and ethical issues, and technical limitations in handling complex academic writing tasks. 3) Opportunities: Potential for educational innovation and pedagogical integration, advancements in AI technology to support linguistic research, and fostering global collaboration and access through AI tools. 4) Threats: Risks to academic integrity due to AI-generated content, technological and implementation challenges, and privacy and security concerns regarding data handling. Conclusions Based on the SWOT analysis, we introduced a strategic plan to maximize strengths and opportunities while addressing weaknesses and threats. The strategy includes promoting personalized learning through AI tools, streamlining the creation of educational materials, fostering innovative research applications, ensuring human oversight to maintain content quality, developing ethical guidelines to prevent misuse, investing in necessary infrastructure and training, and implementing robust data protection measures.