1 Introduction

Rapid developments in artificial intelligence, including in generative artificial intelligence, have overturned existing practices and models in translation, and will continue to shape the industry in the future. In times when human expertise was not fully exploited, translation could be left to humans, or, at best, assistants. However, the rise in influence of artificial intelligence in language is changing the game. Today, translation companies tout their machine translation (MT) systems, developed on neural machine translation (NMT) frameworks, which can translate almost any text, almost instantly. While artificial intelligence can indeed translate with impressive feats of linguistic effectiveness, it cannot handle complex, jargon-filled, or context-sensitive content. With the advent of AI, the space for human translators to manoeuvre will forever be different: they will now need to be proofreaders, editors, and managers of AI. Curricula in the field of translation must, in turn, adapt and reevaluate their existing teaching methods. The new generation of students must be taught skills that were only marginally considered before. Traditional curricula trained translators for the human tasks of translation, emphasising proficiency in learning one or more languages and cultural competency. However, updated curricula must now include technical skills, critical thinking, and ethical awareness. We discuss in this paper which skills are essential in the new curriculum, and how we can teach those skills to future generations of translators [1]. By offering courses of study that build AI literacy, institutions will produce graduates that are employable now and into the future, and ensure the continued relevance of the human role in translation.

2 Revising Translation Curricula for the AI Era

2.1 Revising Translation Curricula for the AI Era

Alongside copyright concerns, the greatest immediate challenge posed by generative AI to the translation industry is the pervasive use of machine translation tools. As impressive as AI has become at delivering fast translations, the results are often far from consistent, depending on the language pair being used, on the complexity of the text, and on the subject matter. The demand for human translators to post-edit AI-generated translations to make them accurate, coherent and culturally appropriate will remain acute. Teaching students how to properly post-edit machine translation requires a different skill set to the one needed on an everyday basis by human translators. That requires an understanding of what it means to communicate effectively in human-sounding text, which goes beyond correcting mistakes to encompass improving the flow and making sure that the final translation does what the text is meant to do. In many cases, this involves making judgment calls on stylistic choices and appropriateness in specific contexts, which are areas in which machines obviously underperform [2]. Courses on post-editing can therefore be introduced into translation degrees to prepare students for work in a domain that genuinely works with AI rather than being displaced by it.

2.2 Developing Proficiency in AI Tools

Second, they should experience hands-on use of the AI tools that are now part and parcel of the translation profession. In addition to conventional CAT tools, translation software now includes complex AI-driven platforms that can automate entire chunks of the translator’s workflow. These usually incorporate machine-learning algorithms that are ‘trained’ to improve over time through human feedback. Given the importance of this type of tool in the future translation profession, students should learn how the tools work, when and how to make the most of them, and how to train them to produce better results. Training modules in higher-ed should focus on the practical use of AI-powered translation tools, explaining how these tools work, what their strengths and weaknesses are, how to use them with confidence and how to critically evaluate the quality of AI-generated texts [3]. Students should therefore develop technical skills that will allow them to ‘work together’ with AI tools as part of the translation process, harnessing the power of technology to boost productivity while maintaining high standards of quality. Figure 1 showcases the flexibility and broad compatibility of a tool like Transit, which works with numerous file types essential for the translation process.

Figure 1. A Comprehensive AI Translation System Supporting Multiple File Formats (Source:star-spain.com)

2.3 Enhancing Multidisciplinary Knowledge

A second major curricular reform to embrace is the expansion of students’ expertise beyond language and culture. Perhaps the most crucial shift in the AI translation era is for translators to work in niche areas, including legal, medical and technical translations. Unlike general contents that can be translated by AI tools, specialised texts with highly technical subjects and professional jargon require subject area knowledge. Skilled translators must read widely and become familiar with the specific domain in order to write in the voice of an expert. This is a crucial feature distinguishing human translators from AI systems [4]. Universities should encourage students to acquire cross-disciplinary knowledge in domain areas that intersect with translation, such as law, medicine or engineering. Students can take elective courses or interdisciplinary minors in order to become more competitive in niche translation markets where AI tools alone cannot produce the nuanced and accurate translations needed. Not only is this an effective measure to increase employability, but it also helps students further position themselves as human experts in areas where human translators are irreplaceable.

3 Prioritizing Skills in the AI-Driven Translation Industry

3.1 Critical Thinking and Problem Solving

While the presentation of numerous visual elements and repetitive tasks can be automated, AI lacks the capacity for critical thinking or the creative skills needed to solve complex problems. Thus, in the AI era, critical thinking is perhaps the most important skill that translators should possess. On top of having the linguistic skills to understand the source texts and the technical know-how to operate an AI system, translation professionals need to be able to diagnose the limitations of AI-generated translations and think about how they might be improved. This demands not only linguistic expertise but also the capacity for reflective and analytical thinking. [5] As such, educational programmes should include a range of case studies, real-world translation problems and collaborative tasks that challenge students to critically evaluate AI outputs and to make informed decisions on how to modify them. In this way, institutions can better prepare graduates to meet the cognitive demands of working with AI systems where human judgment is vital in order to ensure translation accuracy and effectiveness. Table 1 demonstrates real-world case studies where AI-generated translations were the initial output for professional translation projects, but that required critical thinking and human post-editing to resolve key issues and produce the best possible output.

Table 1. Case Study for Critical Thinking in Translation

3.2 Ethical Decision-Making

The introduction of AI into the field of translation raises many ethical concerns such as data privacy issues, intellectual property issues, and issues such as translations containing biased or harmful content. The more an AI system is trained on data, the more likely it is that such a system will translate in a way that propagates biases present in its training dataset. Educational institutions should thus teach ethics within their translation curricula and teach students to recognise and address these issues. [6] Courses on AI ethics should include the topics of algorithmic bias, the responsibilities of human translators to ensure fairness of translations, and the legal implications of using AI-generated translations in professional settings. Institutions should thus foster students’ ethical awareness of the moral landscape they will face when working within an industry that encompasses AI technology.

3.3 Soft Skills for Collaboration

These soft skills – communication, adaptability, teamwork – will become even more valuable as AI becomes more prevalent in the translation industry. Translators will increasingly work in multidisciplinary teams alongside engineers, data scientists and project managers to fulfil their translation tasks. Translators’ soft skills will be crucial for their ability to communicate with and collaborate with colleagues from diverse professional backgrounds. Universities and other educational establishments emphasise the need to develop students’ soft skills through group projects, internships and other collaborative learning environments. If institutions foreground the importance of teamwork and cross-functional collaboration, they set students up for success in workplaces where AI is yet a part of a wider, more integrated translation process [7]. Soft skills are essential for translators’ continued flexibility, which will help them continue to serve as a valuable part of an increasingly automated industry.

4 The Role of Institutions in Supporting AI-Driven Translation Education

4.1 Updating Course Content Regularly

The fast-paced nature of AI development means that educational institutions must continuously update their course content to stay relevant. AI tools, algorithms, and translation technologies are constantly evolving, and the skills required to work with these tools will change accordingly. Translation programs should, therefore, establish mechanisms for regularly reviewing and revising their curricula, incorporating the latest advancements in AI and translation technology [8]. This could involve partnerships with technology companies, industry experts, and AI researchers to ensure that students are learning the most up-to-date practices. By staying current, institutions can provide their students with a competitive edge in a job market increasingly shaped by technological innovation.

4.2 Providing Access to AI Resources

In addition to revising curricula, educational institutions must ensure that students have access to the tools and resources necessary to engage with AI technology. This could include providing licenses to AI-powered translation software, creating AI research labs, or offering workshops on machine learning and natural language processing. Institutions should also encourage students to participate in internships or cooperative education programs that expose them to real-world applications of AI in translation [9]. By giving students the opportunity to work with AI tools in practical settings, institutions can bridge the gap between theoretical knowledge and practical skills, better preparing students for the workforce.

4.3 Supporting Research on AI and Translation

Another important role of institutions is to support research initiatives that explore the intersection of AI and translation. Faculty and students should be encouraged to conduct research on topics such as improving AI translation algorithms, mitigating biases in AI-generated translations, and developing best practices for integrating AI into translation workflows. By fostering a research-oriented environment, institutions can contribute to the advancement of AI technologies while also ensuring that students are at the forefront of innovation in the translation field. Research grants, conferences, and collaborative projects with industry partners can further enhance the institution’s role in shaping the future of translation education in the AI era [10].

5 Conclusion

As AI continues to evolve and embed itself in the translation industry, educational institutions bear the responsibility of adapting their curricula to prepare students for this technological shift. By prioritizing skills such as post-editing machine translations, fostering technical proficiency in AI tools, and enhancing cross-disciplinary knowledge, educational programs can ensure that graduates are equipped to work alongside AI rather than being displaced by it. Furthermore, by emphasizing the development of critical thinking, ethical decision-making, and soft skills such as collaboration, institutions can nurture a new generation of translators who are adaptable, thoughtful, and capable of navigating the complex challenges posed by AI. This revised approach to translation education is not just a response to the current technological trends but an investment in the future of the profession, ensuring that human translators continue to play a vital role in delivering high-quality, culturally sensitive translations in an AI-enhanced world. Institutions must act proactively to integrate these changes, shaping the future of translation in ways that balance technological progress with the irreplaceable value of human insight and creativity.