Advances in Social Science and Culture ISSN 2640-9682 (Print) ISSN 2640-9674 (Online) Vol. 7, No. 5, 2025 www.scholink.org/ojs/index.php/assc 49 Original Paper Teaching Adaptation Strategies for Chinese University English Teachers in the AI Era Pingqing Chen1* 1 Hainan Vocational University of Science and Technology, Haikou, Hainan, China * Correspondence author: Pingqing Chen, Hainan Vocational University of Science and Technology, Haikou, Hainan, China Received: July 19, 2025 Accepted: September 12, 2025 Online Published: September 29, 2025 doi:10.22158/assc.v7n5p49 URL: http://dx.doi.org/10.22158/assc.v7n5p49 Abstract The rapid emergence of artificial intelligence (AI) technologies is reshaping language education worldwide, compelling teachers to adapt their pedagogy and professional identities. This article examines how Chinese university English as a Foreign Language (EFL) teachers are adjusting their teaching methods in response to the AI era, drawing on the author’s personal reflective teaching practice in tertiary classrooms. Recent advances in AI-assisted tools—from automated writing evaluation and intelligent feedback systems to AI-generated learning materials and conversational chatbots—offer new opportunities to enhance EFL instruction. Chinese university instructors have begun integrating these tools to provide more personalized writing feedback, facilitate flipped learning, and engage students in novel ways. The reflective findings illustrate how AI integration has improved students’ writing revision and participation, while also challenging teachers to redefine their roles and maintain the human touch in teaching. Through critical engagement with literature from 2020-2025, the article contextualizes these pedagogical shifts within broader trends in AI-mediated language education and the evolving teacher identity in the digital age. It discusses the benefits of AI (such as increased efficiency and learner autonomy) alongside concerns (such as bias, academic integrity, and teacher displacement), emphasizing the need for ongoing professional development and ethical guidance (UNESCO, 2023; Hockly, 2023; Kasneci et al., 2023). The article concludes that AI can enrich EFL teaching in Chinese higher education when used as a complementary tool, with teachers’ reflective adaptation being key to harnessing AI’s potential while safeguarding pedagogical values. Keywords Language education, Chinese university EFL teachers, Higher education (China), Reflective practice, AI-assisted writing evaluation, Intelligent feedback systems, Chatbots for language learning, Flipped www.scholink.org/ojs/index.php/assc Advances in Social Science and Culture Vol. 7 No. 5, 2025 Published by SCHOLINK INC. 50 learning with AI, Personalized feedback & student engagement, Complementary human–AI pedagogy Introduction Artificial intelligence has rapidly become a powerful force in education, with applications ranging from intelligent tutoring systems and automated assessments to adaptive learning platforms (Almashour et al., 2025; Kasneci et al., 2023). In the field of language teaching, AI tools are increasingly prevalent. Educators have noted AI’s ability to act as a conversational partner for students, generate novel ideas for lesson plans, and offer tailored feedback on language use (Minnillo et al., 2024; Hockly, 2023). At the same time, many instructors and scholars voice concerns about AI’s biases and its impact on student learning and academic integrity (Minnillo et al., 2024; UNESCO, 2023). This duality is particularly evident in English as a Foreign Language (EFL) education, where technologies such as grammar-checking algorithms, automated writing evaluators, and chatbots are becoming integral to classroom practice (Almashour et al., 2025; Han & Li, 2024). These innovations promise greater personalization and efficiency in language learning, but they also raise questions about the evolving role of the teacher. In China’s higher education system, the integration of AI into teaching and learning has gained momentum in recent years. Universities are exploring AI-driven language learning apps, intelligent essay-scoring systems, and virtual teaching assistants to support EFL instruction. Chinese university EFL teachers thus find themselves at the forefront of a pedagogical shift, tasked with incorporating advanced technologies into traditionally face-to-face, exam-oriented classrooms. As a result, Chinese EFL educators are experimenting with AI to enhance writing instruction, provide instant feedback, and boost student engagement (Gao & Wang, 2024; Zhou & Hou, 2025). However, adopting AI in the classroom also challenges teachers to update their skills and reconsider their teacher identity in an age where information and guidance are increasingly provided by machines (Pan & Wang, 2025; Qin & Chuaychoowong, 2025). Purpose and Scope: This article investigates how Chinese university EFL teachers are adapting their teaching strategies in the AI era, focusing on practical techniques and the implications for teacher roles. It is based on the author’s reflective teaching practice and situates these experiences within the growing body of literature on AI in language education, EFL pedagogy transformation, and teacher identity in the digital age. By examining both the opportunities and challenges presented by AI, the paper aims to provide insights for language teachers, teacher educators, and researchers interested in the confluence of technology and pedagogy (Feng & Sumettikoon, 2024; Xue, 2024). Literature Review AI in Language Teaching: Opportunities and Challenges The past few years have seen a surge of interest in applying AI technology to language education. A variety of AI applications are now available to assist language learning. For example, AI-powered www.scholink.org/ojs/index.php/assc Advances in Social Science and Culture Vol. 7 No. 5, 2025 Published by SCHOLINK INC. 51 grammar and writing checkers (such as Grammarly and similar tools) offer immediate, individualized feedback on written language, and automated scoring systems can evaluate essays or short answers in seconds (Mekheimer, 2025; Han & Li, 2024). These tools provide instant correction and suggestions, supplementing teachers’ feedback and allowing learners to practice and revise independently. In addition, AI-driven speech recognition and chatbot systems serve as conversation partners for speaking practice, giving students low-pressure opportunities to improve their oral skills. Educators have praised AI’s ability to personalize learning and generate useful instructional content (Minnillo et al., 2024; Hockly, 2023). For instance, generative AI models can quickly produce level-appropriate reading passages or vocabulary exercises tailored to specific topics, which teachers might use to enrich their course materials. However, the integration of AI into teaching also brings new challenges. AI systems are not infallible; they sometimes provide incorrect or biased information, which can mislead learners if not checked (Minnillo et al., 2024; Kasneci et al., 2023). There are concerns about students’ overreliance on AI or misuse of AI tools (for example, using translation engines or text generators to do assignments), which raises issues of academic integrity (Minnillo et al., 2024; UNESCO, 2023). Additionally, the use of AI in the classroom can blur the teacher’s traditional role. If students turn to AI for answers or feedback, the teacher’s authority and control over the learning process may diminish, requiring educators to redefine their value in the classroom context (Almashour et al., 2025). These concerns highlight that while AI offers exciting opportunities, teachers must adapt by developing strategies to ensure AI is used ethically and effectively, and by focusing on what human teachers do best (such as providing mentorship, context, and critical judgment) (UNESCO, 2023; Hockly, 2023). Transformations in EFL Pedagogy with AI AI technologies are also catalyzing broader shifts in EFL pedagogy, encouraging more student-centered and flexible learning formats. One noticeable change is in writing instruction. Automated writing evaluation tools enable students to engage in iterative drafting with immediate feedback on grammar and style. Research has found that EFL students who use AI feedback during writing revision tend to make more improvements and achieve higher writing quality than those who rely on traditional feedback alone (Al Ghaithi & Behforouz, 2023; Han & Li, 2024; Mekheimer, 2025). That said, the presence of the teacher remains vital, as students often need guidance to interpret and apply AI feedback effectively (Mekheimer, 2025; Han & Li, 2024). In practice, this means teachers spend less time on rote error correction and more on higher-level coaching (for example, helping students develop ideas and organization), leveraging AI to handle many lower-order concerns. Another significant innovation is the AI-enhanced flipped classroom. Flipped learning – where students learn new content at home and practice skills in class – can be augmented by AI-generated resources and support. Yavuz et al. (2025) reported that a university course using an AI-supported flipped model saw increased student motivation, more active class participation, and improved personalized learning experiences. AI tools help address common flipped-classroom challenges: adaptive learning platforms www.scholink.org/ojs/index.php/assc Advances in Social Science and Culture Vol. 7 No. 5, 2025 Published by SCHOLINK INC. 52 and chatbots can guide students through pre-class materials by providing personalized content and answering questions on demand, thus better preparing them for in-class activities (Yavuz et al., 2025; Lo & Hew, 2023). By arriving to class with a stronger grasp of foundational knowledge, students can engage in deeper communicative or analytical tasks during the lesson. Nevertheless, teachers implementing flipped models with AI must still carefully design and monitor the process. For instance, they need to verify the accuracy of AI-created materials and ensure student accountability. Some studies note that not all learners consistently engage with pre-class AI activities, showing that student motivation and clear expectations remain crucial (Lo & Hew, 2023; Minnillo et al., 2024). Teacher Identity in the Digital Age The integration of AI into education is prompting a re-examination of teacher identity and professional roles. Recent studies indicate that AI adoption is reshaping teacher identity at multiple levels. Satvati et al. (2025) found that AI integration significantly impacts language teachers’ identity at the micro (classroom), meso (institutional), and macro (societal) levels. At the micro level, teachers who embrace AI often report an enhanced sense of efficacy, as AI tools can relieve them of routine tasks and allow more focus on creative teaching (Zhou, Hashim, & Sulaiman, 2024; Zou & Song, 2025). At the meso level, factors such as institutional support, peer influence, and professional development opportunities shape how teachers adapt to AI (Zhou, Hashim, & Sulaiman, 2024; Lan, 2024). In Zhou et al.’s study, educators with strong support systems and training were more positive about using AI in their practice, whereas a lack of support or understanding from administrators could hinder adoption (Zhou, Hashim, & Sulaiman, 2024). Ethical considerations also come into play at this level (e.g., deciding whether to use AI to detect plagiarism or how to ensure all students have fair access to AI tools) (UNESCO, 2023). Such factors become part of teachers’ professional identity as they develop personal stances on appropriate AI use in education. On a macro-societal level, public discourses about AI and the future of work influence teacher identity. Fears that “AI will replace teachers” can lead to anxiety about job security; however, research shows that engaging with AI through professional development can mitigate these insecurities and even empower teachers (Satvati et al., 2025; Lan, 2024). Many teachers come to see AI as an augmentation of their role rather than a threat. Still, educators emphasize the need to maintain the human qualities of teaching that machines cannot replicate. Empathy, mentorship, cultural understanding, and ethical judgment are facets of teacher identity that become even more salient in the AI era (Almashour et al., 2025; Hockly, 2023). As Almashour et al. (2025) found in Jordan, students appreciate AI’s efficiency but stress the irreplaceable value of teachers’ human connection and understanding. Thus, a key aspect of teacher identity in the digital age is negotiating a balance between embracing innovative AI tools and preserving the human-centric ethos of education. www.scholink.org/ojs/index.php/assc Advances in Social Science and Culture Vol. 7 No. 5, 2025 Published by SCHOLINK INC. 53 Methodology Reflective Practice Approach This study adopts a qualitative reflective practice approach. The author, a Chinese university EFL teacher, systematically examined her own teaching over two semesters (8 months) while integrating various AI tools into her courses. The approach is similar to an autoethnographic teacher-research: the teacher was both practitioner and researcher, using self-reflection to gather insights on pedagogical changes. Data for reflection included weekly teaching journal entries, annotated lesson plans, and informal student feedback (from conversations and end-of-course surveys). After each instructional innovation involving AI, the author recorded observations about student engagement, learning outcomes, and her own role adjustments (Xue, 2024; Sun & Sun, 2025). The teaching context spanned undergraduate EFL courses (e.g., Academic Writing, College English, Business English) with class sizes of about 30 students. Over the reflection period (2023-2024), the teacher gradually implemented four major AI-supported strategies in these classes: (1) using an AI-assisted writing evaluation tool for student essays, (2) providing intelligent feedback via an AI tutoring system, (3) employing AI-generated materials in a flipped classroom model, and (4) engaging students with an English conversation chatbot. Through iterative reflection, recurring themes and lessons were identified regarding how each innovation affected teaching practices and student learning. The author also occasionally consulted with two colleagues who were experimenting with educational AI, which provided additional perspectives and helped validate her interpretations (Liu, Q., Chou, & Feng, 2025; Xue, 2024). The reflective findings are organized by these four key strategies. For each strategy, the author describes how the AI tool was integrated, what changes were observed in the classroom, and how the teacher’s role or sense of professional identity evolved. These practice-based insights are later discussed in light of current research to draw broader implications for EFL teaching in the AI era. Findings from Reflective Practice AI-Assisted Writing Evaluation One of the first adaptations was incorporating AI-assisted writing evaluation into an Academic Writing course. The author introduced an online automated writing evaluation platform that students could use to check their essay drafts before submitting them for grading. Students uploaded their drafts and received detailed feedback from the AI within minutes. The system automatically highlighted grammatical errors, pointed out awkward phrasings, and offered suggestions for improvement (for example, indicating if a sentence was unclear or if a different word choice might make a point stronger). It also provided summary scores on dimensions such as organization and clarity. Armed with this instant feedback, students were able to revise their work before the teacher’s review. The impact of this tool was evident in the quality of student writing. Final drafts showed fewer language errors and better structure compared to previous semesters when students did not have access www.scholink.org/ojs/index.php/assc Advances in Social Science and Culture Vol. 7 No. 5, 2025 Published by SCHOLINK INC. 54 to the AI tool. Students reported that they appreciated the immediate feedback; as one student put it, it was like having a “24/7 editor” to consult while writing. In line with this classroom experience, a study by Al Ghaithi and Behforouz (2023) found that EFL students who received feedback from an AI writing evaluation system made greater writing gains than those who received no automated feedback. Similar benefits are reported when teachers combine AI suggestions with human coaching (Han & Li, 2024; Mekheimer, 2025). The teacher’s reflections, however, highlighted the continued need for human guidance. The AI feedback was purely mechanical and sometimes suggested changes that were stylistically inappropriate or misunderstood the student’s intent. A few students initially followed every AI recommendation blindly, which occasionally led to odd word choices or a loss of the essay’s personal voice. To address this, the teacher guided students on how to critically evaluate the AI’s suggestions. She spent a portion of class time discussing examples of AI feedback, showing which suggestions to accept or reject and explaining the reasoning behind those decisions. This approach aligns with the advice of researchers who stress that AI-generated feedback should be used in conjunction with teacher guidance and student reflection, rather than replacing them (Han & Li, 2024; Mekheimer, 2025). Implementing AI-assisted writing evaluation also influenced the teacher’s role and workload. By delegating the initial round of grammar and spell-checking to the AI, the teacher could devote more time to higher-order feedback on content and organization. In effect, the AI took over some of the labor of error correction, freeing the teacher to act more as a writing coach focusing on ideas and structure. The teacher’s identity in the writing classroom shifted subtly: she became less of a proofreader and more of a mentor guiding students through the revision process—an identity shift widely observed when teachers weave AI into feedback cycles (Han & Li, 2024; Qin & Chuaychoowong, 2025). Intelligent Feedback Systems Another adaptation involved using an AI-driven tutoring system to deliver personalized feedback, particularly for speaking practice. The author integrated a mobile app powered by speech recognition and natural language processing that served as a virtual language coach. Students regularly recorded short spoken responses (e.g., summarizing a news article or giving an opinion on a topic), and the AI system instantly analyzed their speech, providing feedback on pronunciation, intonation, fluency, and word choice. The app also gave each recording a fluency score and highlighted problem areas (for example, specific mispronounced consonants or overly long pauses). This allowed students to receive individualized coaching on their spoken English on a frequent basis, far beyond what the teacher could realistically provide one-on-one in a large class. The impact of this intelligent feedback system was positive. Students appreciated the immediate, private feedback on their speaking. Many reported that practicing with the AI coach helped them become aware of pronunciation mistakes they hadn’t noticed before. For instance, one shy student who was usually reluctant to speak in class found that the app’s gentle corrections and the ability to replay her own speech boosted her confidence; she practiced certain troublesome sounds repeatedly with the www.scholink.org/ojs/index.php/assc Advances in Social Science and Culture Vol. 7 No. 5, 2025 Published by SCHOLINK INC. 55 app and gradually improved. Overall, learners’ pronunciation and fluency showed improvement over the semester, and they grew more willing to participate in face-to-face speaking activities as a result of their practice with the AI—consistent with the broader promise of AI tutors to expand practice opportunities (Kasneci et al., 2023; Wang & Xue, 2024). Despite the benefits, the teacher’s reflections noted some limitations of the AI tutor that required her intervention. The AI’s feedback, while excellent for pronunciation and timing, was less nuanced when evaluating content or grammar. For example, the system might tell a student to “speak more naturally” or “add more details,” but it could not explain how to do so in context—something the teacher later addressed in person. In one case, a student with a strong regional accent consistently received low fluency scores from the app’s algorithm, which affected his motivation. The teacher stepped in to reassure him that the AI was not fully attuned to his accent and to provide a fairer assessment of his progress. This highlighted that AI tools may carry biases or blind spots (in this case, favoring certain accents or speech patterns), and the teacher’s judgment was necessary to interpret the AI’s results appropriately (UNESCO, 2023; Hockly, 2023). Using the intelligent feedback system also changed the teacher’s role in the feedback process. Instead of being the sole provider of feedback, she now acted as a mediator and interpreter of AI-generated feedback. In class, the teacher reviewed common trends from the AI reports (for instance, noting if many students struggled with the same vowel sound) and then tailored her instruction to address those issues. She guided students on how to use the AI feedback to improve—for example, demonstrating in class how to shape a difficult vowel sound that the app flagged. The teacher thus became a coach who combined the AI’s data-driven insights with her own expertise to support each student. This collaboration between teacher and AI meant students received more feedback overall, while still benefiting from the teacher’s human insight (Kasneci et al., 2023; Gao &Wang, 2024). Flipped Learning with AI-Generated Resources The author restructured parts of her course into a flipped classroom model enhanced by AI-generated materials. Instead of introducing new content during class, she used generative AI tools to create pre-class study resources. For one unit on “Technology and Society,” for example, the teacher had an AI produce a short reading passage tailored to her students’ proficiency level and context (including relevant examples), along with a list of key vocabulary and a set of comprehension quiz questions. Students were assigned to read the passage and take the self-check quiz online before coming to class. In the subsequent class session, students arrived with background knowledge and vocabulary already in hand, allowing the teacher to devote class time to deeper discussions, debates, and problem-solving activities on the topic rather than basic explanation. The majority of students completed the AI-generated pre-class tasks; even those who were usually quiet were more willing to participate, having gained some understanding in advance. Class discussions were notably more substantive and interactive. This outcome aligns with findings that AI-supported flipped learning can improve students’ engagement with content and their level of preparation for class (Lo & Hew, 2023; Yavuz et al., 2025). www.scholink.org/ojs/index.php/assc Advances in Social Science and Culture Vol. 7 No. 5, 2025 Published by SCHOLINK INC. 56 Using AI in this way also enabled quick customization of materials. The teacher could tailor content to student interests (for instance, including local or up-to-date examples in the reading) much faster than writing materials from scratch, which potentially increased student motivation. However, the teacher found it crucial to review and edit the AI-generated resources before distribution. She checked the AI-produced passage for accuracy and cultural appropriateness, making minor revisions to ensure the content was correct and suitable. This extra step addressed occasional issues (such as an awkward phrase or a biased statement) in the AI’s output. Ensuring quality control of AI-generated materials became a new part of the teacher’s preparation routine (UNESCO, 2023; Minnillo et al., 2024). Another challenge in the flipped model was holding students accountable for the pre-class work. While most students engaged with the AI materials, a few admitted to skimming or skipping the readings. To reinforce accountability, the teacher began incorporating a brief, graded quiz at the start of class (drawing on the AI-generated questions) and tracking quiz completion online. These measures helped encourage all students to do the necessary preparation (Lo & Hew, 2023). Overall, the AI-enhanced flipped approach transformed the teacher’s role in the classroom. Rather than spending class time lecturing on basic content, she shifted to curating content beforehand and then facilitating active learning activities in class. This demanded more planning before class—finding or generating appropriate materials and designing in-class tasks—but made the class itself more student-centered and participatory. The teacher noted that her planning mindset evolved: she became a designer of learning experiences, using AI as a tool to deliver preliminary input, and then focusing her in-class teaching on guiding application and critical thinking. The result was a more efficient use of class time and a learning experience that students found engaging and tailored to their needs (Yavuz et al., 2025; Gao &Wang, 2024). Student Engagement via Chatbots To further boost student engagement, the author integrated AI chatbots as conversational partners for language practice. Students were encouraged to chat in English with an AI chatbot (similar to ChatGPT) for at least 10 minutes a day on any topic of interest, and to share highlights of these conversations in class. Many students found chatting with an AI to be motivating and low-pressure. One student noted that the chatbot was patient and never “judged” her for grammar mistakes, which made her more willing to practice speaking. Several learners increased their speaking time thanks to this tool, and this extra practice led to observable improvements in their fluency and confidence over the semester. These observations mirror research findings that AI-driven chatbots can significantly foster EFL students’ behavioral, cognitive, and emotional engagement (Wang & Xue, 2024; Hockly, 2023). Students were not only spending more time on task (speaking and writing to the bot), but also exploring new vocabulary and ideas prompted by the AI, and they often came to class excited to discuss their chatbot interactions. The teacher also introduced a chatbot-based virtual assistant on the course’s online forum to handle common queries (e.g., assignment deadlines or technical issues). This 24/7 “TA” chatbot addressed www.scholink.org/ojs/index.php/assc Advances in Social Science and Culture Vol. 7 No. 5, 2025 Published by SCHOLINK INC. 57 routine questions, freeing the teacher to focus on more substantive interactions with students. The convenience of instant answers was appreciated by learners and significantly reduced repetitive emails to the teacher. As with the other AI tools, using chatbots required establishing clear guidelines. A few students initially attempted to misuse the chatbot by asking it to produce homework answers instead of practicing their English. The teacher intervened to set rules for ethical use, emphasizing that the chatbot should be used for practicing conversation, getting explanations, or brainstorming ideas – not for cheating or bypassing learning. This guidance, along with class discussions about the reliability of AI-generated information, helped students use the chatbot constructively. For example, when one chatbot conversation provided a questionable historical “fact,” the class, guided by the teacher, cross-checked and corrected the information. This incident underscored the importance of critical thinking and taught students how to treat AI outputs with healthy skepticism (UNESCO, 2023; Kasneci et al., 2023). Integrating chatbots expanded the learning environment beyond the classroom and the teacher’s direct supervision. Learning became, to some extent, a student–AI partnership, with the teacher acting as a facilitator and coach. She had to trust students to engage with the AI on their own time and guide them in reflecting on those experiences. While this meant ceding a degree of control, it also created more opportunities for autonomous practice. The teacher’s role shifted toward designing the activity and then monitoring and supporting students’ engagement, rather than being present in every interaction. This shift exemplified how teacher roles are evolving in the AI era—from being the sole source of practice to orchestrating diverse learning opportunities (Hockly, 2023; Almashour et al., 2025). Discussion The reflective practices outlined above demonstrate how AI integration is changing the landscape of EFL teaching in the Chinese university context, and they carry several broader implications for pedagogy, teacher identity, and educational policy. A central finding is that AI can greatly augment teaching and learning when used deliberately, but it does not diminish the importance of the teacher—if anything, it recalibrates the teacher’s role. Evolving Teacher Roles: The adoption of AI tools has nudged the teacher from a traditional knowledge transmitter toward a facilitator and manager of learning. Rather than being the sole source of information or feedback, the teacher in these cases orchestrated interactions between students and AI resources, stepping in to guide and correct as needed. This confirms observations in the literature that AI integration tends to shift teachers’ roles toward being coordinators of human–AI collaboration in the classroom (Kasneci et al., 2023; Almashour et al., 2025). Teachers find themselves developing new competencies (e.g., AI literacy) to effectively integrate these technologies. They must exercise professional judgment about when to rely on AI outputs and when to intervene with human insight. In the author’s experience, this meant learning to interpret AI feedback reports, curate AI-generated content, and moderate chatbot use—activities that were not part of language teaching in the past. www.scholink.org/ojs/index.php/assc Advances in Social Science and Culture Vol. 7 No. 5, 2025 Published by SCHOLINK INC. 58 Adapting to these tasks is now becoming part of modern teacher identity (Lan, 2024; Zhou, Hashim, & Sulaiman, 2024). Student Learning and Engagement: The experiences strongly suggest that well-implemented AI tools can enhance student learning outcomes and engagement. Across the different strategies, students wrote more polished essays, practiced speaking more frequently, came to class better prepared, and showed greater enthusiasm for participation. These improvements are borne out by contemporary research—e.g., improved engagement with chatbots (Wang & Xue, 2024) and higher writing performance with AI feedback (Han & Li, 2024; Mekheimer, 2025)—and were evident in the author’s classes. It is important to note, however, that the gains were mostly in areas where AI excels: providing instant feedback, reinforcing practice, and personalizing tasks. Deeper aspects of learning—such as critical thinking, creative expression, and cultural nuance – still required the teacher’s guidance. This aligns with the view that AI works best as a complement to human instruction. The AI can handle repetitive drills, evaluations, and information delivery, while the teacher focuses on higher-order skills, addresses nuances, and keeps students motivated. Teacher Identity and Professional Growth: From the teacher’s perspective, integrating AI was initially accompanied by uncertainty—would it threaten her role or overwhelm her with new tasks? Over time, the reflective practice showed that embracing AI, especially with proper support, can be empowering for teachers. This mirrors findings that engaging with AI through training and reflection can boost teachers’ confidence and alleviate concerns about job insecurity (Satvati et al., 2025; Lan, 2024; Zhou, Hashim, & Sulaiman, 2024). The author found that each successful implementation (be it an AI writing tool or a chatbot activity) reinforced her sense of professional competence and opened up new ways to be effective in the classroom. She evolved to see AI not as a rival but as a valuable assistant, and her professional identity shifted to incorporate being an “AI-enhanced” educator. Crucially, this process was facilitated by collegial support and ongoing learning, including PLC-style collaboration (Xue, 2024) and reflective, self-directed PD (Sun & Sun, 2025; Liu, Q., Chou, & Feng, 2025). Ethical and Practical Considerations: The use of AI in the classroom also brings to light important considerations. Teachers must develop clear policies on academic integrity in the age of AI—for instance, distinguishing between acceptable use of AI for learning versus misuse. In the reflections, setting guidelines for chatbot use was one example of maintaining ethical standards. Similarly, issues of access and equity are relevant: not all students have equal access to devices or reliable internet for using AI tools outside class, so educators and institutions should strive to provide necessary resources or alternatives. Maintaining the Human Touch: Perhaps the most significant insight from this inquiry is that the human dimension of teaching remains irreplaceable, even as AI becomes more prevalent. Students may enjoy interacting with chatbots or benefit from automated feedback, but they still look to their teachers for mentorship, motivation, and meaningful human connection. Recent studies echo that students value www.scholink.org/ojs/index.php/assc Advances in Social Science and Culture Vol. 7 No. 5, 2025 Published by SCHOLINK INC. 59 AI’s efficiency yet emphasize the enduring value of teacher empathy, understanding, and relational engagement (Almashour et al., 2025; Hockly, 2023). In the author’s classes, the introduction of AI did not reduce students’ reliance on the teacher’s guidance; rather, it altered the focus of that guidance. The effective integration of AI actually places greater demand on teachers’ pedagogical discernment, creativity, and emotional intelligence. The reward, as seen in this case, is a richer learning environment where students benefit from the best of both worlds: AI-driven resources and human-driven mentorship. Conclusion As AI technologies become increasingly embedded in education, Chinese university EFL teachers are actively reshaping their pedagogical approaches to integrate these tools in meaningful ways. This article, through a blend of reflective practice and engagement with current research, has detailed several adaptation strategies that illustrate the transformative potential of AI in the language classroom. From automated writing evaluators to intelligent tutoring systems, AI-generated lesson materials, and chatbots, each tool can play a distinct role in enhancing teaching effectiveness and student engagement. The experiences of the author echo a key message from the literature: AI is most powerful as a complement to, not a replacement for, human teachers. By leveraging AI for what it does best—rapid feedback, personalized practice, and data-driven insights – teachers can free themselves to focus on higher-order instruction and mentorship. In the context of Chinese higher education, where EFL instruction often contends with large classes and exam pressures, such augmentation is particularly valuable. The reflective findings showed concrete benefits: improved student writing revisions, more speaking practice, better preparedness for class, and heightened enthusiasm for learning. These outcomes align with emerging research in the 2020–2025 period, reinforcing their validity and offering evidence that AI integration can lead to positive pedagogical change (Qin & Chuaychoowong, 2025; Feng & Sumettikoon, 2024). However, this journey also underscores that successful adaptation requires more than just adopting new tools; it demands a rethinking of teacher identity, continuous professional learning, and attention to ethics. Teachers must navigate the balance between technology and teaching, ensuring that AI’s use is pedagogically sound and aligned with educational values. Ongoing professional development and institutional support are essential so that teachers gain confidence in using AI and share best practices—illustrated by the importance of peer collaboration and targeted training (Xue, 2024; Sun & Sun, 2025; Pan & Wang, 2025). Moreover, maintaining the humanistic core of education is paramount. Qualities like empathy, cultural insight, and inspirational guidance should guide AI’s integration so that the “smart” classroom remains a deeply human space (UNESCO, 2023). In conclusion, Chinese university English teachers in the AI era are not passively being replaced or overwhelmed by technology; instead, many are proactively adapting, leading change in their classrooms through reflective experimentation. Their strategies—from AI-assisted feedback loops to www.scholink.org/ojs/index.php/assc Advances in Social Science and Culture Vol. 7 No. 5, 2025 Published by SCHOLINK INC. 60 flipped AI classrooms and chatbot engagements—demonstrate a path forward for language educators worldwide. These educators are building a new model of EFL teaching that is enhanced by artificial intelligence while firmly grounded in the art of teaching. As AI tools continue to evolve, so too will the strategies and identities of teachers. The insights presented here contribute to an ongoing conversation about that evolution. Ultimately, the teacher’s role remains indispensable: it is the teacher’s expertise, creativity, and humanity that turn AI from a mere tool into a catalyst for deeper learning (Gao & Wang, 2024; Zhou & Hou, 2025). By embracing that synergy, teachers can ensure that the AI era in education fulfills its promise of enriching learning experiences for all. 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