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A qualitative design uses semi-structured interviews with 17 accounting instructors from UK universities to identify thematic patterns. Findings indicate GenAI raises ethical issues including academic misconduct, overreliance, accuracy and bias, transparency and information privacy. Educators recommend strategic AI integration in teaching, AI-friendly assessments, updated policies, and AI literacy training for staff and students.",{"@graph":69,"@context":126},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/academic-integrity-is-under-fire-in-the-generative-ai-age-insights-from-accounting-educators-to-overcome-challenges-threats-and-ethical-concerns/639672/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/academic-integrity-is-under-fire-in-the-generative-ai-age-insights-from-accounting-educators-to-overcome-challenges-threats-and-ethical-concerns/639672.png","ImageObject",300,407,{"name":92,"@type":93},"Jake","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-31","2026-10-22",true,{"@type":102,"interactionType":103,"userInteractionCount":24},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118,122],{"name":109,"@type":110,"acceptedAnswer":111},"What is the study’s main purpose regarding Generative AI and academic integrity?","Question",{"text":112,"@type":113},"To examine the challenges and threats Generative AI creates for academic integrity, and to gather insights from accounting educators on how to overcome those challenges.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How was data collected in the study?",{"text":117,"@type":113},"The research used a qualitative approach with semi-structured interviews involving 17 accounting instructors from different UK universities.",{"name":119,"@type":110,"acceptedAnswer":120},"What ethical issues and threats did the findings identify?",{"text":121,"@type":113},"The results highlight ethical concerns such as academic misconduct, overreliance, accuracy and bias, transparency and information privacy risks, plus fabricated or inaccurate outputs.",{"name":123,"@type":110,"acceptedAnswer":124},"What recommendations do academics make to ensure ethical and effective use of GenAI in education?",{"text":125,"@type":113},"They emphasize strategic incorporation of AI in teaching, new forms of assessment, clear academic policies, and AI literacy training for both students and faculty, alongside AI-friendly tools supporting higher-order thinking.","https://schema.org",{"og:url":83,"og:type":128,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":130,"canonical":83},"index,follow",{"doc_id":132,"site_id":62},639672,1793149020,{"code":4,"msg":5,"data":135},{"doc_id":132,"user_id":136,"nickname":92,"user_avatar":137,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":138,"file_id":139,"file_url":140,"file_type":141,"file_size":142,"view_count":24,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":56,"language":143,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":144,"faqs":145,"seo_title":146,"seo_description":67,"update_tm":147,"read_time":148},962084928904,"https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d","Academic integrity is under fire in the Generative AI age: insights from accounting educators to overcome challenges, threatsand ethical concerns  \nKrayyem Al-Hajaya  \nDepartment of Accounting, Business School, Mutah University, Mu’tah, Jordan  \nAbstract  \nPurpose – This study investigates the challenges and threats of Generative AI to academic integrity as well as seeks to gain insights from accounting educators to overcome the challenges identified.  \nDesign/methodology/approach – The research methodology followed a qualitative approach. This involved the use of semi-structured interviews among 17 accounting instructors from different UK universities. This method allowed for the extraction of thematic patterns related to the factors mentioned above.  \nFindings – The results suggest that GenAI hold many ethical issues and concerns like academic misconduct, overreliance, accuracy and bias, transparency and information privacy, which should be addressed. To ensure ethical and effective use, academics highlight the importance of the strategic incorporation of AI in teaching, new forms of assessment, academic policies concerning AI use, besides AI literacy training.  \nPractical implications – The findings from this research provide actionable recommendations to educators, higher education institutions and policymakers. Among the actions that should be taken in universities are AI guidelines, clear polices and regularity framework. Furthermore, this may include the dissemination of AI literacy among the students and faculty members, as well as the implementation of training programs for AI. Apart from this, the use of assessment tools for the support of higher-order thinking that are AI-friendly should also be considered.  \nOriginality/value–This research makes a contribution to the existing body of knowledge related to AI in higher education in general and accounting education specifically in the area of exploring the views of educators on the issues of academic integrity, ethics in the digital age and AI-based teaching methodologies. This research offers a very important perspective to the debate related to the inclusion of AI in higher education.  \nKeywords Generative AI in higher education, Academic integrity, AI misuse, AI ethics, AI threats, Accounting education  \nPaper type Research article  \n1. Introduction  \nThe applications of Generative AI (GenAI) in higher education highlight its potential to offer multiple advantages to the educational environment. The positive impact of GenAI can be seen in enhanced teaching and learning approaches, improved learning outcomes, greater global access to quality education and increased time and cost efficiency, among other benefits (Jiao, 2024) . Intelligent tutoring features and personalized learning experiences provided by GenAI can help bolster learning outcomes, particularly for students in underserved and underrepresented communities. The scalability and outreach of AI enable students from both developed and developing countries to benefit equally from improved learning experiences (Wood and Moss, 2024) .  \nDespite the benefits that GenAI offers to the educational environment – where it can be ethically employed as a complementary learning aid for brainstorming, clarifying complex materials and supporting technical tasks when properly acknowledged and not used as a substitute for human effort (Wood et al., 2023; Choi et al., 2023; Ballantine et al., 2024)–its unethical use nevertheless poses significant threats and challenges. The ethical concerns associated with GenAI include academic misconduct, such as inaccuracy, dishonesty, cheating and plagiarism (Chan and Hu, 2023; Sweeney, 2023; Dakakni et al., 2023; Ballantine et al., 2024). Consequently, there are  \nHigher Education, Skills and WorkBased Learning  \n237  \nReceived 17 February 2025 Revised 23 September 2025  \n1 November 2025 Accepted 2 November 2025  \nHigher Education, Skills and Work  \nBased Learning Vol. 16 No. 1, 2026 pp","cbCaikqPIsFIdv6p","https://ap.wps.com/l/cbCaikqPIsFIdv6p","pdf",499567,"English","# Introduction\n## Academic integrity challenges from GenAI\n# Methodology and approach\n## Semi-structured interviews with accounting instructors\n# Findings and ethical concerns\n## Academic misconduct, bias, privacy and transparency\n# Practical implications\n## AI guidelines, policies, and AI literacy training\n# Originality and value","[{\"question\":\"What is the study’s main purpose regarding Generative AI and academic integrity?\",\"answer\":\"To examine the challenges and threats Generative AI creates for academic integrity, and to gather insights from accounting educators on how to overcome those challenges.\"},{\"question\":\"How was data collected in the study?\",\"answer\":\"The research used a qualitative approach with semi-structured interviews involving 17 accounting instructors from different UK universities.\"},{\"question\":\"What ethical issues and threats did the findings identify?\",\"answer\":\"The results highlight ethical concerns such as academic misconduct, overreliance, accuracy and bias, transparency and information privacy risks, plus fabricated or inaccurate outputs.\"},{\"question\":\"What recommendations do academics make to ensure ethical and effective use of GenAI in education?\",\"answer\":\"They emphasize strategic incorporation of AI in teaching, new forms of assessment, clear academic policies, and AI literacy training for both students and faculty, alongside AI-friendly tools supporting higher-order thinking.\"}]","Academic integrity is under fire in the Generative AI age - insights from accounting educators to overcome challenges, threats and ethical concerns | PDF",1792704876,48]