Call for Papers: Special Issue on Academic Innovation in the Age of AI

IT Professional seeks submissions for this upcoming special issue.
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Submissions Due: 30 October 2025

Important Dates

  • Submission deadline: 30 October 2025
  • Publication date: May/June 2026

AI—especially generative AI (GAI)—is exerting a profoundly disruptive influence on academia. One of the primary reasons is GAI’s ability to produce content that closely mirrors human-authored writing, raising fundamental questions about authorship, originality, and assessment (Howell & Potgieter, 2023). As The Atlantic starkly put it in December 2022, “The College Essay Is Dead,” warning that “Nobody is prepared for how AI will transform academia” (Marche, 2022). Building on GAI’s capabilities, the emergence of AI agents—autonomous systems capable of making decisions and performing tasks—is ushering in a new phase of educational disruption. These agentic AI systems support more personalized, adaptive learning and are poised to reshape how educational content is delivered and managed, especially as part of the rapidly expanding EdTech landscape (Kshetri, 2025).

Academic institutions have responded to GAI tools in widely divergent ways. Some have rushed to integrate these technologies into their curricula, often without fully considering their pedagogical, ethical, and assessment implications. Others have adopted a more measured approach, experimenting with GAI to better understand its impact on teaching and learning. In contrast, a number of institutions have taken restrictive stances, implementing outright bans on these tools due to concerns about academic integrity and misuse.

The rise of AI agents presents new challenges for colleges. For example, AI agents could automate tasks like identifying and submitting missing assignments through learning management systems (LMS), potentially diminishing active student engagement. As these technologies continue to advance, higher education institutions (HEIs) will need to rethink course design and the fundamental purpose of education to ensure that learning remains meaningful and impactful in an AI-driven era (Gulya, 2024).

Amid these controversies, the rapid adoption of generative AI in higher education is fundamentally reshaping both how students learn and how institutions approach assessment. According to the Digital Education Council’s 2024 survey, 86% of students across 16 countries reported using AI in their academic work (Riddell, 2024).

Academic institutions and educators have adopted varied responses to generative and agentic AI. Many call for clear policies and stricter assessments, with some considering a return to oral exams (Hart & Mok, 2023). To address AI-assisted assignment completion, teachers increasingly require personal engagement and in-class work (UCLA, 2024) and have intensified in-person assignments and exams (Hussain, 2024).

Debates over the ethical use of GAI in education are divided. Critics highlight concerns about academic dishonesty and plagiarism (Kshetri, 2024), while others argue that restricting GAI use is unrealistic, comparing it to banning calculators or the Internet (Cjr, 2023). Governments and international bodies also warn of risks such as privacy breaches, algorithmic bias, digital inequality, and threats to educational integrity (Australian Human Rights Commission, 2003). UNESCO urges widespread AI literacy to reduce digital divides (UNESCO, 2021), and the European Commission calls for ethical frameworks to ensure compliance with data protection and intellectual property laws (European Commission, 2024).

In light of the above observations, this special issue aims to critically examine the multifaceted impact of generative and agentic AI on higher education. It seeks to explore how these technologies are reshaping teaching, learning, and assessment practices, while addressing the ethical, pedagogical, and policy challenges that institutions face. By bringing together diverse perspectives, empirical research, and theoretical insights, the issue will highlight innovative responses from academia, propose frameworks for responsible AI integration, and encourage dialogue on safeguarding educational integrity and equity in an AI-driven future.

Topics of interest include, but are not limited to:

  1. Ethical implications of generative AI use in academic settings
  2. AI and academic integrity: challenges and solutions
  3. The role of AI agents in personalized and adaptive learning
  4. Revisiting assessment methods in the era of AI-assisted learning
  5. Policy development for AI integration in higher education
  6. Addressing algorithmic bias and digital inequality in AI-powered education
  7. AI literacy and education: preparing students and educators
  8. The impact of AI on student engagement and participation
  9. Pedagogical innovations driven by generative AI tools
  10. Governance and regulation of AI technologies in academic institutions
  11. AI agents and agentic AI on teaching and operations

Submission Guidelines

Only submissions that describe previously unpublished, contemporary research and practice that are not currently under review by a conference, or another journal will be considered. Extended versions of conference papers must be at least 30 percent different from the original conference works. Feature articles should be no longer than 4,200 words and have no more than 20 references (with tables and figures counting as 300 words each). Articles should be understandable by a broad audience of computer science and engineering professionals, avoiding unnecessary theory, mathematics, jargon, or abstract concepts. For author guidelines, see the Author Information page.

All manuscripts must be submitted to the Authors Portal by the deadline, making sure that the specific Special Issue is selected in order to be considered for publication under this Call for Papers. Submissions are subject to peer review on both technical merit and relevance to IT Professional’s readership.

The use of artificial intelligence (AI)–generated text in an article should be disclosed in the acknowledgements section, while the sections of the paper that present AI-generated text verbatim should be quoted within quotation marks and provide a citation to the AI system used to generate the text.

IT Professional magazine is a hybrid publication, allowing either traditional manuscript submission or author-paid Open Access manuscript submission.

In addition to submitting your paper to IT Professional, you are also encouraged to upload the data related to your paper to IEEE DataPort. IEEE DataPort is IEEE’s data platform that supports the storage and publishing of datasets while also providing access to thousands of research datasets. Uploading your dataset to IEEE DataPort will strengthen your paper and will support research reproducibility. Your paper and the dataset can be linked, providing a good opportunity for you to increase the number of citations you receive. Data can be uploaded to IEEE DataPort prior to submitting your paper or concurrent with the paper submission.

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