AI-Driven Educational Transformation in Higher Education: A Review of Current Practices

Shivani Negi

doi:10.36948/ijfmr.2026.v08i04.85224

AI-Driven Educational Transformation in Higher Education: A Review of Current Practices

Author(s)	Ms. Shivani Negi
Country	India
Abstract	Despite the fact that artificial intelligence has already gained ground in higher education systems, especially in the field of online learning, it is important not to mistake its development for actual transformation. In this section, we will show that AI is rapidly gaining a foothold in teaching, learning, and online learning. To verify the hypothesis concerning the positive impact of the use of AI in class, we will review the empirical data from the authoritative institution Paper, a test conducted in the course of professional training, positive results achieved through intelligent tutoring, learning analytics and automatic feedback, and supportive arguments regarding the answer in the view of prepared arguments. In comparing these statistics, there have been 45,398 students and faculty respondents from 35 countries surveyed for the Digital Education Council (DEC) in the 2026 survey, 1,054 UK undergraduate students included in the 2026-HEPI survey, 400 higher education respondents responding from 90 countries surveyed by UNESCO in 2025, and 1,681 faculty included from 28 countries in the 2025 DEC-WG Faculty survey. Among the findings is an asymmetry of transformation: AI deployment activities are commonly observed; however, only 15% of students claim integration in many subjects, and only 29% rated their classroom teachers very highly in terms of abilities in guiding AI use, and only 28% rated most or many of the assessments as being appropriate to the use of AI in the workplace. An experiment within a physics course has validated that effective AI tutoring structures can be more effective than rudimentary active learning, but it has also been shown that most other AI classroom applications are primarily incidental and only indirectly related to educational design. It further argues that changes that last over time, or sustainable change, require coherent improvement of teaching, assessment, educator capabilities, leadership, and equity objectives and offers the ALIGN framework (Access, Learning design, Integrity, Governance, and new capabilities) as an evidence-based institutional implementation model.
Keywords	generative AI; higher education; educational transformation; intelligent tutoring; assessment; faculty readiness; AI literacy; academic integrity
Field	Sociology > Education
Published In	Volume 8, Issue 4, July-August 2026
Published On	2026-08-06
DOI	https://doi.org/10.36948/ijfmr.2026.v08i04.85224

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AI-Driven Educational Transformation in Higher Education: A Review of Current Practices

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