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Article . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2026
License: CC BY
Data sources: Datacite
ZENODO
Article . 2026
License: CC BY
Data sources: Datacite
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Faculty and Student Readiness for AI Adoption in MBA Education: An Empirical Study at ASM Group of Institutes

Authors: Professor Swapna Roy; Professor Priti Puri;

Faculty and Student Readiness for AI Adoption in MBA Education: An Empirical Study at ASM Group of Institutes

Abstract

Artificial Intelligence (AI) is reshaping management education by transforming teaching methodologies, assessment systems, research practices, and administrative processes. In alignment with ASM AI Fest 2026 and the theme "AI-Driven Pedagogy & Institutional Transformation," this study examines the readiness of faculty and students for AI adoption in MBA education at ASM Group of Institutes. The research evaluates awareness levels, perceived usefulness, technological competence, institutional preparedness, and willingness to integrate AI tools into academic and administrative functions.Using a mixed-method approach, primary data were collected from MBA faculty members and students through structured questionnaires, while secondary data were gathered from global reports, AICTE guidelines, NEP 2020, and international case studies on AI in education. The findings reveal high conceptual awareness of AI tools such as ChatGPT, Grammarly, Canva AI, and data analytics platforms; however, structured implementation strategies, formal training, and policy frameworks are still evolving. The study proposes a phased implementation plan including faculty training, pilot classroom integration, AI-supported assessment tools, and process automation in academic administration. The research concludes that AI readiness at ASM is promising but requires strategic alignment, capacity building, and responsible AI governance to create a future-ready academic ecosystem in MBA education.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green