@inproceedings{0a4b9987fed04cb790c271b79cef98c8,
title = "The four business models for AI adoption in education: Giving leaders a destination for the digital transformation journey",
abstract = "Effective digital transformation requires new technology to work in harmony with the people towards a common goal. All the universities do not have the same capabilities currently across these three parameters and may not be able, or willing, to develop them in the same way. Therefore, several alternative models conducive to digital transformation and AI adoption must be identified. A university must not have to go on this journey without a roadmap. There should be several education business models that optimize AI adoption to choose from. Identifying the destination in advance reinforces the trust between the digital transformation leader and the followers. This research identifies four education business models that are optimized for AI. The first is focus and disaggregate. The second is to keep the existing model but enhance it with AI. The third is an educator expanding beyond their current model and the fourth is a disruptor entering education.",
keywords = "artificial intelligence, business model, digital transformation, education",
author = "Alex Zarifis and Leonidas Efthymiou",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 13th IEEE Global Engineering Education Conference, EDUCON 2022 ; Conference date: 28-03-2022 Through 31-03-2022",
year = "2022",
doi = "10.1109/EDUCON52537.2022.9766687",
language = "English",
series = "IEEE Global Engineering Education Conference, EDUCON",
publisher = "IEEE Computer Society",
pages = "1868--1872",
editor = "Mohammed Jemni and Ilhem Kallel and Abdeljalil Akkari",
booktitle = "Proceedings of the 2022 IEEE Global Engineering Education Conference, EDUCON 2022",
address = "United States",
}