Andrew William Green, Ph.D.

Andrew W. (Andy) Green, Ph.D., is an Assistant Professor of Information Security and Assurance in the Department of Information Systems and Security at the Michael J. Coles College of Business at Kennesaw State University. He directs the KSU Cyber Range at Coles College and serves as the faculty advisor for the Orthodox Christian Fellowship (OCF) Club at KSU. Green also chairs the Parish Cybersecurity Committee of the Greek Orthodox Archdiocese of America.

Before transitioning to full-time academia, Green spent more than twenty years in cybersecurity. His experience includes cybersecurity and IT consulting for small- to mid-sized businesses, as well as earlier work in healthcare IT, where he developed and supported transcription interfaces used by medical facilities across the U.S.

Green’s academic research examines the connections between information security, privacy, and public policy. His work has appeared in leading peer-reviewed journals, and he has co-authored several textbooks used in university courses worldwide. He also provides expert analysis and commentary on cybersecurity for various media outlets.

He currently serves as President-Elect of the Special Interest Group on Information Security and Privacy (SIGSEC) within the Association for Information Systems (AIS), an international association of information systems scholars that named him a Distinguished Member in 2025.

latest posts

Mar 13, 2026	Georgia Senate Bill 568 fails — again, we wait
Mar 27, 2025	Is Georgia moving to hand-marked paper ballots for elections?
Mar 26, 2025	What does ChatGPT Know about Information Systems?” accepted for publication at the Communications of the AIS
Apr 27, 2024	To report or not to report? Extending Protection Motivation Theory to Vulnerability Discovery and Disclosure” accepted for publication at Computers & Security
Feb 10, 2023	Importing OVA into Amazon AWS

selected publications

JIT
Unpacking digital transformation – Constructing a framework based on industry use cases

Khawaja Asjad Saeed, Andrew William Green, and Alison Brooke Hedrick

Journal of Innovation & Knowledge, Jul 2025

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Based on industry use cases, we identify six distinct types of digital transformation (DT), each grounded in a specific concept or enabling technology. These DT types can be implemented individually or combined to drive transformation initiatives. While deploying a single DT type often focuses on improving operational efficiency or streamlining existing workflows, initiatives that combine multiple DT types tend to pursue more ambitious goals, such as the creation of new products, services, or business models. However, the complexity increases signifi cantly with the integration of multiple DT types, as organizations must not only address behavioral changes but also overcome technical challenges involving systems integration, data architecture, and interoperability.
@article{2025digitaltransformation, title = {Unpacking digital transformation – Constructing a framework based on industry use cases}, author = {Saeed, Khawaja Asjad and Green, Andrew William and Hedrick, Alison Brooke}, journal = {Journal of Innovation & Knowledge}, volume = {10}, issue = {5}, pages = {1-12}, year = {2025}, month = jul, day = {25}, doi = {10.1016/j.jik.2025.100759}, publisher = {Elsevier}, issn = {2444-569X}, url = {https://doi.org/10.1016/j.jik.2025.100759}, }
CAIS
What does ChatGPT Know about Information Systems?

Daniel E. O’Leary, Aaron M. French, Veda C. Storey, and 8 more authors

Communications of the Association for Information Systems, Apr 2025

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Large language models such as ChatGPT provide efficient access to a wealth of information. However, there are significant questions regarding the depth and quality of knowledge in any one domain. This paper focuses specifically on the information systems (IS) field and assesses ChatGPT’s knowledge. To analyze the extent and quality of information systems knowledge derived from queries to ChatGPT, we used over 3,000 queries from a broad range of exam and quiz questions. These queries were obtained from university courses and professional information system certification exams. The query topics are based on a framework for information systems education, with queries gathered from multiple faculty members at different universities. The results of querying ChatGPT with these questions find that ChatGPT can answer 65% to 85% of information systems queries successfully, across each of the areas of the framework. ChatGPT performed well on essay, true/false and multiple choice questions, with no statistical difference between its success rate on multiple choice and true/false questions. We conclude that ChatGPT tends to perform approximately at the level of an average student, but may not perform at a level sufficient to pass certain professional exams. ChatGPT’s knowledge is very broad, covering virtually all areas of the information systems knowledge we identified, but not at an expert level.
@article{2025chatgpt, title = {What does ChatGPT Know about Information Systems?}, author = {O'Leary, Daniel E. and French, Aaron M. and Storey, Veda C. and Buckman, Joseph. R. and Chua, Cecil and Green, Andrew William and Gu, Grace and Niederman, Fred and Pereira, Francis and Templeton, Gary and Wallace, Linda}, journal = {Communications of the Association for Information Systems}, volume = {56}, number = {19}, pages = {461-482}, year = {2025}, month = apr, doi = {10.17705/1CAIS.05619}, publisher = {Association for Information Systems}, issn = {1529-3181}, url = {https://doi.org/10.17705/1CAIS.05619}, }