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Teaching GenAI Readiness: Secure AI Adoption for Small Businesses

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Generative Artificial Intelligence (GenAI) is reshaping business operations across industries, enabling new efficiencies in automation, decision support, and cybersecurity. However, small and medium-sized enterprises (SMEs) often lack the technical expertise, financial resources, and implementation support needed to adopt GenAI effectively. At the same time, undergraduate Information Technology (IT) programs tend to focus on enterprise-scale AI development, creating a gap in preparing graduates to support GenAI deployment in small business contexts. This paper presents a curriculum proposal informed primarily by a literature review, supported by a Pennsylvania-based SME needs assessment survey to examine GenAI adoption challenges and identify key curriculum gaps. The model proposed is anchored in applied AI literacy, cybersecurity, ethical governance, and experiential engagement with small businesses. The model aligns with national workforce initiatives such as NICE and NSA CAE, helping to prepare IT graduates to bridge the AI readiness gap and drive local innovation through secure and practical GenAI adoption.

Original languageEnglish (US)
Title of host publicationACM SIGCITE 2025 - Proceedings of the 26th ACM Annual Conference on Cybersecurity and Information Technology Education
PublisherAssociation for Computing Machinery, Inc
Pages101-106
Number of pages6
ISBN (Electronic)9798400722400
DOIs
StatePublished - Dec 27 2025
Event26th ACM Annual Conference on Cybersecurity and Information Technology Education, ACM SIGCITE 2025 - Sacramento, United States
Duration: Nov 6 2025Nov 8 2025

Publication series

NameACM SIGCITE 2025 - Proceedings of the 26th ACM Annual Conference on Cybersecurity and Information Technology Education

Conference

Conference26th ACM Annual Conference on Cybersecurity and Information Technology Education, ACM SIGCITE 2025
Country/TerritoryUnited States
CitySacramento
Period11/6/2511/8/25

All Science Journal Classification (ASJC) codes

  • Education
  • Law
  • Artificial Intelligence
  • Computer Graphics and Computer-Aided Design

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