  Artificial intelligence (AI) as a disruptive technology is not new. However,
its recent evolution, engineered by technological transformation, big data
analytics, and quantum computing, produces conversational and generative AI
(CGAI/GenAI) and human-like chatbots that disrupt conventional operations and
methods in different fields. This study investigates the scientific landscape
of CGAI and human-chatbot interaction/collaboration and evaluates use cases,
benefits, challenges, and policy implications for multidisciplinary education
and allied industry operations. The publications trend showed that just 4%
(n=75) occurred during 2006-2018, while 2019-2023 experienced astronomical
growth (n=1763 or 96%). The prominent use cases of CGAI (e.g., ChatGPT) for
teaching, learning, and research activities occurred in computer science
[multidisciplinary and AI] (32%), medical/healthcare (17%), engineering (7%),
and business fields (6%). The intellectual structure shows strong collaboration
among eminent multidisciplinary sources in business, Information Systems, and
other areas. The thematic structure of SLP highlights prominent CGAI use cases,
including improved user experience in human-computer interaction, computer
programs/code generation, and systems creation. Widespread CGAI usefulness for
teachers, researchers, and learners includes syllabi/course content generation,
testing aids, and academic writing. The concerns about abuse and misuse
(plagiarism, academic integrity, privacy violations) and issues about
misinformation, danger of self-diagnoses, and patient privacy in
medical/healthcare applications are prominent. Formulating strategies and
policies to address potential CGAI challenges in teaching/learning and practice
are priorities. Developing discipline-based automatic detection of GenAI
contents to check abuse is proposed.
