The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Exploring Cloud-Based AI Music Tools and Their Implications for IT and Multimedia Professionals
Abstract
Cloud-based artificial intelligence (AI) music tools have rapidly evolved into scalable, production-ready systems embedded within cloud-native infrastructures, fundamentally reshaping multimedia workflows and digital content ecosystems. Leveraging transformer-based architectures, diffusion models, and distributed GPU-enabled environments, these platforms generate full-length musical compositions from minimal prompts and parameter controls. Despite growing commercial adoption, limited empirical research has examined their professional and technological implications for Information Technology (IT) and multimedia practitioners. This study investigates the architectural foundations, workflow transformation dynamics, ethical risk perceptions, and competency requirements associated with cloud-based AI music systems. Using a mixed-method descriptive-correlational design, data were collected from 184 IT and multimedia professionals across academic and industry sectors to examine AI literacy, adoption intention, ethical concern, and workflow integration patterns.
Related Content
|
Randy Joy Magno Ventayen, Elmar B. Noche, Maricel Aqui.
© 2026.
34 pages.
|
|
Evren Idil Yazan.
© 2026.
30 pages.
|
|
Sonia Ahuja.
© 2026.
24 pages.
|
|
Saroj Sandeep Phalke, Gitanjali Shinde, Grishma Bobhate, Poonam Railkar, Haribhau R. Bhapkar, Sonal Fatangare.
© 2026.
28 pages.
|
|
Syrenzo Ramos Sicuan.
© 2026.
26 pages.
|
|
K. S. Jishnu, P. S. Shijukumar, G. Bhargavi, Vimal Sankar, P. S. Sujith Kumar, Nisha Thorakattu Madathil.
© 2026.
30 pages.
|
|
Vibha Tiwari, Rahul Lalwani, Akshada Telang.
© 2026.
36 pages.
|
|
|