Author
Listed:
- Nurul Aisyah Kamrozzaman.
(UNITAR International University, Kelana Jaya, Malaysia)
- Siti Aishah Sabtu.
(UNITAR International University, Kelana Jaya, Malaysia)
- Amy Liew Xiu Jie
(UNITAR International University, Kelana Jaya, Malaysia)
- Noor Sahirah Md Nayan
(Universiti Teknologi MARA, Shah Alam, Malaysia)
Abstract
As Malaysia’s digital economy evolves, there is a growing imperative for virtual assistants (VAs) to embrace artificial intelligence (AI) tools to augment service delivery and enhance professional competitiveness. Nevertheless, considerable obstacles persist especially in rural and underserved areas stemming from infrastructural deficiencies, financial limitations, and disparities in digital literacy. This mixed-methods investigation examines the obstacles encountered by Malaysian VAs in the integration of AI, with a specific focus on initiatives spearheaded by the Malaysia Digital Economy Corporation (MDEC), including the GOT Program. Data were gathered from 40 virtual assistants through both surveys and semi-structured interviews, incorporating perspectives from participants across urban and rural settings. The results indicate a heterogeneous adoption of AI, despite the acknowledged advantages of technologies such as chatbots, natural language processing systems, and predictive analytics. Principal challenges comprise affordability concerns, restricted exposure, language barriers, and apprehensions regarding job displacement. Evaluations conducted post-intervention revealed significant advancements in AI familiarity, frequency of usage, and user confidence, thereby underscoring the beneficial effects of targeted training initiatives. The study emphasizes the necessity for localized, inclusive, and culturally pertinent training programs, alongside equitable infrastructural development and supportive policy frameworks. By addressing the digital divide, this research enhances both theoretical comprehension and practical policymaking aimed at promoting inclusive AI integration within Malaysia’s freelance economy. The findings advocate for ongoing cross-sectoral collaboration to ensure that AI adoption is conducted in an ethical, accessible, and empowering manner particularly for marginalized and rural-based virtual assistants.
Suggested Citation
Nurul Aisyah Kamrozzaman. & Siti Aishah Sabtu. & Amy Liew Xiu Jie & Noor Sahirah Md Nayan, 2025.
"Barriers to Artificial Intelligence Adoption in the Malaysian Virtual Assistant Industry: A Mixed-Methods Study,"
International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 9(5), pages 3722-3732, May.
Handle:
RePEc:bcp:journl:v:9:y:2025:issue-5:p:3722-3732
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bcp:journl:v:9:y:2025:issue-5:p:3722-3732. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Dr. Pawan Verma (email available below). General contact details of provider: https://rsisinternational.org/journals/ijriss/ .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.