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Barriers to Artificial Intelligence Adoption in the Malaysian Virtual Assistant Industry: A Mixed-Methods Study

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
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    References listed on IDEAS

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    1. Ding, Tao & Li, Hao & Liu, Li & Feng, Kui, 2024. "An inquiry into the nexus between artificial intelligence and energy poverty in the light of global evidence," Energy Economics, Elsevier, vol. 136(C).
    2. Chien-Chang Lin & Anna Y. Q. Huang & Stephen J. H. Yang, 2023. "A Review of AI-Driven Conversational Chatbots Implementation Methodologies and Challenges (1999–2022)," Sustainability, MDPI, vol. 15(5), pages 1-13, February.
    3. Muhammad Salar Khan & Hamza Umer & Farhana Faruqe, 2024. "Artificial intelligence for low income countries," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-13, December.
    4. Benjamin Plackett, 2022. "The rural areas missing out on AI opportunities," Nature, Nature, vol. 610(7931), pages 17-17, October.
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