Adoption of AI technology in food industry of Pakistan

Authors

  • Muhammad Mubeen IQRA University, Karachi
  • Muhammad Fawad Azeem IUBS, IQRA University, Karachi
  • Sadaf Baloch IUBS, IQRA University, Karachi, Pakistan
  • Muniba Munir IUBS, IQRA University, Karachi, Pakistan
  • Adeebah Shah IUBS, IQRA University, Karachi, Pakistan
  • Adeebah Shah IUBS, IQRA University, Karachi, Pakistan

DOI:

https://doi.org/10.54554/jhcd.2025.18.2.9

Abstract

Artificial Intelligence (AI) is rapidly reshaping industries by automating processes, optimizing decision-making, and creating opportunities for efficiency and innovation. In emerging markets such as Pakistan, the dairy sector faces rising competitive pressures, changing consumer demands, and increasing operational complexity. This study evaluates the readiness of employees at Millac Foods Pakistan, a leading dairy manufacturer, to adopt AI technologies in their daily work. A quantitative research design was employed, using stratified sampling to collect survey responses from 70 employees across multiple departments. Findings indicate that while employees demonstrate openness to AI adoption, significant gaps remain in awareness, technical skills, and practical usage. Approximately half of the respondents expressed interest in AI-related training, though only 1% reported regular use of AI tools. Major barriers included lack of time and limited understanding of AI applications. Despite these challenges, strong willingness for departmental training, combined with support for peer-led “AI Champion” models, reflects a cautiously positive readiness profile. This study contributes to the growing discourse on digital transformation in emerging economies by highlighting workforce-level challenges and opportunities in the dairy sector.

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Published

2025-12-31

How to Cite

Mubeen, M. ., Muhammad Fawad Azeem, Baloch, S., Munir, M., Shah, A., & Shah, A. (2025). Adoption of AI technology in food industry of Pakistan. Journal of Human Capital Development (JHCD), 18(2), 116–125. https://doi.org/10.54554/jhcd.2025.18.2.9

Issue

Section

ARTICLES