ARTIFICIAL INTELLIGENCE AND EMPLOYEE PRODUCTIVITY IN MALAYSIA: A DOI-BASED CONCEPTUAL FRAMEWORK
DOI:
https://doi.org/10.55197/qjssh.v7si4.1587Keywords:
technology adoption, digital transformation, diffusion of innovation theory, organizational performance, innovation characteristicsAbstract
Corporate Malaysians are embracing AI tools rapidly; however, this conceptual paper argues that the translation of these technologies into measurable employee productivity remains underexplored. This research aims to examine this disconnection through Rogers’ Diffusion of Innovation theory. The framework incorporates five innovation characteristics, namely relative advantage, compatibility, complexity, trialability and observability. According to our framework, productivity gains from AI will depend on how workers assess the benefits of the technology and whether it is aligned, as well as whether its benefits are visible in practice rather than automatic. This research incorporates AI adoption and usage to mediate between the aforementioned perceptions and productivity. Although previous studies have examined AI adoption and performance outcomes, the mechanism linking innovation characteristics with employee productivity remains insufficiently explained, particularly in the Malaysian context. To narrow the gap in the Malaysian context, this research will shift from initial acceptance to actual work results. In doing so, the study extends DOI beyond behavioural acceptance by positioning AI adoption and usage as the mechanism connecting innovation characteristics with employee productivity. Managers and policymakers planning AI rollouts can take guidance from it. We close the study with a series of propositions that can be tested in future empirical research.
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