Grounded in the Resource-Based View, this paper proposes that talent readiness, financial access and change management shape expected business outcomes from AI. It outlines Pearson and partial-correlation tests for a target sample of 150 Hong Kong SMEs and defines transformational, incremental, futile and stagnant pathways. The report is a theoretical model and analysis plan, not completed empirical validation, so its relationships should be treated as hypotheses.
Key findings
- The model centers on talent, finance and change-management readiness. • It distinguishes four AI-adoption pathways. • No observed results from the proposed 150-SME sample are reported.
Why this matters globally
Its value is a readiness-first decision framework, but it should not yet be used to predict returns or set policy without empirical testing.
Thai researcher contribution
An author linked to North Bangkok University and Bangkok University brings Thai academic participation to the Hong Kong SME digital-adoption question.
Limitations to consider
This is a proposed model rather than a completed survey; outcomes are expected rather than observed, and Hong Kong-specific assumptions may not transfer directly.