Enhancing SME Financial Accuracy through Prompt Engineering Services to Address Manual Recording Challenges (Phenomenological Study)

The majority of Indonesian Small to Medium Enterprises (SMEs) still remain on using manual financial recording despite digital tools being widespread and available to access, resulting in hindered efficiency and data inaccuracies. AI technology are currently on the rise, creating new jobs on tuning AI to fit individual needs. Earlier studies predominantly focuses on AI adoption in large enterprises, overlooking prompt engineering potentials as a bridge on smaller enterprise digitalization. This research gaps are addressed through this research by studying the lived experiences and operational workflows of seven Small to Medium Enterprise (SME) owners and accountant to identify resistance factors and adoption perquisites through a phenomenological approach. High AI enthusiasm and low technical readiness are revealed in this research, currently 70% of the participants uses manual/hybrid recording. The research also reveal that tiered prompt engineering service monetization to be crucial, it helps improving financial accuracy by 27.3% and predictability by 34.5%. This research shows scalable monetization processes that match high-level computational intelligence with technical and resource-based limitations of emerging economies, therefore supporting SDG 8 and SDG 9.