Study of the impact of integrating generative AI technology with ERP systems on automatic report generation and demand forecasting: A case study of manufacturing industry in Bangkok and Metropolitan Area

This study aimed 1) to develop a prototype system for automated report generation and demand forecasting that integrates Generative AI with the Odoo ERP platform via n8n, 2) to assess user acceptance before and after system use based on the UTAUT framework, 3) to analyze differences across all five UTAUT dimensions—PE, EE, SI, FC, and BI, and 4) to identify factors influencing users’ intention to adopt the system after real-world implementation. The research employed a quantitative quasi-experimental design using a Pre– Post One Group approach. The sample consisted of 30 participants selected through purposive sampling, limited to Odoo ERP users who were responsible for producing or utilizing operational reports. The research instruments included the AI–ERP prototype and a UTAUT questionnaire validated by domain experts. The reliability coefficients were 0.906 (pre-use) and 0.850 (post-use). Data were analyzed using descriptive statistics, paired t-tests, and Cohen’s d effect sizes, processed with the jamovi software. The findings revealed statistically significant increases in all dimensions after system use (p < .05). FC (d = –0.959) and BI (d = –1.074) demonstrated the largest effect sizes. The negative values of Cohen’s d resulted from the formula using “pre minus post” means, indicating that post-use scores were substantially higher. These results show that the system effectively reduced repetitive tasks, improved workflow speed, and strongly enhanced both user acceptance and intention to continue using the system in the future.