This study addresses the lack of structured frameworks to guide the ethical and pedagogical integration of Generative Artificial Intelligence (GAI), with a specific focus on ChatGPT, in engineering education and corporate training contexts. Through a mixed-methods approach—including a systematic literature review, comparative analysis of existing GAI applications, and empirical fieldwork involving 114 participants in Argentina and Colombia—the research identifies both benefits and challenges associated with GAI adoption. While ChatGPT fosters accessibility, user engagement, and cognitive assistance, it also introduces concerns regarding algorithmic bias, misinformation, and over-reliance, amid limited regulatory oversight (Fu and Weng in Comput Educ Artif Intell 7, 2024 [7];Kong and Yang in IEEE Trans Learn Technol 17:1588–1599, 2024 [9]). The internal consistency of the research instrument, confirmed through Cronbach’s Alpha (α = 0.63), supports its reliability for exploratory use. Based on the findings, a Human-Centered Design (HCD) framework is proposed, encompassing five interrelated principles: ethical governance, pedagogical adaptability, human-AI collaboration, bias mitigation, and sustainability. This model aims to enable inclusive and context-sensitive adoption, particularly in educational and training environments with limited digital infrastructure (Yang et al. in Guest editorial: Human-centered AI in education: augment human intelligence with machine intelligence. Educ Technol Soc 26(1):95–98, 2023 [15]).