This study examined the effectiveness of an artificial intelligence (AI)–based instructional design course on academic self-efficacy, achievement motivation, and self-regulated learning among students at Islamic Azad University, Azadshahr Branch. The research was applied in purpose and employed a quasi-experimental pretest–posttest design with a control group. The population comprised undergraduate students in Educational Sciences and related majors enrolled in the instructional design course. Sixty students were selected through multistage cluster sampling and randomly assigned to an experimental group (AI-based instructional design) or a control group (conventional instructional design). Measures included an Academic Self-Efficacy Questionnaire, Hermans’ Achievement Motivation Questionnaire, and the Self-Regulated Learning Questionnaire by Bouffard and colleagues. Data were analyzed using descriptive statistics and analysis of covariance (ANCOVA). After controlling for pretest scores, the experimental group achieved significantly higher posttest means in academic self-efficacy, achievement motivation, and self-regulated learning than the control group, and the instructional approach accounted for a substantial share of variance in all three outcomes. Accordingly, completing the AI-based course strengthened students’ beliefs in their academic capabilities, increased their motivation to strive for success, and enhanced key self-regulation processes such as planning, monitoring, and self-evaluation. Limitations include sampling from a single university branch, a limited time frame, and reliance on self-report data, which warrants cautious generalization. Practically, teacher education and educational science programs are encouraged to redesign instructional design courses by integrating AI tools in a structured manner across syllabi, assignments, and assessment. Emphasizing responsible AI use to build academic human capital, the study aligns with SDG 4 (Quality Education) and SDG 9 (Industry, Innovation and Infrastructure).