This study aimed to explore the impact of utilizing deep learning technology in developing intelligent software for teaching Arabic to non-native speakers. An experimental methodology was employed, involving two groups (experimental and control) with both pre-tests and post-tests. The sample consisted of 30 Arabic learners who are non-native speakers at the Arabic Language Teaching Institute in collaboration with the German Board, divided equally between the two groups. The control group received traditional instruction, while the experimental group was taught using software based on deep learning technology. The instrument of the study was a test that assessed the four Arabic language skills (listening, speaking, reading, and writing). Results indicated statistically significant differences between the mean scores of the two groups in the post-test, favouring the experimental group across all language skills. This suggests the effectiveness of using deep learning technology in developing intelligent software for teaching Arabic to non-native speakers. The study recommends the adoption of this technology in Arabic language education programs and suggests further research to refine these programs and identify their strengths and weaknesses.