This work presents a threefold study that investigates the potential use of Gen AI tools in computing education through perspectives from the industry and the academe. Generative AI tools in programming education have shown potential advantages to programming instruction for learners and educators. These tools provide benefits such as assisted problem-solving, code-generation capabilities, assistance in debugging codes, and other programming-related tasks. While integrating these tools in programming education promises conceivable potential, its implementation as an education practice can also pose a challenge to pedagogical design, to answer whether these tools help learning or impede the acquisition of students’ programming skills and knowledge. The study employs mixed-methods data analysis, integrating quantitative and qualitative statistical and data collection procedures. The target participants of this threefold study are industry practitioners, teachers, and students in computing education. Data collection procedures and instruments were developed and tested for use in the study. The experimental research design was employed to investigate the effect of Chat GPT as the Gen AI tool in computer programming tasks among first-year computing students. Our preliminary results show that industry practices fully adopt an AI-based software development workflow to improve developer productivity while teaching methods remain constant using a mix of traditional and innovative methods, which is evident from the teacher-made machine problem sets assigned to students. Student performance has significantly improved with the use of Chat GPT in the experimental study compared to students without the use of Gen AI, which coincides with existing studies.