Recent advances in generative artificial intelligence (AI) are transforming the way we learn and design training by integrating it into the practices of teachers and students. However, the effective integration of AI requires considering the limitations of existing frameworks. Despite their effectiveness, traditional models such as ADDIE and SAM have limitations such as restricted customization, long design cycles, and limited flexibility. These barriers make it difficult to use them in dynamic and adaptive educational scenarios. This article proposes a new instructional design model integrating generative AI, resulting from an exploratory survey of instructional designers, teachers, and trainers to identify their interest and readiness for using IA. The insights captured from our survey underscore a significant inclination towards AI-driven automation and emphasize the need for human collaboration and oversight to ensure pedagogical relevance. Our model revisits ADDIE phases by leveraging these results. Key contributions include a structured way to integrate AI in the design process, a human-AI collaboration framework, and iterative evaluation mechanisms. In addition to filling existing gaps in instructional design, this study opens the door for adaptive, AI-enhanced learning experiences. Empirical validation in actual educational environments will be the focus of future research.