Generative Artificial Intelligence (GAI) is an emerging technology increasingly adopted in organizational management due to its accessibility, ease of use, and ability to generate human-like, creative outputs. While its rapid diffusion across sectors is noteworthy, it also raises critical concerns that require in-depth examination. In our study, we try to explore the principal challenges that GAI can bring, and how these difficulties can stop or block some organizational strategies. We divided the problems into four groups: technical limits, practical obstacles, ethical dilemmas, and strategic risks. The technical ones are related to the way the AI works and how it depends on past data to make new things. The obstacles are more about integration, it needs special skills, and people inside the organization don’t always accept the change. Then, we talk about the ethical part, where we find problems like protection of data, responsibilities, copyrights, laws, and also the energy that these models consume. Finally, there are strategic risks that we must consider seriously, like the decisions that are wrong or unfair, the manipulation of information, the growing competition, the loss of human competences, and the inequalities that GAI can make bigger. In our analysis, we try to look critically at all these issues. We also propose some ideas to adopt GAI in a better way, including more training for workers, clear ethical rules, and always keeping human supervision. Our conclusion is that cooperation between all actors is necessary to make standards, give support, and help organizations to use GAI in a responsible and safe way.