Many AI Adoption initiatives fail due to unrealistic expectations, inadequate data, and lack of scalability. Companies often neglect proper training and governance, leading to project inefficiencies. To fix this, businesses must set clear objectives, invest in robust AI models, and ensure cross-functional collaboration. Continuous evaluation and ethical AI use are key to avoiding failure. By addressing these obstacles, organizations can turn AI Adoption into a long-term success.