Integrating AI into existing systems presents various challenges, including compatibility, data quality, and security issues. Organizations must ensure that AI technologies can effectively communicate with legacy systems, which may require significant modifications. Additionally, the performance of AI depends on the quality and volume of data used for training, necessitating robust data governance strategies. There are also concerns surrounding privacy and ethical implications, as AI systems may unintentionally perpetuate biases if not carefully monitored. Addressing these challenges is critical for successful AI adoption and realization of its full benefits.