Rapid adoption of artificial intelligence (AI) tools for breast cancer screening may lead to unintended consequences such as algorithmic bias, increased rates of false positives or false negatives, and a lack of transparency in decision-making. Algorithmic bias can result in disparities in screening outcomes for certain demographic groups, potentially exacerbating existing health inequities. Moreover, overreliance on AI tools without proper validation and oversight can compromise patient safety and trust in the healthcare system. To mitigate these risks, it is essential to prioritize the development of AI algorithms that are transparent, interpretable, and regularly audited for bias. Healthcare providers should undergo training to understand the limitations and capabilities of AI tools, ensuring they are used as decision support rather than decision-making tools. Additionally, ongoing monitoring and evaluation of AI systems in real-world clinical settings can help identify and address any unintended consequences promptly.