Artificial intelligence (AI) offers significant potential to advance implementation science (IS) by addressing key challenges such as speed, sustainability, equity, generalizability, context-outcome relationships, and causality. However, its use also raises concerns about unintended consequences, including biases, inequities, and the need for ethical and transparent application. This paper explores how AI can complement IS methods, providing examples from global health, public health, and precision health. It highlights opportunities for AI to enhance data collection, analysis, and decision-making while emphasizing the importance of transdisciplinary collaboration to ensure ethical and effective use. AI can accelerate knowledge generation and translation, improve equity through culturally sensitive tools, and support sustainable healthcare systems. However, AI's potential to exacerbate existing inequities and its reliance on biased data require careful monitoring. The paper also discusses the need for regulations, frameworks, and proactive monitoring to address AI's unintended consequences. Recommendations include building representative teams, using AI responsibly, and ensuring transparency in AI applications. Overall, AI has the potential to transform IS, but its integration must be guided by ethical considerations and a commitment to equity and sustainability.Artificial intelligence (AI) offers significant potential to advance implementation science (IS) by addressing key challenges such as speed, sustainability, equity, generalizability, context-outcome relationships, and causality. However, its use also raises concerns about unintended consequences, including biases, inequities, and the need for ethical and transparent application. This paper explores how AI can complement IS methods, providing examples from global health, public health, and precision health. It highlights opportunities for AI to enhance data collection, analysis, and decision-making while emphasizing the importance of transdisciplinary collaboration to ensure ethical and effective use. AI can accelerate knowledge generation and translation, improve equity through culturally sensitive tools, and support sustainable healthcare systems. However, AI's potential to exacerbate existing inequities and its reliance on biased data require careful monitoring. The paper also discusses the need for regulations, frameworks, and proactive monitoring to address AI's unintended consequences. Recommendations include building representative teams, using AI responsibly, and ensuring transparency in AI applications. Overall, AI has the potential to transform IS, but its integration must be guided by ethical considerations and a commitment to equity and sustainability.