Artificial intelligence (AI), particularly generative AI, has the potential to combat vaccine hesitancy by building trust in vaccines. However, it must be used ethically and responsibly. Vaccine hesitancy is a complex issue influenced by sociocultural, political, and psychological factors, and misinformation can significantly impact public health. Traditional public health approaches often struggle to keep up with the rapid spread of misinformation, especially during crises like the COVID-19 pandemic. AI can help identify and counter misinformation by analyzing text against a knowledge base of verified facts. Large language models (LLMs) can detect emotionally charged language and provide insights into vaccine acceptance or reluctance. AI can also generate content, including text and images, and analyze data quickly to understand hesitancy topics and trends. This enables the development of targeted interventions, such as data-driven chatbots that provide health information. However, AI has risks, including the potential to generate misinformation and amplify emotional drivers of hesitancy, such as anger and fear. The development of AI tools must balance accuracy, transparency, and ethical considerations. AI's ability to replicate human-like content can risk reproducing biases and misinformation, especially around sensitive issues like vaccine acceptance. AI's adaptability in health communication extends beyond message generation, allowing for customization according to specific demographics. This capability is particularly useful in tackling vaccine hesitancy, where the underlying reasons for reluctance can vary among different populations. The integration of AI into public health programs requires a commitment to ethical principles, transparency, and the augmentation of human expertise rather than replacement. Only through this holistic approach can AI fully unlock its capacity to navigate the complexities of emotions and misinformation and build vaccine confidence to advance public health.Artificial intelligence (AI), particularly generative AI, has the potential to combat vaccine hesitancy by building trust in vaccines. However, it must be used ethically and responsibly. Vaccine hesitancy is a complex issue influenced by sociocultural, political, and psychological factors, and misinformation can significantly impact public health. Traditional public health approaches often struggle to keep up with the rapid spread of misinformation, especially during crises like the COVID-19 pandemic. AI can help identify and counter misinformation by analyzing text against a knowledge base of verified facts. Large language models (LLMs) can detect emotionally charged language and provide insights into vaccine acceptance or reluctance. AI can also generate content, including text and images, and analyze data quickly to understand hesitancy topics and trends. This enables the development of targeted interventions, such as data-driven chatbots that provide health information. However, AI has risks, including the potential to generate misinformation and amplify emotional drivers of hesitancy, such as anger and fear. The development of AI tools must balance accuracy, transparency, and ethical considerations. AI's ability to replicate human-like content can risk reproducing biases and misinformation, especially around sensitive issues like vaccine acceptance. AI's adaptability in health communication extends beyond message generation, allowing for customization according to specific demographics. This capability is particularly useful in tackling vaccine hesitancy, where the underlying reasons for reluctance can vary among different populations. The integration of AI into public health programs requires a commitment to ethical principles, transparency, and the augmentation of human expertise rather than replacement. Only through this holistic approach can AI fully unlock its capacity to navigate the complexities of emotions and misinformation and build vaccine confidence to advance public health.