Precision agriculture increasingly relies on data-driven technologies that demand visual interaction with digital interfaces, creating significant barriers for visually impaired farmers who constitute a vulnerable and underserved population in agricultural communities worldwide. Voice-activated artificial intelligence assistants offer transformative potential to bridge this accessibility gap by enabling hands-free, eyes-free interaction with farm management systems through natural speech interfaces. This review examines the current state of voice-activated AI technologies specifically designed to support visually impaired farmers in real-time agricultural decision-making. We analyze core speech recognition architectures, natural language processing algorithms, and multimodal sensor integration strategies that enable these systems to deliver actionable guidance on crop management, irrigation scheduling, pest detection, weather monitoring, and market information access. Key applications include voice-controlled precision irrigation systems, conversational interfaces for disease diagnostics, and audio-based advisory platforms for resource optimization. Despite promising field deployments demonstrating improved farm productivity and independence for visually impaired users, significant challenges remain regarding ambient noise robustness, low-latency processing in resource-constrained environments, multilingual support for diverse farming communities, and equitable technology access in rural settings. Future development must prioritize inclusive design principles, offline functionality, and culturally appropriate interaction models to ensure voice-activated AI assistants become genuinely transformative tools for empowering visually impaired farmers in the evolving landscape of precision agriculture.