AI in customer service is revolutionizing customer interactions by automating routine tasks, enhancing response times, and personalizing experiences through technologies like voice agents, real-time agent assistance, and predictive analytics. By 2026, AI is expected to transform customer service with six key use cases, including self-service voice agents that handle entire conversations, and predictive analytics that anticipate customer needs. These technologies rely on advanced speech-to-text processing, natural language processing, and integration with existing business systems to provide accurate and context-aware responses. Real-time agent assistance supports customer service representatives by suggesting responses and providing relevant information during calls, while automated quality monitoring ensures compliance and highlights areas for improvement. Intent and sentiment analysis allows companies to proactively address customer issues by detecting patterns and customer emotions. The success of AI in customer service depends heavily on the accuracy of underlying Voice AI models, such as AssemblyAI's Universal-Streaming speech-to-text model, which ensures precise transcription of critical details. The implementation of AI solutions requires careful planning, starting with high-volume, routine tasks to ensure customer satisfaction and operational efficiency, while gradually expanding capabilities.