Voice AI assistants and automation platforms combine speech-to-text, large language models, and text-to-speech to create voice-first agents that handle customer interactions, routine tasks, and multi-step workflows. This topic covers personal and enterprise assistants, automation platforms, voice synthesis and transcription, and conversation‑intelligence tools that together move voice from a novelty to an operational channel in 2025. Relevance and timing: advances in high‑quality TTS and voice cloning, more efficient open models for on‑premise use, and stronger enterprise requirements for governance and observability have accelerated deployments across contact centers, field services, and internal help desks. At the same time, regulators and customers demand clearer privacy controls and provenance for synthetic voice, making observability and compliance central design considerations. Key tools and roles: PolyAI focuses on voice‑first conversational agents for enterprise contact centers with multilingual support; Kore.ai provides an enterprise agent platform for building, orchestrating, and governing multi‑agent workflows; Yellow.ai targets CX and EX automation with agentic, multi‑channel automation; IBM watsonx Assistant supports no‑code and developer‑driven virtual agents for enterprise automation; ZenCall.ai and Simple Phones provide phone‑centric AI agents that combine STT, LLM routing, and TTS to answer, route, and book appointments with CRM integrations; ElevenLabs supplies realistic TTS, voice cloning, and transcription capabilities used to raise naturalness and brand continuity; Mistral AI offers open/efficient models and production tooling emphasizing privacy and governance. Practitioners should evaluate voice AI across accuracy (STT/TTS), orchestration and governance, integration with CRMs and workflows, and deployment model (cloud, private, edge) to balance user experience, compliance, and operational control.