AI chatbots and assistants for in‑car experiences cover voice-first conversational agents, customer‑service bots, and background automation layered into vehicle ecosystems such as Apple CarPlay and competing platforms. These solutions must combine low-latency speech transcription and high-quality text‑to‑speech with secure, privacy-aware model hosting and orchestration to handle navigation, media, scheduling, diagnostics and live support without distracting drivers. Relevance: Automotive integrations are maturing as manufacturers and platform providers enable third‑party assistants and tighter CarPlay/Android Automotive hooks. At the same time, advances in multi‑agent orchestration, no‑code agent builders, and scalable inference make it practical to run specialized assistants (personal assistants, customer service bots, voice schedulers) that interact with vehicle systems and cloud services while meeting latency and safety constraints. Tools and roles: Enterprise teams can use IBM watsonx Assistant to build no‑code or developer-driven virtual agents and multi‑agent flows for customer service or fleet management. Conversational backends like Anthropic’s Claude family provide dialogue and reasoning capabilities. Google’s Vertex AI supports training, fine‑tuning and deploying models at scale; Together AI addresses inference and GPU scaling for low-latency deployment. No‑code agent platforms such as Nelly and StackAI accelerate creation and orchestration of specialized agents, while Anakin.ai provides prebuilt apps for rapid content and workflow automation. Practical considerations: designers must balance on‑device processing and cloud calls, ensure robust speech recognition/TTS pipelines, integrate calendar and vehicle APIs for voice scheduling, and prioritize safety, privacy and regulatory compliance. The current landscape favors modular stacks that combine conversational models, orchestration layers and optimized inference to deliver reliable in‑car assistant experiences.