Automotive AI platforms for autonomous and assisted vehicles bring together real‑time edge vision, agentic orchestration, large‑scale data infrastructure, and safety/governance controls to move vehicle autonomy from research into production. As of 2026, deployments increasingly require deterministic edge middleware and validated autonomy behaviors, low‑latency perception pipelines, robust data platforms for training and simulation, and governance layers that meet regulators’ safety and security expectations. Key tool categories: Edge AI Vision Platforms provide deterministic perception and inference close to sensors; AI Automation/Agent Platforms enable multi‑agent orchestration and behavior libraries for mission logic; AI Data Platforms handle real‑time telemetry, labeled datasets, simulation replay and model lifecycle; AI Security & Governance enforces access controls, explainability, auditing and runtime mitigation. Representative tools illustrate the landscape: Shield AI’s Hivemind and EdgeOS focus on deterministic middleware, behavior catalogs (Pilot) and productionization workflows (Forge) for autonomy; AutoGPT and LangChain supply frameworks to build and orchestrate agentic workflows and stateful agent graphs; Warp acts as an Agentic Development Environment to accelerate developer iteration and debugging; IBM watsonx Assistant provides enterprise virtual agents and no‑code developer flows for operator interfaces and automation. Trends and practical considerations: modern stacks combine LLM‑based planners with hard real‑time control, requiring tight integration between safety‑certifiable middleware and flexible agent layers. Real‑time vision at the edge, rigorous data pipelines for simulation and validation, and clear governance practices (security, explainability, certification evidence) are now central operational requirements. For organizations evaluating platforms (e.g., Rubin and others), priority criteria include deterministic latency, reproducible validation tooling, agent orchestration primitives, and governance hooks for auditability and regulatory compliance.