This topic examines AI platforms used in healthcare to deliver clinical decision support (CDS) and operational AI—covering virtual assistants, autonomous agents, conversation intelligence, and no‑code/low‑code builders. As of 2026-02-17, hospitals and health systems are moving from pilot projects to production deployments, prioritizing platforms that combine LLM‑driven assistants with strong governance, EHR interoperability (FHIR), privacy controls (HIPAA), and auditability. Key platform types include enterprise agent frameworks and virtual assistants (IBM watsonx Assistant), agentic infrastructure that provides service-level visibility and activity auditing (Xilos), CX/EX automation suites for patient and employee interactions (Yellow.ai, Observe.AI), and no‑code/low‑code agent builders for rapid workflow automation (MindStudio, StackAI, Lindy). Observe.AI’s real‑time agent assist and auto‑QA features illustrate how conversation intelligence can reduce contact‑center load and improve triage; stack-level products focus on end‑to‑end deployment, governance, and monitoring of autonomous agents. Practical evaluation favors platforms that support model validation, explainability for CDS, data lineage, and integration with clinical data platforms. Operational AI use cases include automated clinical documentation, scheduling and capacity optimization, patient outreach, and front‑line decision support. Current trends emphasize agent orchestration, visibility into autonomous actions, and no‑code tooling to widen adoption among clinical and administrative teams. Success depends on rigorous evaluation against safety, regulatory compliance, and measurable clinical and operational outcomes rather than feature lists alone.