Enterprise GenAI platforms and managed GenAI services cover the software, hosted services and governance layers organizations use to deploy AI at scale. This topic examines platforms that deliver out-of-the-box assistants and orchestrated multi‑agent workflows, the managed services that package integration and operationalization, and the supporting marketplaces, data platforms and governance/security tools that make deployments auditable and compliant. Relevance in 2026 stems from widespread enterprise adoption: organizations want AI that integrates with business apps, automates multistep processes, and meets regulatory and vendor‑risk requirements. Key trends include the shift from point tools to platform ecosystems, growth of agentic automation that acts inside software interfaces, and increased demand for observability, policy enforcement and verticalized governance for regulated sectors. Representative tools illustrate the landscape: IBM watsonx Assistant provides enterprise virtual agents and multi‑agent orchestrations via no‑code and developer workflows; Kore.ai focuses on building, deploying and governing multi‑agent workflows with observability; Microsoft 365 Copilot embeds assistant capabilities across productivity apps to surface insights and automate tasks; Adept’s agentic systems (e.g., ACT‑1) enable AIs to observe and act inside software interfaces to automate complex workflows; HubSpot’s Breeze layers contextual AI across its customer platform for CRM workflows; Monitaur targets insurance and regulated industries with centralized policy, monitoring, validation and vendor governance. Together these platforms, plus AI marketplaces (for models and connectors) and AI data platforms (for datasets, labeling and pipelines), form the operational stack enterprises require to deploy GenAI reliably, securely and in compliance with evolving governance expectations.