Enterprise Agent & Automation Platforms for White‑Collar Task Automation covers the software and operational patterns organizations use to replace repetitive knowledge‑work with supervised AI agents, orchestrated workflows, and embedded copilots. As of 2026, firms are moving beyond point pilots to production deployments that require not only agent design and execution but also model lifecycle, integration, and regulatory controls. Key platform categories include no‑code/low‑code automation platforms (StackAI, MindStudio, Relevance AI) that let business teams assemble, test, and operate autonomous agents and workflows; cloud ML and GenAI platforms (Vertex AI) for training, fine‑tuning, hosting, and monitoring models at scale; enterprise assistant frameworks (IBM watsonx Assistant) for building virtual agents and multi‑agent orchestrations focused on CX and internal support; and governance and validation tools (Monitaur) that centralize policies, monitoring, vendor oversight, and compliance for regulated industries. Developer tooling like JetBrains AI Assistant complements these stacks by improving coder productivity and enabling tighter integration between codebases and deployed agents. Relevant trends include the consolidation of agent orchestration, increasing demand for explainability and audit trails, the rise of curated agent marketplaces and templates for industry workflows, and tighter cloud‑native integration for observability and security. Typical white‑collar use cases are customer‑experience automation, claims and contract processing, research and summarization, and developer acceleration. When evaluating solutions, organizations should weigh low‑code usability, multi‑agent orchestration, model governance, cloud deployment options, and vendor support for industry compliance—balancing speed of automation with controls required for enterprise risk management.