Agentic Automation is an approach to automating business processes in which tasks are not carried out by rigidly programmed scripts but by AI agents capable of making decisions based on context. While classic RPA automation fails at every deviation from the learned scenario, an agentic workflow can handle variability: an agent reads an unstructured email, understands the request, looks up data in systems, prepares a response or document, and escalates to a human when uncertain. More complex processes are handled by the orchestration of multiple specialised agents – one collects data, a second analyses it, a third checks the quality of the output. Typical deployments include processing incoming invoices and orders, preparing price quotes, employee onboarding, reporting and customer support. A successful project begins with mapping processes and selecting a narrow, measurable case with high recurrence; a pilot with human oversight follows, along with measuring savings and gradually expanding the agents' authority. The critical factors are data quality, integrations via API or MCP, and clear rules of accountability for the agents' outputs.
See also: AI Agent, AI Process Automation.
