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Glossary

AI Work Automation

AI work automation is the use of AI models to turn unstructured requests — emails, chats, documents, forms — into completed work: grounded answers or actions executed in business systems. Unlike chat assistants, it operates on structured work items with evidence, approvals, and an audit trail, so every outcome is traceable and governed.

Synonyms: AI workflow automation, agentic workflow automation, AI work orchestration, intelligent work automation

AI work automation sits between two older categories. Traditional workflow automation and RPA execute fixed rules quickly but break on unstructured input; chat assistants handle unstructured language well but produce answers without structure, governance, or follow-through. AI work automation combines the two: models classify and extract structure from whatever arrives, retrieval grounds responses in approved sources, and any proposed change to a business system passes policy checks and approval gates before it executes. Because every step — intake, grounding, approval, execution — is recorded, teams get the speed of automation with the accountability of a managed process.

Frequently asked questions

How is AI work automation different from an AI chatbot?
A chatbot produces a reply and forgets the exchange. AI work automation converts each request into a structured work item, grounds answers in cited evidence, routes proposed actions through approvals, and records the outcome — the unit of value is completed work, not a message.
How does it relate to agentic workflow automation?
They describe the same category from different angles. Agentic framing emphasizes the model planning and acting; work-automation framing emphasizes the governance around it — structured intake, evidence, approval gates, and an audit trail that makes agent activity safe to run in production.