Agentic Workflow
A multi-step process where AI agents autonomously plan, execute, and iterate on tasks to achieve complex goals. Unlike single-turn responses, agentic workflows enable AI to break down problems and work through solutions systematically.
Agentic workflows represent a fundamental shift from reactive AI to proactive problem-solving. Instead of simply answering questions, AI agents using agentic workflows can decompose complex requests into subtasks, execute each step sequentially or in parallel, evaluate intermediate results, and adjust their approach based on outcomes—mirroring how human experts approach sophisticated challenges.
In customer service, agentic workflows enable AI to handle complex resolution scenarios that require multiple steps: diagnosing an issue, checking account status, identifying relevant solutions, applying fixes, and verifying resolution—all without requiring human intervention at each stage. This transforms AI from a support assistant into a capable agent that can independently resolve end-to-end service requests.
The power of agentic workflows lies in their flexibility and intelligence. AI agents can adapt their workflow based on context, handle unexpected obstacles by trying alternative approaches, and learn from outcomes to improve future executions. This capability is essential for achieving high resolution rates on the complex, multi-faceted queries that characterize modern customer service.