Agentic Workflows
Food for Thought
Agentic workflows enable AI systems to autonomously plan, execute, and adapt complex, multi-step tasks by reasoning, making decisions, and utilizing tools with minimal human intervention.
Example
An AI agent, upon receiving an invoice complaint email, autonomously extracts relevant data (invoice number, customer details, disputed amount), cross-references it with the accounting system, identifies potential discrepancies (e.g., pricing errors, missing items), initiates a dialogue with the customer for clarification if needed, and either automatically resolves simple errors or generates a detailed case for a human agent, including a proposed resolution and supporting documentation, significantly reducing resolution time and improving customer satisfaction.
Key Questions
- What multi-step, complex tasks in our organization are currently manual or inefficient?
- What processes require significant data gathering and analysis before action can be taken?
- What tasks involve coordinating multiple systems or data sources?
- What tasks require the ability to adapt to changing circumstances or unexpected events?
- Where can AI autonomously plan and execute a sequence of actions to achieve a specific goal?
- What tasks require the AI to use a suite of tools or access various resources to complete the workflow?
- How can an AI agent identify and escalate complex or exceptional cases to human operators?
- Where can AI provide human operators with detailed summaries and recommendations to expedite decision-making?