Term
Agentic Workflow
Definition
An Agentic Workflow in AI is a process where AI "agents" (software designed to act autonomously) systematically plan, execute actions, and learn from those actions to achieve specific, long-term objectives.
Where you’ll find it
This concept is part of the architecture of AI systems themselves, primarily on platforms that involve complex, goal-oriented AI tasks such as robotics control systems, automated trading platforms, and advanced data analytics tools.
Common use cases
- Automating repetitive tasks in data aggregation and processing, improving the AI's ability to make decisions and learn over time.
- Directing autonomous vehicles where AI continuously learns and adapts to varied traffic and environmental conditions.
- Improving customer interactions through AI-powered support systems that learn from each customer engagement to enhance future interactions.
Things to watch out for
- Ensure that the objectives set for the AI are clear and achievable; vague goals can lead to inefficient learning and action loops.
- Monitor the AI's performance periodically to make adjustments, as the AI might develop unintended behavior patterns over time.
- Be aware that AI systems with Agentic Workflows require substantial initial data input and ongoing data feeds to learn effectively.
Related terms
- Machine Learning
- Autonomous Agents
- Reinforcement Learning
- Predictive Analytics
- AI Optimization