Member-only story
Agentic AI Fundamentals: Architectures, Frameworks, and Applications 🤖
Explore the essential concepts, architectures, and frameworks that form the foundation of autonomous agents.
What is Agentic AI?
Agentic AI has the potential to change the way we work. An agent is a program that performs tasks autonomously, making decisions based on pre-defined rules or learned patterns to achieve its objectives. It is typically independent, goal-oriented, adaptive, context-aware, and capable of operating across multiple domains. By leveraging these characteristics, Agentic AI can significantly enhance efficiency and productivity in various fields. The ability to adapt and make context-aware decisions allows these agents to handle complex tasks with minimal human intervention, leading to more streamlined workflows and innovative solutions.
There are a variety of applications and use cases, such as:
- Insurance: Agentic AI, like the Morpheus AI industry accelerator, streamlines and automates complex processes such as claims processing and onboarding, reducing administrative costs and improving accuracy.
- Marketing: AI frameworks manage tasks like data gathering and sentiment analysis, optimizing marketing efforts and strategies through collaborative AI agents.
- Retail: Agentic AI enhances personalized customer interactions across various touchpoints, leading to improved customer loyalty and increased sales.
- Healthcare: AI systems provide diagnostic support through tasks like radiology image analysis and treatment recommendations, improving the quality of care.
Good Data Enables Agentic AI
AI agents heavily rely on high-quality data to function effectively, as the accuracy and reliability of AI models directly depend on it. They perceive their surroundings through sensors, interpret the data, make decisions, and take actions based on those decisions.
