Why is Hot New Agentic AI Now Dominating the Space? -- Pure AI

Why is Hot New Agentic AI Now Dominating the Space?

By Pure AI Editors
11/01/2024

One of the most active areas of AI research and development is "agentic AI." The "agentic" part of the term means agent-based, where an agent is a specialized AI software component that can communicate with other agents. By combining various agents, an agentic AI system can do far more than a single AI component. Specifically, an agentic AI system can:

Sense: Gather data from databases, log files, other software system outputs.
Reason: Use a large language model, such as GPT-x, to accept a goal in plain English.
Act: Execute tasks such producing reports or approving a car loan.
Learn: Continuously learn and improve based on feedback.

Another way of thinking about agentic AI is that it's a collection of AI assistants that can work together. All of the major AI players -- Microsoft, Google, Amazon, Meta, and so on -- have intense agentic AI research programs under way.

Figure 1: High-Level View of an Agentic AI System — **[Click on image for larger view.]** *Figure 1*: High-Level View of an Agentic AI System

An early example of agentic AI is Microsoft's AutoGen system. Another example is Google's Vertex AI Agent Builder.

Applications Of Agentic AI

Agentic AI systems have the potential for broad applicability. Most knowledge-based activities could benefit from agentic AI. Some hypothetical examples include:

Software Development - Imagine a command such as, "Create a software system that uses machine learning to predict our sales to mid-sized clients, and integrate that prediction system into our existing CRM system."
Business Operations - "Use our internal data sources to automate our current manual invoicing process."
Scientific Research - "Design a new hybrid ceramic material that is heat resistant and less expensive than the existing materials we use in our manufacturing."
Healthcare - "Create a software system that monitors all patients, records their statuses, and signals an alert when the attention of a doctor is needed."
Finance - "Design an investment strategy that optimizes return on investment."

Comments
The Pure AI editors asked Dr. James McCaffrey from Microsoft Research for comments about agentic AI. McCaffrey cautioned, "Current individual AI assistants can suffer from hallucinations and generate incorrect advice and conclusions. Therefore, it's important to have humans-in-the-loop. This precaution is even more true of agentic systems because their increased complexity could cause cascading hallucinations.

"Put somewhat differently, AI assistants and emerging agentic AI systems should probably be considered initial starting points for knowledge systems that are vetted and evaluated by humans rather than final solutions that are ready for immediate deployment. Additionally, all the well-known issues regarding privacy, safety and so on, are equally important for agentic AI systems."