Gartner ThinkCast
From Hype to Reality – What AI Agents Can (and Can’t) Do
Feb 25, 2025
Discover the fascinating world of agentic AI and its growing role in decision-making. Learn how these AI agents interact empathetically, even helping users tackle tough personal challenges. The potential for autonomy in dynamic environments is explored, along with the collaboration of AI agents in achieving regulatory compliance. Misconceptions about AI capabilities are addressed, clarifying the distinction between agentic AI and traditional chatbots. This insightful discussion prepares listeners for the future of multi-agent systems.
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Quick takeaways
- Agentic AI systems, capable of making autonomous decisions, rely on real-time interaction and learning to optimize problem-solving solutions.
- Multi-agent systems enhance AI functionality by enabling collaboration among agents, ensuring compliance and improving the quality of outputs in complex environments.
Deep dives
Understanding Agentic AI
Agentic AI refers to artificial intelligence systems that possess the ability to make autonomous decisions while operated within set boundaries. These AI agents are designed to sense their environments and identify optimal solutions to problems through real-time interaction and learning. For instance, a smoking cessation application exemplifies this by guiding users through specific conversations based on their inputs, demonstrating how agents can both provide support and build rapport over time. This capability emphasizes that agentic AI extends beyond mere programmed responses, leveraging sensory data to tailor interactions and solutions effectively.
