Understanding Agentic AI
You’ve probably heard about ChatGPT, Google’s Gemini, and various AI writing tools, but there’s a new term gaining attention: agentic AI. While it might sound like just another buzzword, it’s built on existing technology with recent significant advances.
What is Agentic AI?
Agentic AI refers to artificial intelligence systems that can make decisions and act independently to achieve specific goals. Unlike traditional AI chatbots that require explicit instructions at each step, AI agents can break down complex objectives into manageable actions.
“Agentic AI is now making this sort of sense-decide-act loop available to everybody,” said Peter Stone, professor at the University of Texas and chief scientist at Sony AI America. This capability allows AI to task programs with sensing the world, deciding what to do, and actually acting.
Key Characteristics of Agentic AI
- Autonomy: Makes decisions and acts without constant human input
- Planning: Develops and follows plans to meet goals
- Adaptability: Adjusts strategies based on feedback and context
- Learning: Improves performance over time through experience
How Agentic AI Differs from Generative AI and Chatbots
While generative AI creates content based on training data and user prompts, agentic AI adds a layer of autonomy with reasoning and planning to achieve goals proactively. For example, a generative AI might write a vacation itinerary, but agentic AI could plan the trip, book flights, reserve hotels, and even handle changes if needed.
“Chatbots answer questions. Agentic AI solves problems by turning insights into outcomes,” explained Ankur Patel, CEO of Multimodal. This means orchestrating tasks across platforms, verifying documents, assessing risks, and even triggering real-world actions.
Applications and Industries
Agentic AI is being implemented across various industries, including:
- Robotics: Autonomous robots navigating complex environments
- Software development: AI agents writing and debugging code
- Customer service: Advanced chatbots resolving complex issues
- Supply chain management: AI managing inventory and optimizing delivery routes
- Healthcare: Tools flagging anomalies and suggesting diagnoses
The Future of Agentic AI
While there are concerns about job displacement, experts believe agentic AI will primarily augment human capabilities rather than replace them entirely. The technology is advancing rapidly, with consumer applications emerging in areas like web browsing and travel booking.
However, agentic AI also raises important questions about trust, responsibility, and risk management. As these systems become more autonomous, ensuring proper safeguards and oversight will be crucial.
Trust and Limitations
“The risk is directly related to the space of actions and the agency or autonomy that you give to the agent,” emphasized Stone. To build trust, AI systems need features like detailed audit trails, decision logs, and the ability to route critical decisions to humans when necessary.
As agentic AI continues to evolve, it promises to transform how we interact with technology, making it more proactive and capable of handling complex tasks independently. While challenges remain, the potential benefits in efficiency, customer experience, and error reduction make it an area worth watching closely.
