Agentic AI
Definition
Agentic AI is a type of artificial intelligence that works proactively and autonomously to make decisions and perform tasks.
With limited human guidance, Agentic AI understands a user’s goals and interprets the context of the problem they need solved. This AI can handle simple to complex workflows. Humans set the objectives and provide data while the AI agents handle the rest.
What is an AI agent?
An AI agent, sometimes called an LLM agent, is an autonomous system that uses AI to complete tasks on behalf of a user.
While an AI assistant can help you work on tasks, an AI agent proactively and independently handles tasks on their own. Humans provide data and set goals, and the AI agent determines the steps necessary to achieve those goals.
How does Agentic AI differ from Generative AI?
Agentic AI systems use data and context to make decisions and complete tasks to reach human-set goals.
Generative AI is a type of artificial intelligence that uses data and human prompts to create new content, such as text or images. Agentic AI uses generative capabilities to develop solutions and ideas.
How does Agentic AI work?
Typical AI chatbots and tools follow predefined guidelines to respond to user inputs. Agentic AI goes beyond standard AI capabilities by combining automation, LLMs, and machine learning to create autonomous, proactive AI agents.
These AI agents learn from data, user behavior, and experiences while adapting to changing environments. From there, they can understand data, make decisions, and act independently of humans.
What are practical examples of Agentic AI in action?
From personal assistants to sophisticated financial management, Agentic AI goes beyond the standard capabilities of AI. Here are a few examples:
- Human resources: AI agents can provide personalized responses to employees’ questions about benefits or onboarding.
- Engineering: Rather than waiting for a human employee to report an issue, Agentic AI can proactively detect outages, equipment failures, and bottlenecks.
- Customer service: Representatives can save time using AI agents to automate responses to common questions or quickly find customer information.
What benefits do Agentic AI and AI agents offer?
The benefits of Agentic AI promise to transform the way we work. Here’s how:
- Better decision making: AI agents can analyze complex data sets to make the most informed decisions possible.
- 24/7 access: AI agents don’t clock out at 5 p.m. Agentic AI makes organizations highly available to customers or employees.
- Scalability: Agentic AI is primed for adaptability. Agents can easily take on new tasks, allowing the organization to expand operations into new fields.
What are the risks and challenges with Agentic AI?
Since AI agents operate autonomously, there are some challenges organizations will need to navigate:
- Accountability is blurry: Who is to blame if an AI agent approves a financial transaction that should not have been approved? The developer? The organization? Or the AI agent?
- Security is risky: AI agents work with sensitive information, which makes them susceptible to vulnerabilities if not properly secured.
- Oversight is complicated: AI agents are technically complex and require constant monitoring to ensure they operate correctly and ethically. Organizations must effectively manage Agentic AI to reap the benefits.
AI agents must comply with an organization’s ethics and goals. Robust security measures, accountability policies, and management frameworks are crucial to the success of Agentic AI.
What’s next for AI agents and Agentic AI?
Previous AI tools and assistants have been rules-based, meaning they depend on human instruction to function as needed. In the future, the autonomy of Agentic AI will bring more proactiveness to organizations.
As more industries adopt Agentic AI practices, organizations will quickly see operational benefits as AI agents become entwined with operations. Some may start with a single AI agent, while others progress to an enterprise ecosystem of autonomous agents.