Agentic AI is a kind of artificial intelligence designed to act autonomously toward objectives, with limited human supervision. Rather than simply reacting to instructions, an agentic system can plan, make decisions, and execute multi-step tasks.

What Is Agentic AI?

Agentic AI systems consist of agents (or multiple collaborating agents) that reason about goals, analyze context, and carry out actions to achieve outcomes.

They differ from traditional AI that waits for explicit commands. Instead, agentic systems take initiative. 

For example, an agentic AI for IT support might detect anomalies, plan diagnostics, and apply fixes rather than waiting for human direction.

Key Characteristics of Agentic AI

Important traits of agentic AI include:

• Autonomy: It can make decisions and act without continuous human intervention.
• Goal-directed behavior: It pursues predefined or context-derived objectives.
• Planning and adaptation: It can decompose tasks, plan sequences of actions, and adjust to feedback or changing conditions.
• Collaboration/orchestration: In more complex systems, multiple agents coordinate to solve subtasks. 

These qualities make agentic systems suitable for more complex real-world problems than reactive AI.

Why Agentic AI Matters

Agentic AI promises to shift AI from being a tool to becoming a proactive collaborator. It can help:

• Automate complex workflows that require context awareness and decision-making
• Speed up tasks across domains like dev ops, operations, and customer service
• Free humans from repetitive oversight by delegating more responsibility

However, deploying agentic AI comes with challenges. Among them are ensuring safety, trust, alignment with business goals, and good data quality.

Agentic AI and Incredibuild

Developing or integrating agentic AI involves a lot of testing, iteration, and integration across systems. Incredibuild can accelerate build, deployment, and testing phases, especially when agentic AI logic spans multiple modules.

Accelerate your agentic AI project cycles with Incredibuild. Start your free trial today.

FAQs about Agentic AI

How is agentic AI different from generative AI or standard AI agents?

Agentic AI doesn’t just generate output from prompts. It reasons, plans, and acts autonomously over multiple steps. In contrast, many generative models and simple AI agents await input.

What are common use cases for agentic AI?

Examples include autonomous IT operations, multi-step customer support agents, autonomous workflow orchestration, supply chain management, and intelligent assistants that can proactively manage tasks.

What is a risk when using agentic AI?

One major risk is that autonomous decisions may go off track due to:

• Data bias
• Misaligned goals
• Unanticipated changes in the environment 

Also, governance, transparency, and accountability are harder.