Agent AI: what is it and how does it work?
Artificial Intelligence is evolving rapidly. Among the most relevant innovations of recent years is... agent AI It is gaining prominence for completely changing the way intelligent systems operate.
Unlike traditional models, which only respond to commands, agentic AI is capable of... to make decisions, act autonomously, and pursue defined goals., integrating data, tools and strategies in real time.
But in the end, What is agentive AI?, How does it work in practice, and why are companies and professionals paying increasingly close attention to this technology? That's what you'll understand in this article. Check it out!
What is agentive AI?
A Agency AI (or Agency Artificial Intelligence) It is a type of artificial intelligence system based on autonomous agents.
These agents are capable of to perceive the environment, analyze information, make decisions, and execute actions. to achieve specific goals, all with minimal human intervention.
Instead of simply answering a question or executing a single command, agentic AI functions as a “intelligent orchestrator”, It's capable of planning steps, choosing tools, correcting course, and learning from the results. In other words, it gives you more than just an answer.
In practice, this means that AI ceases to be merely reactive and becomes... proactive and strategic.
Key characteristics of agentic AI:
- It acts in a way autonomous;
- Works oriented towards objectives;
- Makes decisions based on context;
- It integrates multiple tools and systems;
- Learn from feedback and results.
This approach is being applied in areas such as business, technology, marketing, logistics, customer service, finance, and many more.
Concepts of Agency Artificial Intelligence
To better understand how agentic AI works, it's important to know some fundamental concepts that underpin this technology.
Intelligent agents
Agents are software elements that observe the environment, process information, and act according to rules, objectives, and learnings.
An agent-based AI system can have a single agent or multiple agents working together.
Autonomy
Autonomy is one of the main pillars of agentic AI. Unlike traditional systems, it does not depend on constant commands to function. The AI analyzes the context, decides what to do, when to act, and how to execute each step., within previously defined limits.
A practical example is the use of agentic AI in lead management: the AI agent automatically identifies the contact's characteristics, analyzes their behavior, and creates a personalized email flow, adjusting actions according to the customer's interactions.
Below we will cite some more examples of the areas in which agentic AI can be used.
Planning and decision making
Unlike traditional AI, agentic AI is capable of planning sequences of actions, Evaluate scenarios and choose the best strategy to achieve your goals.
Integration with other tools
AI agents can access APIs, databases, external software, spreadsheets, CRMs, email systems, automation platforms, and much more, all in an integrated way.
Continuous learning
Based on the results of the actions performed, the agentic AI adjusts its behavior, improves future decisions, and becomes increasingly efficient.
Examples of agentic AI in practice
Agent AI is already present in several real-world applications and is likely to become increasingly common in everyday professional life. Below are some examples of areas where agent AI can be used.
Customer service
- Identify the customer's problem;
- Consult databases;
- Resolve the request;
- Scale up to a human only when necessary.
All of this in an automated and personalized way.
Marketing and sales
In the commercial sector, agentive AI can:
- Analyze customer behavior data;
- Develop approach strategies;
- Run campaigns;
- Adjust actions based on results.
Process management
Companies use agentive AI to:
- Automate internal workflows;
- Monitor performance indicators;
- Identify operational bottlenecks;
- Suggest operational improvements.
In the corporate environment, agentive AI can be responsible for internal process management, Identifying errors, proposing adjustments, and even redistributing tasks among teams, and then monitoring the results of the implemented changes.
Finance and investments
In the financial sector, intelligent agents can:
- Analyze market behavior in real time;
- Identify investment opportunities aligned with the defined profile;
- Simulate different financial scenarios and risk levels;
- Execute investment decisions autonomously, respecting pre-established limits, such as a monthly budget of up to R$ 10 thousand.
Software development
In technology, agentic AI can:
- Analyze system or company requirements;
- Writing code snippets;
- Testing functionalities;
- Correct errors automatically;
- Manage development tasks.
Read also: Artificial Intelligence: How Computer Engineering Facilitates Technological Innovation
Agent AI and generative AI: what's the difference?
Although the terms are often used together, Agent AI and generative AI are not the same thing.
Generative AI
A Generative AI It uses Machine Learning and is focused on content creation. It generates text, images, videos, code, and audio from human commands. Well-known examples include chatbots, image generators, and writing assistants.
Key characteristics of generative AI:
- Acts under command;
- Responds to prompts;
- Generates content;
- It does not perform actions autonomously.
Read also: Artificial Intelligence and Machine Learning
agent AI
Already agent AI It goes beyond content creation. It:
- Define strategies;
- Performs actions;
- It uses and integrates with tools;
- Makes decisions;
- Works with a goal-oriented approach.
In many cases, agentic AI It uses generative AI models as part of the process., but it adds a layer of autonomy and strategic intelligence.
Agency AI Course in Brazil: Why specialize now?
With the rapid advancement of artificial intelligence, professionals who master concepts of any type of AI tend to have a competitive edge.
How to agent AI It is a more advanced form, giving it a significant competitive advantage in the market.
Companies are increasingly seeking individuals capable of:
- Automate complex processes;
- Integrating AI into business;
- Create smart and scalable solutions;
- Making decisions based on data and technology.
In this scenario, investing in a Agency AI course in Brazil It's a strategic way to prepare for the present and future of work.
Always thinking about technology, ESEG College, part of the Etapa Group, created the professional extension course in Artificial Intelligence, Agency, and Decision Making in Complex Contexts.
Agency AI Course at ESEG College
Considering this new market reality, the ESEG College offers a Agency AI Course aimed at professionals who want to understand, apply, and lead projects with intelligent agents.
The course is 100% online, with a practical focus and accessible approach, even for those without a technical background in technology.
What you learn in ESEG's Agency AI course:
- Fundamentals of Agency Artificial Intelligence;
- Difference between traditional, generative, and agentic AI;
- Creation and use of intelligent agents;
- Process automation with AI;
- Integration of tools and systems;
- Practical applications in the corporate environment;
- AI-driven decision making.
This course is aimed at business, management, and technology professionals; leaders and managers who want to innovate; analysts, consultants, and entrepreneurs; and individuals seeking professional growth with a focus on innovation.
Agent AI is already transforming companies, professions, and business models, and those who understand this technology are ahead of the curve.
Want to learn how to apply it in practice and boost your career?
Learn about the Course of Artificial Intelligence Agency From ESEG College, talk to our team and take the next step towards your future!
