The world of artificial intelligence is changing rapidly before our eyes. What was once science fiction is now a reality that impacts our daily lives. Two new approaches, AI Agents and Agentic AI, represent the next step in the development of intelligent systems that can work independently and collaborate with each other.
A new study helps us understand the difference between them and what it means for the future of technology.
To understand how significant this evolution is, let’s imagine how the change has taken place in our daily lives. Just two and a half years ago, most of us had never even heard of ChatGPT. Today, millions of people around the world use AI systems every day to write emails, solve problems, learn new skills or simply chat when they need advice. But what we are seeing now is just the tip of the iceberg, AI systems are becoming so sophisticated that they no longer wait for our commands, but are starting to recognize what they need to do and how to collaborate with each other.
This transformation is not just a technical curiosity or a futuristic vision, it is changing the way we work, learn and solve problems. As we adapt to these changes, we believe it is important to understand what exactly is happening “under the hood” of these advanced systems and how they can improve our work and lives.
ChatGPT and similar systems are like a very smart student, they can answer a question when you ask them, but they can’t initiate an activity or “remember” to do something on their own. It’s like having an assistant waiting for you to give them a task, but they will never realize that they need to remind you of an important meeting.
AI Agents: Your Digital Helpers
AI Agents are the next step, they are smart systems that can:
Work independently.
Once you tell them what to do, they continue to work without constant supervision, like a good employee who knows their job.
Focus on specific tasks.
Each agent is like a specialized worker. One may be great at answering customer emails, another at tracking complaints, another at organizing calendars.
Adapt to the situation.
When a new situation arises, they can adapt their approach, like an experienced employee who knows how to solve an unexpected problem.
Real-life examples:
Customer support: An agent reads your complaint, checks the system to see what happened to your order, and responds with a concrete solution.
Organizing emails: An agent recognizes whether an email is urgent, sorts it into the appropriate folder, and may even remind you of important tasks.
Content recommendations: Based on what you usually watch or read, an agent suggests new content that you might be interested in.
Meeting scheduling: When you say “let’s meet next week,” an agent looks at your calendars, finds free time, and suggests dates.
Agent AI: When agents work as a team
Agent AI goes a step further. Imagine an office where different experts collaborate on a complex project. Each has their own expertise, but together they can solve much more complex problems than any of them could individually.
Division of complex tasks: A central “coordinator” takes a large task and breaks it down into smaller parts that can be solved by specialized agents.
Team collaboration: Agents exchange information with each other, much like colleagues in an office discussing a project.
Learning from experience: The system remembers what it has learned from previous tasks and uses that knowledge for future situations.
Team management: There is a “leader” who coordinates work, resolves disputes, and makes sure everything runs smoothly.
Application examples:
Research work: One agent searches for relevant articles, another analyzes them, a third summarizes them, and a fourth creates a final report.
Agriculture: Drones map the land, robots pick crops, and transportation systems coordinate everything under the supervision of a central system.
Medicine: In a hospital, various agents monitor patients’ vital signs, analyze medical histories, and suggest treatments.
Differences between the two approaches
The difference between AI Agents and Agentic AI is like the difference between an individual craftsman and a construction company:
AI Agents are like craftsman specialists, excellent in their field, working independently but limited to what they know best.
Agentic AI is like a large construction company, with different experts who together can build a large building, because they complement and coordinate with each other.
Challenges and limitations
Like any new technology, these systems have their problems:
Individual agent problems:
Sometimes they give incorrect information (like when your GPS takes you the wrong way)
They don’t always understand cause and effect (they may notice that sales increase on Fridays, but they don’t understand why)
They have difficulty planning complex tasks that require many steps
Teamwork problems:
Agents sometimes “don’t understand” each other because they interpret the same task differently
A single agent’s mistake can ruin the work of the entire team
The more agents working together, the harder it is to coordinate their work
How these problems are being solved
Experts are working on improvements:
Information verification: Agents are increasingly checking their answers using up-to-date databases, just as you check information across multiple sources.
Better planning: Techniques are being developed that allow agents to think better before taking action and plan step by step.
Experience memory: Systems are getting better at storing and using previous experiences.
Better communication: Agents are learning how to better collaborate and understand each other.
What awaits us in the future
This technology is just beginning to develop. In the coming years, we can expect:
Smarter assistants that will anticipate our needs
More complex systems that can manage entire processes in companies
Better understanding of cause and effect
More secure and reliable operation
The transition from simple chatbots to complex AI systems that collaborate represents a revolution in the way technology can help us. While AI Agents are already changing the way we do everyday tasks, Agentic AI promises to enable much more complex problem solving through teamwork of digital assistants.
This technology will not replace humans, but will expand our capabilities, just as the calculator expanded our ability to calculate and GPS our ability to navigate. Understanding how these systems work helps us to use them better and prepare for a future in which artificial intelligence will be even more present in our lives.
The journey from reactive systems to truly autonomous and collaborative AI systems is just beginning, but it already heralds a future in which artificial intelligence will become even more capable, independent and useful in our daily lives.
If you are interested in how to effectively use AI agents in your business or have questions about implementing this technology in your organization, feel free to contact me. As an AI strategist with experience in digital learning and innovation, I can help you:
Identify the best opportunities for implementing AI agents in your business
Develop a gradual implementation strategy
Train your team to work with these technologies
Avoid common mistakes when introducing AI solutions
Let’s stay in touch because together we can harness the potential of these advanced AI systems to grow and improve your business.
