Agents and Agentic AI
We are almost at the end of these
series! If you have followed carefully, you will now have mastered the basics
of AI! But with it would not be complete without introducing Agents. So what is
an agent in AI? “An AI agent is a software system that uses
artificial intelligence to autonomously pursue goals and complete tasks on
behalf of users. Unlike traditional programs that follow fixed instructions, AI
agents can reason, plan, observe, act, and adapt based on
their environment and objectives. They are powered by foundation models (such
as large language models) that enable natural language understanding,
reasoning, and decision-making. AI agents can process multimodal inputs—text,
audio, video, code—and operate either interactively with humans or in the
background without direct user input”. Now automation has existed for many
years, so what makes the agent special? It´s reasoning capacity, based on it´s
LLM. The agent is built around an LLM enabling it to act, by doing a specific
task with a specific set of tools. In the past, automation was ruled-based. A
specific rule was programmed, and the automation machine would not step far away
regarding what it´s program told it to do. By including an LLM in the loop
coordinating the action, the agent mimics human reasoning. As a disadvantage,
they constitute a true black box. Where in rule-based model it is transparent
to explain why an input provides a certain output, the reasoning of the LLM based
on neural networks is so complex it is virtually impossible to determine how
the model reached a certain conclusion.
The agent is composed of an LLM
in it´s heart, memory and tools with which it can access different applications.
Let us take an example from an agent to send email to a customer. If the LLM
alone is prompted to send an email, it will not be able to do so. But the agent
can provide access to the mailbox, enabling the LLM to enter it and execute the
instruction. The LLM could also be connected to other tools, such as a calendar
to check the availability of both parties and organize a meeting. But, let´s
say the customer rejects the invitation and proposes another time. The LLM can
re-check the schedules and send new invitations, without any human intervention!
Have you noticed how chatbots are
powered by AI, and no longer human? I recently needed to reset my password and
was greeted by an AI chatbot. After some indications, the bot understood which
environment I needed to reset my password in and which system. Then it went in
the system and performed the password reset itself and provided me with the new
password! If the bot cannot help you, you can always ask for the intervention
of a human. I remember in my first SAP assignment in 2008 I worked in customer support
for a few months, and was actually in charge of resetting the passwords manually!
By filtering the most repetitive basic tasks, the agent automates what would be
hours of consulting work, taking productivity to whole new levels.
In the following graph, you can
see an example of how an agent works. A user submits a “Create User” form,
which triggers an AI-driven workflow. The AI Agent analyzes the user’s
information, checks relevant systems, and determines whether the user is a
manager. Based on this decision, the system either adds the user to a specific
Slack channel or updates their Slack profile automatically, eliminating manual
user management.
If multiple AI agents collaborate
to automate complex workflows this is called “Agentic AI”. The agents will
exchange data with each other, the entire system working together to achieve
common goals. Each agent will then be specialized in a specific task, which it
will perform more accurately. Finally, an orchestrator agent coordinates the
activities of different specialist agents to complete larger, more complex
tasks.
An agentic AI system could work
as a travel agent, checking your calendar, hotel and flight availability, best
prices and service quality, all in the brink of an eye with no human intervention!
Each task would be performed by an individual agent achieving maximum
efficiency, and they would all synchronize to perform the activities at the
same time. You can now understand why so many jobs appear at risk by AI
automation, with telemarketers, data entry clerks, customer service
representatives, legal support roles, assembly line workers and cashiers toping
the list. Jobs will certainly be automated and replaced by agents, but AI will lead
to the creation of many news jobs as well. What would be the outcome of net job
creation? Repetitive task automation will leave us humans with more capacity to
do what´s important: focus on creativity and building businesses. Will you make
the most of it or will you be replaced by a robot? It´s your choice!
¿Qué son los agentes de IA? Definición,
ejemplos y tipos | Google Cloud
What are
AI Agents?- Agents in Artificial Intelligence Explained - AWS
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