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AI agents handle tasks like coding, emails, and planning without constant human input
Frameworks like LangChain and AutoGen make agents practical for businesses
By 2027, half of large companies may use AI agents for daily operations
Artificial intelligence is no longer just a tool for generating text or answering questions. A new generation of systems known as AI agents has now entered mainstream industries to perform complex tasks autonomously.
These agents are built on the same large language models that are used to run the chatbots. However, agentic AI can execute tasks without needing constant human monitoring, making a significant leap in how machines can be used across sectors.
Language models have always been used for writing essays, explaining schoolwork, or summarizing articles. However, these models have evolved and are now advanced enough to follow longer, multi-step instructions, break down problems into smaller tasks, and even use external tools to finish them. This means that instead of only advising on coding, an agent can write a program, test it, and correct mistakes without constant guidance.
Special software frameworks such as LangChain, AutoGen, and CrewAI play an important role in developing AI agents. These platforms allow models to store memory, search information, and connect with other applications.
For example, when a user asks the agentic AI to plan a trip, it compares flight tickets, finds hotel deals, checks reviews, and prepares a shortlist for the user. Performing this task manually would take hours of effort to visit several websites and compare prices.
Also Read: What are the Types of AI Agents?
Companies have already started using agents in their everyday operations. In Singapore, a startup launched an agent named Manus earlier this year. It can write and deploy computer code with little help from humans. Offices are also using agents to go through documents, handle customer emails, and support technical staff.
Reports suggest that by the end of 2025, one in four large companies will test agents in some form. Within two years, half of them may use these systems regularly. Experts compare this rise to how spreadsheets changed business practices decades ago.
Researchers are actively discussing the growth of the Agentic Web, where different agents communicate with each other. For example, a finance agent could adjust spending plans after receiving updates from a shopping or travel agent. The goal here is to create networks where digital helpers can cooperate instead of working in isolation.
Also Read: AI Agents are Rising, Who Will Keep Them in Check?
Several reasons explain why the use of agents has increased so dramatically:
New language models are capable of deeper reasoning and can work with images, audio, and text together.
Running these systems is much cheaper, which allows smaller companies to use them.
Open-source projects are giving developers free tools and examples to speed up the process of building agents.
Workplaces are under pressure to cut costs and save time, and agents can take over routine tasks.
Despite the excitement, there are problems. Agents sometimes give wrong answers or take too long to process information. They may struggle with creative thinking or make decisions without questioning their own logic. Security is another concern. If an agent has access to important data or financial systems, a mistake could cause serious damage.
Technology leaders believe 2025 will be a turning point for AI agents. Major companies are investing in these systems to manage office work, connect with online services, and support employees. In India, most business leaders say they plan to introduce agents in the coming year.
Large language models have moved from being tools for generating text to becoming the base of intelligent systems that can act on their own. These agents have started managing tasks that once needed constant human effort. If progress continues, they may become an important part of both workplaces and everyday life.
