What Are AI Agents? Here’s How They Can Help You Get Stuff Done

OpenAI leader Sam Altman kicked off the year by declaring that 2025 would be when AI agents “join the workforce.” And he predicted that their addition will “materially change the output of companies.” It’s a sentiment shared by many AI industry luminaries, including Nvidia CEO Jensen Huang, who called agents “a multi-trillion-dollar opportunity.” (This type of technology is sometimes referred to as “agentic AI.”) But while the AI industry hypes up its shiny new toys, the rest of us are left with an important question: What the heck is an AI agent? What is an AI agent? OpenAI defines AI agents “as systems that independently accomplish tasks on behalf of users.” Olivier Godement, who heads up OpenAI’s API product team, says that an AI agent has been equipped with a specific purpose, a specific workflow to follow, and specific tools that enable it to take actions. That special purpose could be serving as a customer support specialist, and the actions it could take could be searching through an internal database, googling information, running a piece of code, or controlling a computer or internet browser. Essentially, agents are AI systems that can accomplish computer-based tasks for you. What’s the difference between an AI agent and a chatbot? Godement recommends thinking of agents as being the next evolution of chatbots. Apratim Purakayastha, general manager of Talent Development Solutions at online education platform Skillsoft, says that AI models become AI agents when they’ve been “enriched” with additional data and capabilities. You could direct an AI agent to continuously monitor prices for flights on a given date, or analyze job applications against an internal rubric. By combining the raw intelligence of AI models with data not included in its original training, says Purakayastha, a whole new world of opportunities arise. When they were originally released, chatbots like ChatGPT only existed as a channel for people to converse with AI models, but interactions were limited to the information the model had been trained on. Now, by activating the app’s Deep Research mode, users can instantly transform the chatbot into an AI agent, capable of searching the internet for minutes at a time and developing reports based on its findings. The AI model stays the same, but the added gadgets make it more useful. How have businesses used AI agents? According to Purakayastha, “gadgets” are actually a pretty good way to think about what makes AI agents different from AI models. Think about another notable agent: James Bond. Just like 007 receives a mission and gets equipped with gadgets specifically designed to help him carry out that mission, AI models are given a purpose and then equipped with the tools needed to carry out that purpose. A more mundane comparison is to an old-school travel agent, who books flights or hotel rooms for clients. One of the most successful examples of a company making use of an AI agent comes from software developer platform Replit. In 2024, the startup released an AI agent, built with an Anthropic Claude model, that can program applications from natural language prompts. Since the agent’s release, Replit has seen its revenue grow by over 10x. Other potential use cases for agents include providing customer support services, enabling more efficient data analysis, and, as recently demoed by Meta, empowering digital sales professionals. Can AI agents replace employees? One thing that AI agents aren’t? Virtual employees. Agents are intended to be used for very specific tasks, and shouldn’t be expected to act as a replacement for a human employee. Instead, says Purakayastha, agents should be thought of as a “virtual facet of an employee” or an “automated process.” A single agent should ideally only be responsible for completing a single step in a workflow, like approving or denying refunds by analyzing internal policy documents. You wouldn’t want to give the refund agent access to any unnecessary context or tools, because it would result in the agent becoming less focused on its specific task. Agents can be programmed to hand off control to each other, so you can essentially create a chain of agents that, when linked together, accomplish tasks. This process, which OpenAI’s Godement refers to as “separation of concerns,” also makes it easier to observe and optimize the effectiveness of agents, since they only need to be judged by their ability to complete a single step of a process. Can my business start using AI agents? AI agents are still in their infancy, and Godement cautions that businesses should “start small” when building agentic applications. Godement recommends identifying a workflow that you think could be more efficient, breaking down all the individual steps, and developing separate agents to handle each of those steps. “There will be a time when you can reinvent your whole product and company with agents,” he says, “but start small with one team of early adopters who are super passionate. You need one undeniable success story.” BY BEN SHERRY @BENLUCASSHERRY