The agentic era of artificial intelligence has arrived. Billed as “the next big thing in AI research,” AI agents are capable of operating independently and without continuous, direct oversight, while collaborating with users to automate monotonous tasks. In this guide, you’ll find everything you need to know about how AI agents are designed, what they can do, what they’re capable of, and whether they can be trusted to act on your behalf.
What is an agentic AI?
Agentic AI is a type of generative AI model that can act autonomously, make decisions, and take actions towards complex goals without direct human intervention. These systems are able to interpret changing conditions in real-time and react accordingly, rather than rotely following predefined rules or instructions. Based on the same large language models that drive popular chatbots like ChatGPT, Claude, or Gemini, agentic AIs differ in that they use LLMs to take action on a user’s behalf rather than generate content.
AutoGPT and BabyAGI are two of the earliest examples of AI agents, as they were able to solve reasonably complex queries with minimal oversight. AI agents are considered to be an early step towards achieving artificial general intelligence (AGI). In a recent blog post, OpenAI CEO Sam Altman argued that, “We are now confident we know how to build AGI as we have traditionally understood it,” and predicted, “in 2025, we may see the first AI agents ‘join the workforce’ and materially change the output of companies.”
Marc Benioff hailed AI agents’ emergence as “the third wave of the AI revolution” last September. The “third wave” is characterized as generative AI systems outgrowing being just tools for human use, instead, evolving into semi-autonomous actors capable of learning from their environments.
“This is the biggest and most exciting piece of technology we have ever worked on,” Benioff said of the company’s newly announced Agentforce platform, which enables the company’s enterprise customers to build digital stand-ins for their human customer service reps. “We are just starting.”
What can AI agents do?
Being designed to take action for their users, AI agents are able to perform a staggeringly wide variety of tasks. It can be anything from reviewing and automatically streamlining computer code to optimizing a company’s supply chain management across multiple vendors to reviewing your calendar availability then booking a flight and hotel accommodations for an upcoming business trip.
Claude’s “Computer Use” API, for example, enables the chatbot to effectively mimic the keyboard strokes and mouse movements of a human user, enabling Claude to interact with the local computing system. AI agents are designed to tackle complex, multi-step problems such as planning an eight-course dinner party by establishing a menu after contacting guests for their availability and potential allergies, then ordering the necessary ingredients from Instacart. You’ll still have to cook the food yourself, of course.
Where can I see an AI agent in action?
AI agents are already being rolled out across myriad industries. You can find agentic AI in the banking system where it assists with fraud detection and automated stock trading tasks. In the logistics industry, AI agents are used to optimize inventory levels and delivery routes as market and traffic conditions change. In manufacturing, AI agents are already helping to enable predictive maintenance and equipment monitoring, ushering in an era of “smart” factory management. In healthcare, AI agents help patients streamline appointment scheduling and automate prescription refilling. Google’s automotive AI agent will even provide near-real-time information about local landmarks and restaurants for Mercedes’ MBUX entertainment and navigation system starting with the next model year’s CLA.
The technology is also being applied to enterprise business and Salesforce is far from the only SaaS company to embrace AI agents. SAP and Oracle both have similar offerings for their own customers.
It should come as no surprise then that the industry’s top companies like Google, Microsoft, OpenAI, Anthropic and Nvidia are all racing to develop and deploy AI agents for the business and consumer markets as well. In November, Microsoft announced Copilot Actions, which would see Copilot-based agents integrated throughout the company’s 365 app ecosystem, and began rolling the feature out to business and enterprise users in January 2025.
In November, Google Cloud announced its AI agent ecosystem program, dubbed AI Agent Space, which, like Agentforce or Google’s other AI agent platform, Vertex AI, enables business customers to develop and deploy their own customized AI agents. Nividia unveiled its Nemotron model families, designed specifically for agentic AI tasks, at CES 2025 earlier this month.
For its part, OpenAI recently unveiled its new Tasks feature for ChatGPT which allows users to set future reminders and regularly-scheduled tasks (like weekly news roundups) for the chatbot to perform at a later date. The company is also rumored to be working on an AI agent of its own, codenamed: Operator, which is expected to be released at some point in January 2025.
Are AI agents safe to use?
That depends on your definition of “safe.” Because agentic AI systems are built atop hallucination-prone large language models susceptible to adversarial attack, AI agents are themselves prone to hallucinations and can be tricked by malicious actors to behave outside of their established safety guardrails. A 2024 study from Apollo Research, for example, found that tasking OpenAI’s o1 model with achieving a goal “at all costs” led the AI agent to try to disable its monitoring mechanism before copying “what it believes to be its weights to a new server and then lie about it to its developers,” claiming it suffered “technical errors.”
Of course, when a chatbot boofs its answer, the stakes are relatively low (unless that user is a lawyer or Google, mind you), compared to what would happen if an AI agent hallucinates data about its automated stock trading strategy. As with all generative AI, users need to be vigilant about what information (be it financial, medical, or personal) they share with chatbots and LLMs.