AI Agent Examples: What Are They, and How Do They Work?

What was once a futuristic concept—AIs making real decisions and automating complex tasks independently—is now our reality. “AI agents” is the latest buzzword you may have seen floating around 𝕏 and such, and while many people swear they have the most advanced AI agents, a lot of them either are a downright sham. But the AI agents market is, in fact, developing rapidly, with a projection to grow from USD 5.1 billion in 2024 to USD 47.1 billion by 2030.

But what exactly is an AI agent, and which companies are genuinely putting them into practice? Let’s dive into some real-life AI agent examples in action to understand the hype.

What are AI agents?

AI agents are autonomous systems designed to perform tasks, make decisions, and learn from interactions to achieve specific goals. They range from simple information retrieval bots to complex agents that automate workflows or operate without supervision. They are either digital robotic assistants that can observe (analyze data), think (make decisions), and act (execute tasks).

With the crypto agents taking trading by storm, and plenty of people claiming they have the best agent out there on 𝕏, you might be led to believe that AI agents run on the browser only. But no. AI agents can also run on hardware. We’ll list some examples of that.

Some of the most common AI agent examples include customer service bots, which handle queries and improve with each interaction, and personal assistants like Siri, Alexa, and Google Assistant, which help with tasks from setting reminders to planning trips. In healthcare, AI agents monitor vitals, suggest treatments, and assist surgeons in real-time, while in finance, they analyze markets and offer investment advice. Autonomous vehicles use AI agents to navigate roads, process sensor data, and make split-second driving decisions—all without human input.

Crypto traders use agents to make decisions and HODL (truth be told, software that automatically buys or sells securities has been around for years, so “AI crypto agents” seems like a re-branding).

AI agent examples: Real-world examples of AI Agents

AI agents are becoming increasingly common across various industries, so let’s check some AI agent examples currently in use.

Deep Research

Our first case when referring to the AI agent examples is OpenAI’s Deep Research , a tool designed to quickly scan, synthesize, and reason through online content. According to Kevin Weil , OpenAI’s chief product officer, it can do research that would normally take a human anywhere from 30 minutes to 30 days in just five to 30 minutes. Deep Research can search the web, analyze text, images, and PDFs, and adapt as it acquires new information. While specifics are still evolving, OpenAI’s Mark Chen claims that Deep Research can generate “a comprehensive, fully cited research paper.” But some commentators don’t agree as much. We’ll have to see if Deep Research can bring all these promises home. Google was quick enough to launch their competitor product. Their devs certainly underwent some Rockstar Games-worthy crunch.

Waymo

Waymo is the ideal AI agent example. Its software is used by self-driving cars. These vehicles rely on a mix of AI agents: Some make decisions, others help with navigation, while some respond in real-time, and others improve over time through learning. The cars are currently running in cities like Phoenix, San Francisco, and Los Angeles. These use AI-driven perception, mapping, and decision-making systems to navigate roads, avoid obstacles, and pick the best routes. Their system adapts automatically to new road conditions and traffic laws to constantly improve through machine learning. Something like giving Waze to a computer.

Waymo has been around for long enough to spark a conflicting dialog: First, the usual “Yes, I’ve heard about those self-driving cars; it’s spectacular!” but also the “So when are you shipping these in for everyone?” It appears that these cars are not dependable enough. Which explains why making AI agents more reliable is literally a multi-million dollar market .

Nightingale Security

Our last AI agent example is Nightingale Security’s software. This company supplies autonomous drones for surveillance, security, and emergency response. Their drones make real-time decisions based on data from cameras, sensors, and alarms. This allows them to patrol set routes and respond to threats without requiring human control. The AI behind these drones analyzes the data to adjust flight paths, alert security teams, and improve patrol patterns. Like all AI agents, even those that run on the browser or sprint through Super Mario World , this system also learns from past events to better its performance, like threat detection and how fit it is to respond. They can also integrate with existing alarm systems to address security breaches or incidents. Based on the vendor’s FAQ , this is evidently an AI agent running on their hardware.

So, you don’t need your AI agent to work via your browser. That’s a big takeaway.

Deploy your AI Agent with Genezio

Got an AI agent idea? Whether you’re building a financial assistant, a healthcare chatbot, or the next-gen self-driving tech, Genezio makes it easy to deploy, scale, and sell your AI solution. We simplify the process of building and hosting applications by offering a serverless architecture so you don’t have to worry about infrastructure—if your AI agent blows up overnight, Genezio will keep it running smoothly. Focus on building game-changing AI—we’ll handle the rest. We also support plenty of Python frameworks .

Ready to deploy? Sign up for Genezio today. It’s free.