With rapid improvements in AI, things are quickly moving away from AI chatbots to action-driven AI agents. AI agents are ready to change our everyday lives and how we interact with services. They don’t just generate text or images, but make decisions and act on them. So, to demonstrate agentic applications, we have compiled powerful real-world examples of AI agents in 2025. From computer-using AI agents to autonomous vehicles, we have mentioned all of them here.
1. Computer-Using AI Agents
The first real-world example of AI agents that we have on the consumer side is Computer-Using AI agents. Leading AI companies are developing Computer-Using AI agents to automate and achieve tasks on the web and local computers. OpenAI’s Operator AI agent is the most noteworthy one as it can autonomously perform tasks on behalf of the user on the web.
OpenAI’s Operator AI agent can navigate websites, click buttons, fill out forms, type text, and scroll pages to complete any task you throw at it. It basically analyzes the active screen and decides where to click next or perform a suitable action. You can use it to book flights, hotels, order groceries, fill out forms, and more.
That said, for sensitive tasks like making payments or entering CAPTCHAs, you still need manual intervention. It’s available to ChatGPT Pro users, which costs $200 per month.
Other than that, Anthropic has developed the Computer Use AI agent, which uses Claude to perform local operations on your computer. It can also browse the web and perform tasks, just like OpenAI’s Operator. The AI agent is currently in preview and requires Anthropic’s API access.
On the other hand, Microsoft has introduced its Computer-using AI agent on Copilot Studio, but it’s aimed at enterprise customers. It can interact with both web and desktop apps, and can complete tasks by visually analyzing the screen. Even without special APIs, the AI agent can handle complex tasks.
Note that Google is also developing Project Mariner, which is a similar AI agent that can perform tasks in the Chrome browser, but it’s currently under development.
2. Knowledge-Based AI Agents
Next, Knowledge-based AI agents are another real-world example of AI agents in 2025. OpenAI’s Deep Research AI agent is available to consumers on ChatGPT, and it can perform complex, multi-step research for you, like a professional analyst.
The Deep Research AI agent plans what information it requires, goes to the web to curate high-quality information, and does a deep analysis to generate a comprehensive report on any subject.
As it uses the powerful ChatGPT o3 reasoning model with lots of tools, the generated reports are more fleshed out. The Deep Research AI agent can analyze images, diagrams, tables, PDF files, and even user-uploaded files to gather more insights. Best of all, the generated reports have in-line citations so you can quickly verify the information on ChatGPT.
Other than that, Google’s Deep Research AI agent in Gemini does the same thing, and it’s available for free. Anthropic has also released the Research tool in Claude that can research on the web and extract information from your personal Google Workspace documents.
China’s Manus AI agent, which is currently invite-only, is a general AI agent that can perform data analysis, deep research, among other things. It can also run code in a sandbox to analyze local files and generate comprehensive reports for you.
3. Coding AI Agents
In the programming world, Coding AI agents are making big waves and stand out as real-world examples of AI agents. Anthropic’s Claude Code is an agentic coding tool that works within the terminal. It can understand your codebase, edit files, fix bugs, build new features, run tests, and do a lot more. Claude Code can even use Git to push commits and merge conflicts automatically.
Claude Code uses the Claude 3.7 Sonnet AI model under the hood, which does extended thinking before performing actions. Apart from that, OpenAI’s latest Codex CLI tool is agentic in nature and operates from the terminal, just like Claude Code. Codex CLI has three modes — Suggest, Auto Edit, and Full Auto. The Full Auto mode can autonomously read, write, and execute commands without human approval.
Next, Cursor is an AI-powered code editor, and its agent can complete coding tasks while keeping programmers in the loop. It can automatically detect errors, apply fixes, and run commands. Devin is another agentic AI tool for developers who want to complete software development end-to-end. It can plan, generate context-aware code, debug, and solve complex coding errors. Devin also has support for multi-agent operations.
4. Conversational AI Agents
For consumers, voice-based conversational AI agents are the best real-world examples of AI agents. The upgraded Gemini voice assistant on Android, which is powered by an AI model, is much more agentic than traditional voice assistants. For example, the Gemini voice assistant can reason, maintain context across multi-turn conversations, and use function calling to execute the action.
Recently, the Gemini voice assistant on Android received support for multiple actions at once. You can ask Gemini to find when a particular train arrives and set a reminder using the Calendar app, in one go. There are many multi-step actions you can perform on your Android phone.
Apart from that, the Perplexity voice assistant on Android is again action-driven as it can find information using its LLM, and send emails or set contextual reminders. It can also book Uber and restaurants through voice input which demonstrates its agentic capability.
The new Alexa Plus voice assistant by Amazon is again an action-driven AI agent. It can execute tasks like booking an appointment, finding a service provider, managing your calendar, ordering groceries, and more. While Apple has also teased an AI-powered Siri that can perform actions, it’s delayed and may be released by the end of 2025.
5. Security AI Agents
Now, let’s talk about AI agents in the cybersecurity field. In this field, AI agents are being leveraged for threat detection and analysis, automatically responding to security incidents, behavioral analysis of systems, automated triaging of alerts, and more. Microsoft recently released Security Copilot with AI agents which can assist companies in areas such as phishing, data security, identity management, and more.
Microsoft Security Copilot can automatically detect phishing alerts and cyberattack signals. There are six different agents designed to process high-volume security tasks. Apart from that, Google also unveiled semi-autonomous Gemini security AI agents on Google Cloud to manage end-to-end security operations. It can help enterprise customers analyze malware, and investigate alerts.
6. Healthcare AI Agents
AI agents are revolutionizing the healthcare space, showcasing a great real-world example of AI agents in action. Healthcare AI agents can automate a lot of administrative workflows like scheduling appointments with doctors, managing patient records, billing, processing insurance claims, and handling patient inquiries. So besides medical-related diagnostic support, AI agents can be highly effective on the administrative side too.
On the diagnostic side, Healthcare AI agents can analyze X-rays, MRIs, and CT scans with speed and accuracy. Just recently, we learnt that a German-based company called Vara has developed an AI-powered software to detect breast cancer early on. Other than that, AI agents can analyze patient data and help in clinical decisions, reducing the burden on doctors.
Next, AI agents can engage with patients and deliver personalized health advice. Google has developed Articulate Medical Intelligence Explorer (AMIE) which offers a conversational diagnostic research AI system. Other than that, medical institutions can create specialized AI agents on Vertex AI for automating administrative and medical workflows.
7. Customer Support AI Agents
Customer support AI agents offer the most practical real-world example of AI agents. In fact, AI agents are already serving customers and answering queries around the world. AI chatbots, with access to customers’ history and order details, can handle customer queries 24×7. With support for AI agents that can check order status, company policies, etc., businesses can effectively leverage AI agents to resolve customer queries.
In this area, nearly all major cloud providers offer AI agents to handle customer interaction. Google has Customer Engagement Suite that includes AI agents, Microsoft provides Microsoft Copilot for Service, Amazon provides Amazon Connect, and Salesforce has Einstein Bots and Salesforce agents. Basically, these AI chatbots with agentic capabilities can transform custom support and can easily handle routine tasks at scale.
8. Finance AI Agents
From fraud detection to analyzing financial data, Finance AI agents can automate a lot of tasks. As we all know, AI systems are trained on a large amount of financial data, news, and economic data from the past. This allows Finance AI agents to perform a thorough analysis of companies and manage customers’ portfolios.
For instance, Finance AI agents can identify trading opportunities based on the risk tolerance of the user. Financial companies can use AI agents to monitor transactions and detect fraudulent activities. Not only that, but AI agents can be used to accurately measure the creditworthiness of individuals by analyzing multiple credit reports.
Besides that, Finance AI agents can automate repetitive back-office tasks like data entry and invoice processing which would reduce operational costs for the company. Big financial institutions such as JPMorgan Chase, Bank of America, Goldman Sachs, etc., are already utilizing AI across the board for fraud detection, risk management, client servicing, and more.
9. Supply Chain AI Agents
To give you another real-world example of AI agents, take a look at supply chain management. Supply Chain AI agents are designed to track shipments, monitor inventory, analyze customer demands, and forecast future trends. AI agents are best suited for demand forecasting as they analyze historical sales data, market trends, and the larger economic indicators to accurately predict demand.
In addition, Supply Chain AI agents can perform route optimization by analyzing real-time traffic data, weather conditions, etc., and re-route vehicles to reduce operational cost. It can also help in procurement, automating warehouse management, and risk management of suppliers. Amazon uses AI agents in its supply chain to manage its network of warehouses. Walmart is also using AI agents for optimizing routes and logistics operations.
10. Autonomous Vehicles AI Agents
Finally, we come to our final example of AI agents which is Autonomous vehicles. Autonomous vehicles operate without human intervention and make decisions solely based on sensor data. They are intelligent AI-powered systems that operate in a dynamic world. Autonomous vehicles use multiple cameras, radar, and LiDAR to gather real-time data and create an internal world model based on their surroundings.
These vehicles analyze the data using AI to make an informed decision as to where to stop, change lanes, accelerate, or slow down. Google’s Waymo autonomous cars are considered Level 4 (fully autonomous) and uses LiDAR along with cameras and radar to navigate traffic and offer a driverless experience. It’s already available in San Francisco, LA, and Phoenix.
Tesla cars are also examples of AI-powered agentic vehicles, but they are not fully autonomous (Level 2). It still requires driver supervision as it mostly uses a vision-based approach to detect obstacles.
So these are the 10 best real-world examples of AI agents in 2025. Action-driven AI agents are going to change the world as they become better and reliable in the future. Google has already stated that we are entering the agentic era, and things are only going to improve going forward. So what do you think about AI agents? Let us know in the comments below.
