Posted 2 hours ago2 hr comment_11730 An AI agent is an artificial intelligence tool that can take actions autonomously within a software environment. While on the surface they might seem similar to other popular AI tools — like ChatGPT or Midjourney — there’s one specific difference between them. AI agents act without human input. As advanced as tools like ChatGPT might be, they can’t act without a person making a request or programming some kind of action. An AI agent can perform complex tasks without any human intervention. AI agents are rapidly becoming a vital technology for automating repetitive tasks, streamlining analysis, and more. In this guide, you’ll find definitions of the five types of AI agents and common examples of workflows that use AI agents. The 5 types of AI agents Despite the wide variety of AI agents across tools, they usually fall within the five following categories. Simple reflex agents This is the simplest type of AI agent. It operates using a simple, “if this, then that” structure, allowing it to perform a range of simple automations. Notably, these AI agents don’t use historical data or future predictions to take action. They only process information that is immediately available to them. An AI agent that automatically sets up a meeting for a sales agent when a lead comes in is an example of a simple reflex agent. Model-based reflex agents A model-based reflex agent can take similar actions to a simple reflex agent with one key difference: an internal state based on a breadth of information. Before these agents take action, they can review historical data and make predictions based on existing trends. This allows them to take on more complex tasks and make better decisions. Goal-based agents Where simple reflex agents take action based on the stimulus they receive as they receive it, goal-based agents work backwards from an established goal. These agents choose from possible actions according to what is most likely to lead to a pre-determined goal. The best example of goal-based AI agents is a self-driving car. The car has a specific destination for its goal, and it makes decisions along the way to get there as efficiently and safely as possible. Utility-based agents Utility-based agents take automatic action to maximize a specific value. A user will turn a desired income into a quantifiable value that the AI agent can optimize for. When faced with a decision, the agent will pick the option that leads to the greatest increase in that value. An AI agent that automatically trades stocks to maximize profit is an example of a utility-based agent. Learning agents A learning agent is an AI agent that improves its own models over time. By taking in information from its environment, including the consequences of previous decisions, this agent essentially “learns” its way towards becoming more effective. An AI agent that uses someone’s viewing history to make better content recommendations over time is an example of a learning agent. 10 examples of AI agents There are hundreds of possible uses for AI agents. Here are just a few examples to inspire you. Content algorithms Platforms like YouTube and Netflix use AI agents to automatically recommend content to users that aligns with their interests. This is done by identifying trends in a user’s viewing history and making predictions about which videos they’re most likely to engage with. These algorithms are almost completely independent. Dynamic pricing systems Adjusting prices in real-time, based on factors like location and supply, can have a massive impact on profit margins. An AI agent can be used to maximize profit by tailoring prices to real-world circumstances on the fly, adapting to purchase trends. Financial trading agents Financial markets process a massive amount of information. Feeding an AI agent with all that data doesn’t just allow it to make better predictions for individual financial assets, it also gives them the background they need to make trades and financial decisions. Project management app automation Many project management platforms have automations that save their users precious time. An AI agent allows these apps to have more complex automations, potentially taking a long series of actions autonomously. Self-driving cars A self-driving car is the perfect example of a goal-based agent. With a destination pre-selected, the car automatically makes turns, regulates its speed, and stops at lights as needed to reach that destination. These cars use AI agents to make these decisions without any human input. Fraud detection agents Fraud detection relies on spotting variances in financial transactions. These can be transactions that are far larger than usual amounts, that come from atypical sources, or are sent to strange destinations. AI agents can analyze massive amounts of financial data to identify trends and spot variance that signals potential fraud. Customer support bot Many organizations already use AI chatbots to automatically answer common customer requests and even automate basic actions. Using AI agents in these roles allows organizations to automate even complex customer support tasks, like opening a ticket and populating the right fields in a customer support tool from a single customer request. Sales agent bots AI agents can answer repetitive questions from prospects, qualify them for future pipeline stages, automatically update contact information in your CRM, and more. These agents can streamline lead generation and qualification processes, meaning your salespeople dedicate their time to top-quality prospects. Training agent Whether you’re training salespeople, customer success agents, or marketers, an AI agent can create scenarios, provide feedback, and guide trainees through complex problems. Digital marketing assistant An AI agent can act like an extra marketer, analyzing past campaigns, planning new initiatives, and even making tactical decisions like adjusting budgets for paid ad campaigns. How integrations make AI agents better While AI agents are incredibly powerful tools, they often have a serious limitation. They only operate within a limited number of systems. Salesforce Agentforce, for example, only acts within your Salesforce environment. While that allows it to automate a ton of actions within Salesforce, it means your agents are limited when dealing with complex workflows that cross tools. Unless you use the right integrations. Unito integrations let users create a two-way sync for over 60 tools, from Salesforce to Smartsheet and Jira. When paired with AI agents, these integrations allow you to automate even the most complex workflows, leaving your employees with more time to handle mission-critical tasks. Want to see what Unito can do? Meet with our team to see what Unito integrations can do for your AI-powered workflows. Talk with sales FAQ: AI Agents examples What is an AI agent? An AI agent is a type of AI tool that can perform actions without human input. A person will usually be involved in setting up the agent, determining its objectives, and even setting the limitations of its actions, but the agent will act autonomously. AI agents typically act within a single software environment, the right software integrations can allow them to operate across more tools. What are the 5 types of AI agents? The five types of AI agents are: Simple reflex agents, which take immediate actions based on the stimulus they receive and no other data. Model-based reflex agents, which evaluate historical data and predictions of future trends to make better decisions. Goal-based agents, which work backwards from an established goal and take the best decisions to reach it. Utility-based agents, which work towards maximizing a quantifiable value used to represent a desired objective. Learning agents, which can dynamically improve their decision-making over time by learning from their own actions and their environment. Is ChatGPT an AI agent? No, ChatGPT isn’t an AI agent. It’s a large language model that answers prompts from humans in a chat interface. It can’t take actions autonomously on other platforms. Is Siri an AI agent? No, Siri isn’t an AI agent. It’s an AI assistant, which performs tasks in a similar way as an AI agent, but it isn’t autonomous. A user has to ask an AI assistant to perform a task, and that assistant serves as the go-between for them and the apps where those tasks happen. An AI agent, after it’s set up, acts on its own without any user input. View the full article
