Artificial intelligence may not have changed the world yet, but it has transformed many everyday tasks. AI tools can help you brainstorm, provide around-the-clock customer service, and identify patterns in vast amounts of data.
AI agents, a subset of AI tools, act independently as intelligent intermediaries between the digital world and the physical world to achieve complex goals. Learn more about the types of AI agents and how to use them to reach your business goals.
What are AI agents?
AI agents, also called intelligent agents, are a distinct category within the broader field of artificial intelligence. Unlike other types of AI systems, agents are designed to operate autonomously, often in real-world environments. They perceive their surroundings, interpret data, and make decisions based on predefined goals without requiring constant human intervention.
This autonomy sets them apart. While other AI systems excel at specific tasks like pattern recognition or language translation (where human prompts spur the system into action), agents can actively navigate complex situations, adapt to changing circumstances, and even learn from their experiences. This makes them ideal for applications like self-driving cars, intelligent robots, and decision-making systems in various industries.
AI agents vs. AI tools: What’s the difference?
AI agents differ fundamentally from AI tools in their level of autonomy, although both may rely on natural language processing and machine learning. While AI tools are powerful for specific tasks like data analysis, answering questions, or translating, they require human input and direction.
AI agents, on the other hand, operate autonomously, making decisions and taking action to achieve predetermined goals without constant human intervention. Think of AI tools as powerful calculators, while AI agents are like self-driving cars that navigate and make decisions on their own.
Benefits of AI agents
Here are some of the benefits of AI agents:
Automation
AI agents can handle repetitive tasks or gather information much faster than humans, improving efficiency. For example, industrial robots guided by AI agents can repeatedly perform tasks in factories with high precision, increasing productivity and efficiency in manufacturing and business processes.
Availability
Unlike humans, AI agents can function without breaks or sleep, making them suitable for tasks requiring constant monitoring.
User experience
AI agents can personalize interactions and provide tailored recommendations or assistance. Virtual assistants can learn your preferences and adjust their responses accordingly, offering a more convenient and user-friendly experience. AI agents on e-learning platforms can personalize learning paths based on a student’s strengths, weaknesses, and learning pace.
Decision-making
AI agents analyze vast amounts of data to identify patterns, trends, and correlations that might go unnoticed. This can be especially valuable for financial institutions, where AI agents spot market trends in real time and make informed investment decisions.
In the case of scientific research, AI agents analyze complex data to accelerate discovery and innovation. AI models generate data visualizations that help researchers better understand the data and explore it in detail.
Security
AI agents play a crucial role in safety and security measures, from self-driving cars to fraud detection. And AI agents monitor networks for cyber threats, and take proactive steps to prevent cyberattacks.
Types of AI agents
The primary types of AI agents include:Goal-based
These agents have a specific goal they are trying to achieve. They can perceive their situation, take actions, and evaluate if those actions move them closer to their goal. For instance, a chess-playing AI agent considers different moves and chooses the one that brings it closer to checkmating the opponent.
Utility-based
These agents take a more nuanced approach to decision-making. They assign values (utilities) to different outcomes and choose actions that maximize their expected utility. A self-driving car with a utility-based system might consider an array of factors—like fuel efficiency versus speed—when choosing the best route.
Learning
Learning agents are programmed to improve their performance while learning from successes and failures, adjusting decision-making for business processes as they go.
Reinforcement learning agents like AlphaGo (a program that excels at the game Go) learn through trial and error, receiving automatic confirmation for successful actions. Another example is a spam filter using specific keywords to identify unwanted emails.
Planning
These AI agents create plans to achieve complex goals. They analyze various possibilities, evaluate potential outcomes, and choose the course of action with the highest likelihood of success. An intelligent planning agent might be used in logistics to optimize delivery routes, taking into account factors like traffic, distance, and driver availability.
How to use AI agents
Explore some of the many ways you can use AI agents:
Education
AI agents can double as intelligent tutoring systems. These AI-powered tutors personalize learning experiences for students, provide feedback and guidance, and answer questions at their own pace. For example, Carnegie Learning’s LiveHint AI focuses on middle and high school math, and it leverages datasets on student work and interactions to provide personalized hints and explanations as students work on problems.
A more familiar example would be Duolingo. An AI chatbot within the language learning app lets users practice speaking and build comprehension skills through conversational interactions.
AI agents can also automatically grade certain types of assessments, freeing up teachers’ time for more individualized instruction.
Health care
AI agents have numerous uses across health care, starting with diagnosis. AI agents that analyze medical images (such as X-rays or MRIs) help doctors in diagnosing diseases or identifying abnormalities. AI agents that analyze patient data can suggest treatment plans and predict potential outcomes.
Along the way, AI agents can also act as virtual nurses by answering patients’ basic questions and providing health information. In certain cases, an AI chatbot like Woebot will even offer emotional support, tracking your mood over time and helping you identify patterns and triggers for stress or anxiety.
For medical research, AI agents are becoming practical for drug discovery. AI agents analyze vast datasets to accelerate pharmaceutical development, helping identify potential targets for new treatments.
Logistics
Delivery drones are still a work in progress, but AI agents are helping them get there. AI agents guide autonomous drones for last-mile deliveries, optimizing routes and ensuring safe navigation.
Elsewhere on the road, AI agents that analyze traffic data in real time optimize traffic flow, reduce congestion, and improve overall traffic management. AI agents are crucial for self-driving cars as they perceive surroundings through cameras and sensors, make navigation decisions, and control the vehicle’s movement.
Marketing
While both AI tools and AI agents offer valuable capabilities for marketers, AI agents hold a significant advantage due to their inherent autonomy. AI tools, like data analysis platforms or sentiment analysis engines, require human interpretation to be effective. Marketers need to define the parameters, interpret the results, and then translate them into actionable insights.
AI agents, on the other hand, operate independently. They can analyze vast amounts of data, identify patterns and trends, and make decisions based on predefined goals without human intervention. This allows them to automate repetitive tasks, personalize marketing efforts, and adapt to changing customer behavior and market trends.
Retail
Some customer service chatbots are AI agents trained to answer questions, solve issues, or direct customers to appropriate resources. AI agents can be implemented to power virtual assistants, which perceive voice commands, access information through the internet, and respond accordingly. Ecommerce platforms can use AI agents to recommend products based on browsing history and purchase patterns.
Use AI agents to set up automated greetings for customers initiating chats, as well as reroute basic inquiries to appropriate departments based on keywords or predefined criteria. This is exactly the role of Shopify Inbox. It’s a messaging tool that lets businesses chat with customers as they shop, and with an assist from Shopify Magic you can review, edit, and respond to drive top-of-funnel conversions, turning more chats into checkouts.
Rennie Wood, founder of Wood Wood Toys, an online business specializing in eco-friendly and developmentally stimulating wooden toys, considered Shopify Inbox’s AI capabilities when changing his marketing strategy—a decision he says cut down on the number of emails he needs to handle personally.
“With Shopify Inbox, we can deliver a good customer experience and answer shoppers’ questions accurately, more often, and faster,” Rennie says. “If somebody reaches out with a problem, I bet eight times out of 10 we can solve it and win the sale.”
Robotics
AI agents are the backbone of robotics, from industrial automation to predictive maintenance to quality control. AI agents control robotic arms in factories with high precision, performing tasks like welding, assembly, and painting. AI agents analyze sensor data from machines to predict potential failures and schedule maintenance proactively, avoiding extra costs and ensuring smooth operations. AI agents with image recognition capabilities can inspect products for defects, ensuring consistent quality control throughout the manufacturing process.
AI agents FAQ
What does an AI agent do?
Today’s AI agents gather information about their environment through sensors or by accessingdata. AI agentsprocess this information using algorithms, learning and adapting as they go. This allows them to improve their performance over time and handle complex tasks.
What is an example of an AI agent?
Programmers build agents to learn from their environments and respond to situations autonomously. This can mean controlling a robotic arm in a factory or recommending products to customers on an ecommerce platform. Apple’s Siri voice assistant is an example of an AI agent—over time, it learns about the users that interact with it, providing better recommendations and answers to questions.
Will AI agents replace workers?
AI models and agents are likely to change the nature of work, not necessarily eliminate jobs. AI excels at automating repetitive tasks, so this could lead to job reductions in sectors such as manufacturing, customer service, and data entry. On the other hand, many new roles will emerge, such as building AI agents and maintaining AI systems. Human intervention will remain essential in all fields.
