Artificial intelligence may not have changed the world yet, but it has transformed many everyday tasks. AI tools help with brainstorming, providing round-the-clock customer service, and identifying patterns in vast amounts of data.
AI agents, a subset of AI tools, work independently as intelligent intermediaries between the digital and physical worlds to achieve complex goals. Learn more about the types of AI agents and how you can use them to achieve your business goals.
What are AI agents?
AI agents, also known as intelligent agents, are a distinct category within the broad field of artificial intelligence. Unlike other types of AI systems, agents are often designed to operate autonomously in real-world environments: they perceive their surroundings, interpret data, and make decisions based on predefined goals without the need for ongoing human intervention.
This autonomy is what sets agents apart: while other AI systems excel at specific tasks like pattern recognition or language translation (where human instructions initiate the system's actions), agents can also actively navigate complex situations, adapt to changing conditions, and learn from experience. This makes agents ideal for applications such as self-driving cars, intelligent robots, and decision-making systems across a range of industries.
What is the difference between an AI agent and an AI tool?
AI agents are fundamentally different from AI tools in their level of autonomy, although both may rely on natural language processing and machine learning. AI tools are powerful for certain tasks such as data analysis, question answering, and translation, but they require human input and direction.
AI agents, on the other hand, operate autonomously, making decisions and taking actions to achieve pre-determined goals without the need for human intervention. AI tools are powerful computing machines, while AI agents are like self-driving cars that navigate and make decisions on their own.
Benefits of AI Agents
The advantages of AI agents are:
automation
AI agents can perform repetitive tasks and gather information much faster than humans can, improving efficiency. For example, industrial robots guided by AI agents can perform tasks repeatedly in factories with high accuracy, making manufacturing and business processes more productive and efficient.
availability
Unlike humans, AI agents can function without breaks or sleep, making them well suited for tasks that require constant supervision.
User Experience
AI agents can personalize interactions and provide customized recommendations and assistance. Virtual assistants can learn user preferences and tailor their responses accordingly to provide a more convenient and user-friendly experience. AI agents on e-learning platforms can personalize learning paths based on students' strengths, weaknesses, and learning pace.
decision making
AI agents analyze vast amounts of data to identify patterns, trends, and correlations that might otherwise go unnoticed. This is particularly beneficial for financial institutions, where AI agents can understand market trends in real time and make informed investment decisions.
For scientific research, AI agents analyze complex data to accelerate discovery and innovation. AI models generate data visualizations to help researchers better understand and explore the data in more detail.
safety
AI agents play a key role in safety and security measures, from self-driving cars to fraud detection, and they monitor networks to detect cyber threats and take proactive measures to prevent cyber attacks.
Types of AI Agents
The main types of AI agents are:
Goal-based
These agents have a specific goal they are trying to achieve. They can perceive a situation, take actions, and evaluate whether that action will bring them closer to their goal. For example, a chess-playing AI agent will consider different moves and choose one that will bring it closer to checkmate its opponent.
Utility Base
These agents take a more nuanced approach to decision-making: they assign values (utilities) to different outcomes and choose the action that maximizes expected utility. A self-driving car with a utility-based system might consider different factors, such as fuel efficiency and speed, when choosing the optimal route.
learn
Learning agents are programmed to improve their performance as they learn from successes and failures, adjusting business process decisions over time.
Reinforcement learning agents like AlphaGo (a program that excels at the game of Go) learn through trial and error and receive automatic confirmation of successful actions. Another example is a spam filter that uses specific keywords to identify unwanted emails.
plan
These AI agents create plans to achieve complex goals: analyzing different possibilities, evaluating potential outcomes, and choosing the course of action with the highest chance of success. Intelligent planning agents might be used in logistics to optimize delivery routes, taking into account factors such as traffic volume, distance, and driver availability.
How to use AI agents
Here are some of the different ways you can utilize AI agents:
education
AI agents can also act as intelligent tutoring systems. These AI-powered tutors personalize students' learning experiences, provide feedback and guidance, and answer questions at the student's pace. For example, Carnegie Learning's LiveHint AI focuses on middle and high school math and leverages datasets on student work and interactions to provide personalized hints and explanations as students work through problems.
A more familiar example is Duolingo, an AI chatbot within the language learning app that allows users to practice speaking and develop comprehension through conversations.
AI agents can also automatically grade certain types of assessments, freeing up teachers' time for more personalized instruction.
health care
AI agents are used in many areas of medicine, including diagnosis. AI agents that analyze medical images (such as X-rays and MRIs) can help doctors diagnose diseases and identify abnormalities. AI agents that analyze patient data can suggest treatment plans or predict potential outcomes.
At the same time, AI agents can also act as virtual nurses by answering patients' basic questions and providing health information. In some cases, AI chatbots like Woebot can also provide emotional support, track mood over time, and identify patterns and triggers for stress and anxiety.
In medical research, AI agents are becoming practical for drug discovery: they can analyze huge data sets to accelerate drug development and help identify potential targets for new treatments.
logistics
Delivery drones are still in development, but AI agents are helping to make this a reality: they guide autonomous drones for last-mile deliveries, optimizing routes and ensuring safe navigation.
Elsewhere on the road, AI agents analyzing traffic data in real time optimize traffic flow, reduce congestion, and improve overall traffic management. AI agents are essential for self-driving cars, as they perceive their surroundings through cameras and sensors, make navigation decisions, and control the vehicle's movements.
marketing
While both AI tools and AI agents offer valuable capabilities to marketers, AI agents offer a significant advantage because they are autonomous in nature. AI tools, such as data analytics platforms and sentiment analysis engines, require human interpretation to be effective. Marketers must define parameters, interpret results, and 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 you 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, resolve problems, and direct customers to appropriate resources. AI agents can be implemented to power virtual assistants that recognize voice commands, access information over the internet, and respond accordingly. E-commerce platforms can use AI agents to recommend products based on browsing history and purchasing patterns.
Use AI agents to set up automated greetings for customers to initiate chats or route basic inquiries to the right department based on keywords or predefined criteria. This is exactly what Shopify Inbox does – a messaging tool that allows businesses to chat with customers while they shop. With the help of Shopify Magic, you can review, edit, and respond to drive top-of-funnel conversions and turn more chats into checkouts.
Rennie Wood, founder of Wood Wood Toys, an online business specializing in eco-friendly, developmental wooden toys, turned to Shopify Inbox's AI features when changing his marketing strategy, a decision he says reduced the number of emails he had to personally handle.
“Shopify Inbox helps us deliver a great customer experience and answer shopper questions more accurately, more frequently, and faster,” says Rennie. “If someone contacts us with an issue, I'd say eight times out of 10 we can solve the problem and close the sale.”
Robotics
AI agents are the backbone of robotics, from industrial automation to predictive maintenance and quality control. AI agents control robotic arms in factories with high precision to perform tasks like welding, assembly, and painting. AI agents analyze sensor data from machines to predict potential failures and proactively schedule maintenance, avoiding extra costs and ensuring smooth operations. AI agents with image recognition capabilities inspect products for defects and 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 and access to data. They use algorithms to process this information, learning and adapting as they go, improving their performance over time and enabling them to handle complex tasks.
What are some examples of AI agents?
Programmers build agents that learn from their environment and react autonomously to situations. This could mean controlling a robotic arm in a factory or recommending products to customers on an e-commerce platform. Apple's voice assistant Siri is an example of an AI agent; over time, it learns about the users it interacts with and provides better recommendations and answers to their questions.
Will AI agents replace workers?
AI models and agents will likely change the nature of work, not necessarily eliminate it. Because AI is good at automating repetitive tasks, jobs may be eliminated in areas 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 in all areas will remain essential.
