A Brief Introduction To AI Agents

Introduction

What are AI agents, and why is everyone talking about them? Why are business owners and tech leaders so eager to adopt them?

Only recently, a survey was conducted with 1100 tech executives by Capgemini and 82% said they intend to integrate AI-based agents across their stacks within the next 3 years. In another survey, it was reported that one in 10 organizations is deploying AI agents, with more than 50% planning to explore their use in the next year.

In this blog, we’ll give you a brief introduction to AI agents, their types, common use cases, and the latest developments, so you can stay up to date with the newest technological advancements.

What are AI agents?

AI agents are autonomous systems designed to perform tasks on behalf of users or other systems and can operate with minimal or no human intervention. AI agents perceive their environment, process information, make decisions independently, and perform various actions to achieve specific objectives.

As surprising as it may sound, AI agents can be both physical and digital. Among physical AI agents, some of the most popular ones can be AI-powered drones, AI smart appliances, and AI-based autonomous vehicles. There are also Hybrid AI agents which can include robots that use cloud-based AI, or smart loT devices that blend hardware sensors with AI software. Examples of digital agents will be covered in more detail below.

AI Agents vs. AI Assistants?

Keeping up with changes in AI, let alone being up-to-date with such nuanced technical differences can be overwhelming if you're not following the trends daily, so here’s a quick breakdown. For example, AI assistants rely simply on their training data and require commands and continuous guidance from humans to function. Think of ChatGPT, which can provide information but can’t operate independently without constant commands from us.??

AI agents are also AI assistants, but they can act independently and only need an “initial push.” For example, they can use external data and memory to improve, and each time you ask an AI agent something, it can autonomously perform that action and deliver an outcome on its own.

Different Types of AI Agents:

1. Simple reflex agents- These agents are designed to make decisions simply based on their current input and respond immediately without requiring memory or learning processes. One example is an AI-powered email auto-responder that replies with pre-written messages based on specific keywords in incoming emails. Its main limitation is that it does not learn from previous conversations.
2. Model-based reflex agents- Model-based reflex agents are more advanced and designed to operate in partially observable environments. For example, smart home security systems fall into this category, as they use internal models of the home’s status to monitor sensors and take actions based on real-time inputs.
3. Goal-based AI agents- Goal-based agents are designed to pursue specific objectives by considering the future consequences of their actions. For example, task scheduling systems fall into this category, as they aim to complete tasks by adjusting schedules and prioritizing based on deadlines, resources, and dependencies.
4. Learning agents- Learning AI agents improve their behavior over time by interacting with the environment and learning from past experiences. This type can include AI-based customer service chatbots that can improve response accuracy based on interaction outcomes, new information, or inputs.
5. Utility-based agents- These AI agents make decisions by evaluating the potential outcomes of their actions and choosing the one that maximizes overall utility. For example, autonomous vehicle route optimization can fall under this category. It can optimize and suggest a route that can minimize travel time by selecting roads with less traffic, but it could also adjust its goal to optimize fuel efficiency by taking longer but less congested routes.
6. Hierarchical Agents- Hierarchical agents are different from other types of AI agents thanks to their structured, multi-layer approach to problems. An example can be air traffic control systems (airports) as different levels of controllers handle specific tasks, from managing airspace and flight flow to guiding planes on the ground and during takeoff or landing.

10 AI Agent Use Cases Across Industries

1. Customer Service & Support

Some of the most common use cases of AI agents in customer service include virtual assistants, such as AI-powered chatbots, that help manage customer issues, handle subscriptions, answer common questions, and personalize offers.

One example of a customer-facing AI agent includes Microsoft Azure Bot Service which uses ML models that improve based on interactions. At least initially, most businesses can integrate AI customer support agents to automate time-consuming manual tasks and let their support team handle more complex issues.

However, we should note that some chatbots aren't considered AI agents because they operate on simple rules or scripts without the actual ability to learn or adapt. For example, menu-based or rule-based chatbots just follow predefined paths, they can't analyze or respond to more complex questions or learn and improve from previous interactions the way more advanced AI-powered bots can.

2. Retail & E-Commerce?

AI agents have diverse use cases in retail and e-commerce. As usual, some of the most common use cases are smart chatbots that can learn and improve from client interactions to real-time independent voice AI agents.?

Another example includes AI agents that are used for personalized recommendations. AI algorithms analyze consumer behavior to deliver tailored product suggestions. It’s usually done by tracking users’ browsing history, past purchases, analyzing user behavior, predicting their preferences, and offering tailored recommendations in real-time. Additionally, it can guide shoppers in their buying journey by offering exact or complementary items.?

Another common use case is AI-based marketing in retail. It can range all the way from trend predictions, segmenting audiences, and creating hyper-targeted ads or marketing campaigns by analyzing shoppers’ data to optimizing pricing and promotions through predictive analytics.

Here are some real-life examples you may or may not have heard of. First of all, Sephora’s Virtual Artist, which uses AI to recommend makeup based on the users’ facial features. Why is it considered an AI agent? Well, it can analyze facial features, and provide personalized product recommendations on its own, showing how different makeup products might look based on the users’ skin tone and face. It works autonomously, without direct human input.

We can’t forget Operator by OpenAI ?which made waves only recently. It’s basically an AI agent that helps people perform actions like booking, shopping, or finding information by interacting in natural language. It understands and processes user requests autonomously, makes decisions, and adapts its responses over time to improve the experience.

3. Healthcare?

One of the most unique use cases of AI agents in healthcare, which not many have heard about, is using AI health assistants to provide e-consultations. So, how do they work? Let’s take Babylon Health for example, which has an AI health assistant that can help patients with medical consultations through text and voice formats. Some of its functions include helping with common symptoms, analyzing the responses, and suggesting potential diagnoses or advising them to seek further medical attention.

Other examples can include AI agents that can provide accurate and specific treatments through patients’ data. For example, IBM Watson for Oncology can analyze clinical data, learn from past outcomes, and suggest specific treatments tailored to each patient.

Another common example can be using generative models to analyze medical imagery and datasets to assist in accurate diagnoses. It can go beyond simply classifying images such as helping doctors with decision-making and continuously learning from new data.

4. Finance & Banking

AI agents can perform complex tasks such as financial forecasting, fraud detection, and expense management. For example, AI-based robo-advisor Wealthfront continuously analyzes financial data, rebalances portfolios, and optimizes investment strategies without any human intervention.?

Another common use case is expense management, where AI agents can analyze spending patterns, detect anomalies, predict future expenses or offer personalized budget recommendations.?

5. Security & Compliance

AI agents can successfully identify and respond to cybersecurity threats and automate the detection of anomalies. Let’s take the example of Darktrace, which is a British cyber security company that has launched Cyber AI Analyst which can autonomously investigate alerts, mirror the human threat investigation process, question data, understand and test hypotheses, and finally reach a conclusion.

6. Human Resources

AI agents can be used by HR specialists in recruitment to screen resumes, conduct initial interviews, and onboard new employees. One such successful AI agent is Oracle Recruiting Cloud ?which analyzes resumes, matches candidates to job roles, and even conducts initial assessments without human intervention.

AI agents are also used for automating repetitive tasks such as managing employee records or answering policy-related queries which can save up quite a lot of time for humans.

7. Education

AI agents in education can help personalize lesson plans, provide instant feedback, and track student progress. Let’s take the example of Cogniti AI ?which creates education AI agents for teachers so that students can have access to “their human teachers” 24/7. For example, instead of being online for students 24/7, teachers can simply provide all necessary pages, files, and other resources to the agent to help answer their questions outside work, personalize feedback, etc. Simply put, it operates on behalf of a human.?

Similarly, there are many AI agent tutors that provide personalized lessons, can learn and find areas the student struggles with, and adjust their teaching methods or content accordingly.

AI agents can also help educational institutions with admissions processes, course scheduling, and resource allocation. This is only a small insight into how they are already revolutionizing the education industry.?

8. Emergency and Disaster Areas

AI agents can use deep learning algorithms to retrieve the information of users on social media sites that need rescue. For example, a disaster response AI agent might be created to monitor social media for mentions of a natural disaster in real-time, and analyze posts that can have keywords like "help," "earthquake," “burning", “hurricane”? and then gather the writer’s information such as location to assist rescue teams in reaching those affected.

9. Home Security

AI agents can detect unusual activity, recognize faces, and alert homeowners in case of security issues by observing changes in the environment. These systems can track down anomalies and take actions on their own, such as sending alerts or activating security measures when threats are detected.

10. Sales and Marketing

AI in sales and marketing is expected to make massive changes in 2025. A recent Forbes article states that not only can AI agents autonomously provide 24/7 client support, but while assisting clients, they can also ask questions to evaluate and determine whether they’re a strong candidate for a given product or service.

Moreover, AI agents in sales are starting to personalize follow-up emails, autonomously update sales records, qualify leads, and make accurate forecasts. All of this will lead to more efficient processes, encouraging sales and marketing experts to focus on coming up with more innovative ideas to attract clients and create genuine connections with them.

Recent AI-Agent Use Cases in Enterprise Companies

1. Oracle introduced AI agents tailored for sales teams. These agents automate tasks such as updating records post-customer meetings and generating intelligence reports by getting data from various business software, supporting multiple languages.
2. IBM's Watson Analytics is being used for sophisticated data analysis, helping businesses predict customer behavior and manage risks.
3. Johnson & Johnson is performing drug discovery with AI Agents.
4. eBay is using AI agents for coding and selling.
5. Deutsche Telekom is using an AI agent for its 80.000 employees. They can ask questions about internal policies, benefits, and product or service inquiries.
6. OpenAI just announced an Operator that can perform tasks such as booking or shopping on a person’s behalf.

Wrapping Up

AI agents are truly revolutionizing a wide range of industries and we can only expect their operations to grow from 2025. With their ability to automate processes, learn from data, and make independent decisions, they offer businesses the opportunity to improve efficiency and focus on less mundane activities in their daily work.

If automation of your repetitive business processes with AI agents is something you're looking for in your business, email us at [email protected] and we will give you a FREE consultation.