From cybersecurity to supply chain management, Agent AI helps businesses automate complex, complex tasks in real time.
term Agent AIor AI AgentIt refers to an AI system that allows for independent decision-making and autonomous action. These systems can infer, plan, and execute actions and adapt in real time to achieve specific goals.
Unlike traditional automation tools that follow pre-determined paths, Agent AI does not rely on a fixed instruction set. Instead, use the patterns and relationships you have learned to determine the best approach to achieving your goals.
To do this, Agent AI breaks down the larger main objectives into smaller subtasks, said Thadeous Goodwyn, director of Generation AI at Booz Allen Hamilton. These subtasks are delegated to more specialized AI models, often using traditional, narrower AI models with specific actions.
The decisions and actions of these components AI systems ultimately allow AI agents to achieve their primary objectives. According to Goodwyn, this ability is rapidly matured.
“The agent's ideas are nothing new. We've been working on this for a while,” he said. “But the reason it's getting so much attention now is because large-scale language models and generation AIs need to succeed in some characteristic agent AI.”
According to “The Status of Generic AI in Deloitte's Enterprises,” agent AI is one of the most closely monitored areas of AI development. Respondents described agent AI (52%) and multi-agent systems (45%) (more complex variants of agent AI) as two of the most interesting areas of AI today.
11 Agent AI Examples and Use Cases
AI experts and enterprise leaders see agent AI delivering value to diverse business functions and industries by streamlining workflows, enhancing decision-making, and automating complex tasks. Here are 11 examples that show the possibilities of transforming IT operations and changing how work is done.
1. Risk reduction and security
By coordinating the components of these activities, Agent AI can help businesses with security operations and risk reduction efforts, according to fellow IEEE Karen Panetta, professor of electrical and computer engineering at Tufts University, and Karen Panetta, dean of graduate education at Tufts School of Tufts School of Engineering.
For example, AI agents in Security Operations Centers can actively scan new and new threats, investigate anomalies, and take corrective action automatically without human intervention. Similarly, in risk management, AI agents can search for abnormal activities, investigate those patterns to determine whether they are fraudulent, and respond automatically when necessary, Panetta said.
2. Supply Chain and Logistics
Agent AI is also useful in the supply chain and logistics sectors where coordinating multiple tasks is standard, Panetta said. For example, if drought in a growing region affects agricultural availability and costs, supply chain employees typically need to check availability in other regions, check prices, reconfigure supply and distribution channels, and find alternative sources of agricultural products.
Historically, workers used their skills to handle many things, not all of the work. Now, Agent AI can adjust the entire workflow, Panetta said. Supply chain workers may enter the desired outcome. For example, you can find and deliver the required amount of supplies at the lowest cost or fastest delivery, and expect the system to automatically initiate actions to make it happen, not only identifying how it is.
3. Call Center
As of early 2025, Agent AI is already “running at scale” in call centres. Stuart Brown, partner and digital business leader at Consultant Guidehouse, builds on the improvements and efficiency that traditional AI has brought.
Call center AI agents coordinate intelligence and automation across multiple activities involved in serving customers, Brown explained. Agents may simultaneously analyze customer sentiment, review order history, access company policies, and address customer needs based on those factors.
4. Improved customer service
Agent AI can improve not only the call center but also the overall customer service, Brown said.
AI agents can help human employees “get answers faster and serve customers faster,” he said. The role of AI agents as a support tool helps ensure that all employees consistently provide high-level services to their customers, regardless of their skills or experience.
Furthermore, Agent AI can actively serve customers at levels that human employees and even traditional AI generally cannot, Brown said. For example, utility companies may use Agent AI to identify customers receiving unusually high invoices. Please contact them with that information. We provide specific, accurate and personalized information on why your invoice is so high. We will suggest ways to lower your future bill.
5. Search for knowledge
Agent AI improves knowledge search by accessing information and acting on insights. For example, an agent AI chatbot can access the knowledge base, answer user queries, and even take the following best actions:
To illustrate, he pointed out an example of how it works in helpdesk. Previous generations of help desk chatbots can answer certain well-defined user questions, but Agent AI is deeper. It analyzes issues, provides options, refines information, and even implements recommended fixes. If the problem cannot be resolved automatically, the agent can triage the problem and route it with related information to a human agent, saving the user without having to repeat all the details.
6. Multimedia creation
Generated AI can create text, images and videos, but Agent AI takes it a step further. According to Goodwyn, it instructs agents to develop multimedia reports, delegating subtasks such as research, text generation, image selection and design to other AI systems to provide a more refined, complete final product.
This use case exemplifies agent AI as an orchestrator of AI capabilities rather than a narrow single-function technology.
7. Scientific and Material Discoveries
Agent AI demonstrates transformational capabilities in areas such as drug discovery and the creation of new materials, Panetta said. Of course, other technologies, including machine learning and unscientific AI, have been used in these fields for decades, but agent AI works at a much higher level.
“[Agentic AI] “This is something I know and I'm smart enough to say it's based on these materials. [the characteristics the user is seeking] And my exploration, here's the new material or combination,” Panetta said.
She added that Agent AI is not just developing recipes for new compounds. You can also identify the best supplier based on priorities such as cost and timing and order the required materials.
8. Healthcare Business
From diagnosis to personalized treatment, the entire patient experience is applied to the ability of agent AI to recognize context and act without constant human intervention. In the backend, Agent AI optimizes tasks such as booking scheduling, claims processing, and regulatory compliance.
Using unstructured clinical notes from hospital electronic health records, researchers at Mass General Brigham developed a high-performance agent AI system that includes multi-note summaries and multi-step inferences for classifying and assessing cognitive impairments.
9. Defense and military logistics
Goodwin points out use of Agent AI in defense and can be used in logistics planning. Consider highly complex military tasks that involve moving materials, equipment, and military forces using multiple modes of transport across different distances.
According to Goodwyn, Agent AI is in the pilot stage in such areas. He emphasized that AI agents are used in this context to coordinate complex purposes and augment human judgments rather than replace them.
10. Manufacturing
Manufacturing is another sector that demonstrates the potential of agent AI, Brown said.
AI technology allows decisions to be made and autonomous actions in a long workflow that includes multiple functions and IT systems. Agent AI workflows can connect to IT systems that power a variety of components, from procurement to manufacturing, and use narrow AI models to complete subtasks.
In such cases, Brown explained that agents can perform complex, multi-stage workflows.
- Be aware that the required materials are low.
- Flags that the material is not available from regular suppliers.
- Search and order from alternative suppliers who can ship materials to manufacturers within a specified price range and time frame.
- Please fill in the required form.
- Enter the required data within the appropriate digital system.
- Reconfigure factory floors and production schedules to meet established deadlines.
“It used to be done by humans,” Brown said. “Now you can do it all with Agent AI.”
However, he added that determining control points based on a responsible AI framework is a best practice to keep humans in a loop.
11. Utilities
Agent AI is already in use in the utility industry, Brown said. Here, like in other areas, Agent AI can coordinate decision-making and subtask automation to achieve the objectives specified by the utility.
For example, utilities test the ability of AI agents to assess, triage and organize responses to disasters such as hurricanes and wildfires. Agents can analyze the data to assess infrastructure damage and impact on individuals and communities. Plan and schedule rescue and repair operations. Routing the workers and materials needed to complete repairs on time. This could dramatically accelerate recovery time and save lives in the process, Brown said.
Brown described an example of a UK utility company that uses Agent AI to meet regulatory requirements to contact customers with special needs such as medical conditions within a specific time frame during suspension. Utility companies have struggled to meet their requirements using traditional technology, but have been successful with AI agents. Not only can agents warn customers of confusion, they can also ask about their needs, understand their communication, and act on it.
It's a fundamental change, but it's not without challenges
The Deloitte report found that 26% of respondents' organizations were already investigating the development of autonomous agents “large or very large or very large.” But like the generator AI, “Agent AI is not all the silver bullets a company needs to accomplish,” the report says.
Agent AI systems differ from generative AI systems, pose regulatory, security, data and labor challenges. These issues are undoubtedly even more important and challenging due to the increased complexity of agent AI systems,” the report states.
However, despite the restrictions, Deloitte and other industry experts highlight the immeasurable potential of Agent AI in business operations.
“A lot of people don't understand the impact,” Brown said. “Though some people still think it's a different tool, Agent AI is a fundamental change in the way we work. It creates new ways of working.”
Mary K. Pratt is an award-winning freelance journalist with a focus on enterprise IT and cybersecurity management.
