AI Agents

Extracted Attributes

• Types

  Simple reflex agents, model-based reflex agents, goal-based agents, utility-based agents, learning agents.

• Benefits

  Reduced costs, increased productivity, workflow optimization, automation of complex tasks, freeing human agents for mission-critical or creative activities.

• Challenges

  Managing AI hallucinations, practical hurdles to widespread enterprise adoption, many companies in the 'trough of disillusionment' phase of the hype cycle.

• Definition

  Autonomous systems capable of making decisions and performing tasks without human intervention, automatically responding to conditions to produce results.

• Key Characteristics

  Perceive environment, process information, take actions to achieve specific goals, operate independently or in collaboration, design workflows, utilize available tools, automate complex tasks, rational agents, can achieve goals inexpensively, rapidly, and at scale.

• Underlying Technology

  Large Language Models (LLMs), Reasoning Models, Generative AI

Timeline

• Exponential progress in underlying technologies like Reasoning Models, enhancing the capabilities of AI agents. (Source: Document 44a07cad-2323-4212-9339-0c55198fbc83)

  Ongoing

• Many enterprises are in the 'Trough of Disillusionment' phase of the Hype Cycle due to practical challenges like managing AI Hallucination, posing obstacles to reliable deployment. (Source: Document 44a07cad-2323-4212-9339-0c55198fbc83)

  Current

Agentic AI

Agentic AI is a class of artificial intelligence that focuses on autonomous systems that can make decisions and perform tasks without human intervention. The independent systems automatically respond to conditions, to produce process results. The field is closely linked to agentic automation, also known as agent-based process management systems, when applied to process automation. Applications include software development, customer support, cybersecurity and business intelligence.

Web Search Results

• Exploring Different Types of AI Agents and Their Uses - New Horizons

  Artificial Intelligence (AI) has transformed how we interact with technology, and at the core of many of these innovations are AI agents. But what exactly is an AI agent? Simply put, an AI agent is an autonomous entity that perceives its environment, processes information, and takes actions to achieve specific goals. These agents operate independently or in collaboration with other agents to solve tasks that traditionally required human intelligence, such as decision-making, problem-solving, [...] The world of AI agents is vast, evolving, and full of potential to transform industries and everyday life. From simple reflex agents to sophisticated hybrid models, these intelligent systems are revolutionizing how we interact with technology and solve complex challenges. Whether optimizing logistics, enhancing customer experiences, or enabling breakthroughs in healthcare, AI agents are reshaping the future.

• What Are AI Agents? | IBM

  # What are AI agents? ## Authors AI Engineer, Developer Advocate IBM ## What are AI agents? An artificial intelligence (AI) agent refers to a system or program that is capable of autonomously performing tasks on behalf of a user or another system by designing its workflow and utilizing available tools. [...] With the ongoing advancements in generative AI and machine learning, there is a growing interest in workflow optimization using AI, or intelligent automation. AI agents are AI tools that can automate complex tasks that would otherwise require human resources. This translates to goals being reached inexpensively, rapidly and at scale. In turn, these advancements mean human agents do not need to provide direction to the AI assistant for creating and navigating its tasks. ### Greater performance [...] At the core of AI agents are large language models (LLMs). For this reason, AI agents are often referred to as LLM agents. Traditional LLMs, such as IBM® Granite™ models, produce their responses based on the data used to train them and are bounded by knowledge and reasoning limitations. In contrast, agentic technology uses tool calling on the backend to obtain up-to-date information, optimize workflows and create subtasks autonomously to achieve complex goals.

• What are AI Agents?- Agents in Artificial Intelligence Explained - AWS

  AI agents are autonomous intelligent systems performing specific tasks without human intervention. Organizations use AI agents to achieve specific goals and more efficient business outcomes. Business teams are more productive when they delegate repetitive tasks to AI agents. This way, they can divert their attention to mission-critical or creative activities, adding more value to their organization. ### Reduced costs [...] AI agents are rational agents. They make rational decisions based on their perceptions and data to produce optimal performance and results. An AI agent senses its environment with physical or software interfaces. [...] agent is a software program that can interact with its environment, collect data, and use the data to perform self-determined tasks to meet predetermined goals. Humans set goals, but an AI agent independently chooses the best actions it needs to perform to achieve those goals. For example, consider a contact center AI agent that wants to resolves customer queries. The agent will automatically ask the customer different questions, look up information in internal documents, and respond with a

• Types of AI Agents | IBM

  There are 5 main types of AI agents: simple reflex agents, model-based reflex agents, goal-based agents, utility-based agents and learning agents. Each type has distinct strengths and applications, ranging from basic automated systems to highly adaptable AI models. All 5 types can be deployed together as part of a multi-agent system, with each agent specializing in handling the part of the task for which they are best suited. Industry newsletter [...] As agentic AI continues to evolve, advancements in generative AI (gen AI) will enhance the capabilities of AI agents across various industries. AI systems are becoming increasingly adept at handling complex use cases and improving customer experiences. Whether in e-commerce, healthcare or robotics, AI agents are optimizing workflows, automating processes and enabling organizations to solve problems faster and more efficiently. [...] AI agents are classified based on their level of intelligence, decision-making processes and how they interact with their surroundings to reach wanted outcomes. Some agents operate purely on predefined rules, while others use learning algorithms to refine their behavior.

• 7 Types of AI Agents to Automate Your Workflows in 2025

  The conversation around AI has shifted from chatbots—those basic interfaces designed to respond to user queries—to more sophisticated AI agents. AI agents are autonomous programs that can observe their environment, make decisions, and take actions to achieve specific goals. They can monitor data streams, automate complex workflows, and execute tasks without constant human supervision. As businesses seek more sophisticated automation solutions, these agents are growing in popularity: the AI