AI Agents
What they are and why they matter
AI agents are systems powered by artificial intelligence (AI) that perform complex tasks or make informed decisions with varying human involvement. They surpass traditional chatbots and large language models (LLMs) by integrating data and advanced analytics tools to be more adaptable and capable of complex reasoning across industries.
Traditional AI to AI agents
AI systems have evolved from simple rule-based programs to intelligent, adaptive models capable of complex reasoning – transforming how software is developed and deployed.
How are AI agents used in today's world?
AI agents are shaping industries by enabling automation, improving efficiency and enhancing customer interactions. Explore more resources:
Agentic AI explained
What is agentic AI? As a leading trend in tech, many people are wondering what it is and how it will impact business. Several factors make agentic AI especially relevant today – including the need for automation, improved decision making and greater productivity. However, there are risks and concerns with autonomous AI that bring responsible AI to the forefront. Listen to Marinela Profi explain agentic AI, real-world use cases, and the benefits and risks.
How are industries using AI agents?
AI agents are revolutionizing multiple industries by improving efficiency, decision making and customer experiences.
AI agents operate on a spectrum of decision making – from fully autonomous actions to human-guided oversight. The key is balancing complexity, speed and determinism to ensure AI delivers the right outcomes at the right time. Bryan Harris Chief Technology Officer SAS
How do AI agents work?
AI agents aren’t a one-size-fits-all solution. Instead, they operate on a spectrum of autonomy, spanning two different decision loops:
- Human out of the loop. Operating autonomously, making real-time decisions without human intervention.
- Human in the loop. Engaging in human oversight as needed, assisting but not entirely replacing human decision making.
Each of these decision loops comes with key considerations, including:
- Complexity of the problem. Lower complexity problems are often best handled autonomously, while higher complexity challenges often benefit from human oversight.
- Determinism. Systems operating independently must deliver consistent, repeatable outcomes. Those working alongside humans can allow for more exploratory or adaptive results.
- Speed of decision making. Real-time use requires millisecond-level responses, while nuanced scenarios may afford more time for analysis.
- Accuracy and governance. The level of automation varies depending on the accuracy required and the need for regulatory oversight in industries like banking, insurance and health care.
AI agents in practice
AI agents operate through five key components: Perception, cognition, decisioning, action and learning.
The role of the environment
An AI agent doesn’t operate in a vacuum – it interacts with systems, people and processes that shape its decisions. The environment provides the context and feedback that influence perception, cognition and actions. A well-defined environment helps the agent make better decisions and continuously improve.
AI agents versus agentic AI
AI agents and agentic AI have been used interchangeably, but they have distinct meanings. Read on to learn the difference.
AI agents are specific, task-oriented AI systems designed to perform repetitive tasks on behalf of a user. These agents can automate processes, analyze data and make decisions based on predefined rules and algorithms. They interact with their environment, systems, people and processes to shape their decisions and actions.
Agentic AI refers to intelligent systems or "agents" that exhibit a higher level of autonomy and decision-making capabilities. These systems can make decisions, carry out tasks, and learn from their interactions within a given environment. Agentic AI is a broader framework that uses multiple AI agents to achieve complex goals autonomously. It involves a combination of AI, automation and human oversight to redefine how businesses operate, make decisions and interact with technology.
In short: AI agents are the tools. Agentic AI is the system that uses those tools to think, decide and act on its own. Not all AI agents are agentic – true agentic AI requires a higher level of autonomy and coordination. But full autonomy alone isn't enough for enterprise use. That’s where thoughtful orchestration, human oversight and trust come in.
SAS® Intelligent Decisioning
SAS Intelligent Decisioning empowers organizations to automate and manage complex decisions with speed and precision. Combining business rules management, real-time event detection, decision governance and advanced analytics enables enterprises to make data-driven decisions at scale. From personalized marketing and next-best actions to credit services and fraud prevention, it streamlines real-time customer interactions and operational workflows.
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