AI Agent Definition

Intelligent agents leverage natural language processing, machine learning—including deep learning—and automation to handle tasks that previously required human intelligence..

AI agents may be:

• Autonomous: Operate independently, making decisions and executing actions without continuous human supervision.
• Reactive: Sense and respond to changes in their environment—whether digital or physical—in real time.
• Proactive: Pursue defined goals by taking initiative, not merely reacting to external stimuli.
• Adaptive: Learn from experience by identifying patterns and refining behaviour to improve future performance.
• Collaborative: Interact effectively with humans and other agents to achieve shared objectives.

AI agents: From simple rules to advanced autonomy

AI agents range from basic rule-based systems to sophisticated models capable of learning and adaptation. They are applied across a wide range of industries, including:

• Customer service: Handling inquiries, resolving issues, and assisting users in real time.
• IT automation: Managing infrastructure, writing code, and orchestrating complex workflows.
• Autonomous vehicles: Navigating dynamic environments with minimal human intervention.
• Data analysis: Interpreting large datasets to uncover trends and generate actionable insights.
• Research and synthesis: Searching, aggregating, and summarizing information to support decision-making.

Unlike traditional chatbots or narrow AI tools, intelligent agents demonstrate a higher degree of autonomy. They can learn from experience, adapt to new contexts, and make decisions independently using internal reasoning systems—reducing the need for constant human input.

As AI capabilities evolve, agents are expected to drive significant transformation across business and society, delivering greater efficiency and unlocking new opportunities.