Autonomous Agents

What are autonomous agents?

Autonomous agents are software systems that use artificial intelligence to perform complex tasks independently of human intervention. In contrast to AI agents, which run on strict rule sets and need a human guide to complete tasks, autonomous AI agents run full systems of open-ended, dynamic decision-making. Businesses integrate autonomous agents into existing systems to monitor efficiency, solve problems without human intervention, and spot patterns that humans might miss. 

Example: Our smart home system is an autonomous agent. It learns our habits and preferences, and adjusts our heating and lighting for maximum efficiency and comfort without our input. 

Most modern autonomous agents are trained on large language models (LLMs) to support their ability to reason and make decisions, but they also include additional systems to improve their autonomy. 

What are the benefits of autonomous agents?

While AI agents, chatbots, and assistants need some form of human input to guide them, autonomous agents do not. Once integrated into existing systems, autonomous agents can make decisions that would otherwise require human oversight. 

For L&D teams, autonomous agents represent the opportunity to automate repetitive tasks like enrollment and scheduling, deliver personalized learning at scale, and provide real-time feedback and coaching to learners. They can also help teams save time by automatically updating content when policies or products change and by predicting future skill needs by analyzing current skill gaps.