As we move into 2025, the insurance industry is witnessing a transformative phase driven by AI, especially with the rise of generative AI (GenAI) and new concepts like AI agents and agentic AI. While AI agents perform specific tasks, similar to a chatbot providing customer support, agentic AI takes it even further by making complex decisions independently, much like a self-driving car navigating without input. This rapid growth in AI technology has created challenges in understanding and applying these concepts effectively. Companies need to bridge the knowledge gap and adapt their strategies to harness the full potential of AI agents and agentic AI in their operations, ensuring they are equipped for the evolving landscape.
April 2025
The rise of artificial intelligence (AI) in our industry is transforming how we operate. While we have used AI tools like machine learning for years, the introduction of generative AI, especially tools like ChatGPT in early 2023, has set a new stage. Moving forward, 2025 and beyond are expected to focus on “AI agents” and “agentic AI.”
These terms, often confused, describe different AI technologies gaining traction in the Market. Companies such as Salesforce, NVIDIA, Microsoft, and OpenAI are leading this charge. Understanding these new concepts is crucial for our industry, as they can significantly enhance various parts of the insurance value chain. However, there is still a significant knowledge gap regarding ai agents and agentic AI within the sector.
Many people mistakenly believe that AI agents only support human workers, like call center representatives. In reality, they augment human capabilities rather than replace them. This misunderstanding is exacerbated by a trend where many tech firms label their products as “AI” or “AI-enabled,” causing confusion among businesses trying to navigate this rapidly evolving landscape.
As the AI field continues to evolve swiftly, organizations are feeling the pressure to adapt constantly. Companies might figure out their AI strategies only to see new advancements emerge, requiring them to rethink their approaches. The challenge lies not just in keeping up with technology but also in educating employees quickly enough to utilize these innovations effectively.
AI Agents
AI agents are systems capable of observing their environment and taking actions towards achieving a goal with little or no supervision. They can identify tasks and work independently, making them similar to digital employees. Examples include chatbots that handle customer queries and cybersecurity systems monitoring threats.
Agentic AI
On the other hand, agentic AI goes a step further. It can not only follow instructions but also make decisions and plan actions to meet complex objectives within ecosystems that consist of multiple AI agents. Think of agentic AI as a manager who continuously learns and adjusts strategies based on feedback and the environment to achieve specific results.
Examples to Illustrate
To make these concepts clearer, here are two illustrations:
Illustration A:
Imagine an AI agent as a vehicle’s navigation system. It provides directions, but you are still in control of driving. In contrast, agentic AI can be compared to a self-driving car. It knows where to take you and navigates all routes and obstacles without needing your input.
Illustration B:
Picture an AI agent as a stock Market bot programmed to buy or sell based on set prices. Now, think of agentic AI as a sophisticated system that reviews your investment goals, Market trends, and other factors to adjust your investment strategy automatically.
The potential of AI agents and agentic AI in industry applications is vast. As we continue to discover the benefits and risks associated with these technologies, understanding their capabilities will be vital for success in our increasingly AI-driven world.
Tags: AI Agents, Agentic AI, Generative AI, Machine Learning, Technology in Insurance
Frequently Asked Questions about AI Agents and Agentic AI
What is an AI agent?
An AI agent is a type of computer program that can perform tasks automatically. It can help with things like scheduling, answering questions, or managing data. AI agents learn from their experiences to improve over time.
What does “agentic AI” mean?
Agentic AI refers to artificial intelligence that makes decisions and takes actions on its own. Unlike regular AI, which follows specific instructions, agentic AI can adapt and operate independently in certain situations.
How do AI agents work?
AI agents use algorithms and data analysis to understand and respond to various tasks. They often rely on machine learning, which helps them learn from previous experiences and make smarter decisions in the future.
Are AI agents safe to use?
Generally, AI agents are designed with safety in mind. However, like any technology, they can have risks. It’s essential to ensure they are well-protected and monitored to prevent misuse or errors.
What are some examples of AI agents in everyday life?
You might use AI agents every day without realizing it. Examples include virtual assistants like Siri and Alexa, customer service bots on websites, and recommendation systems on streaming services. These agents help make our lives easier and more efficient.