AI Agents vs. Agentic AI

As we delve deeper into our industry research on AI and Customer Experience (CX), I've noticed that many business leaders are often confused by the terms "Agent AI" and "Agentic AI," as they are sometimes used interchangeably. However, these terms represent distinct concepts depending on the context. Here's a straightforward guide to clarify the difference.

1. Agent AI: Agent AI typically refers to artificial intelligence systems designed to perform tasks or services autonomously on behalf of a user or another system. These agents can be software programs or robots that perceive their environment through sensors and act upon it using actuators. For the longest time in customer care industry- chatbots and automated customer service agents were common assistants to a customer service agent. Today, all these assistants and even household names like Siri or Alexa, are common examples of Agent AI. They are designed to understand user queries and perform actions or provide information in response. Note that such AI Agents expect curation and ingestion of data from various resources.
2. Agentic AI: Agentic AI refers to AI systems that exhibit a degree of autonomy and decision-making capabilities, often with a focus on self-directed actions and goals. This concept emphasizes the AI's ability to act independently, make choices, and potentially adapt to new situations without direct human intervention. Agentic AI systems may or may not include an AI agent tasked for improving a customer interaction. Advanced autonomous systems, such as self-driving cars or AI-driven trading systems, can be considered agentic because they make complex decisions based on a variety of inputs and changing conditions. We are empowering machines to become our partners in solving problems, taking actions, and making decisions.?

In summary, while both terms involve AI systems that perform tasks, "Agent AI" is a broader term that includes any AI acting on behalf of a user, whereas "Agentic AI" emphasizes the autonomy and decision-making capabilities of the AI.

It is fascinating to witness Agent AI and Agentic AI navigate the complexities of two pivotal AI concepts: Everyday AI, which seamlessly integrates AI technologies into routine business processes, and Game-changing AI, which has the power to fundamentally transform industries or create entirely new markets, such as through autonomous vehicles, AI-driven drug discovery, and innovative human-computer interactions.

Gartner makes a clear distinction here to help organizations understand where to focus their AI investments based on their strategic goals—whether to enhance current operations with everyday AI or to pursue transformative opportunities with game-changing AI.

Agentic AI is promising and game-changing and we have yet to fully witness the growth and innovation that this technology will drive.

Note: By 2029, 50% of new applications will harness AI (everyday AI or game changing AI) to create personalized, adaptive user interfaces, a dramatic increase from less than 15% in 2024. These insights and emerging trends were shared at the recent Gartner IT Symposium/Xpo 2024 in Orlando and they will continue to be hot topics at Gartner Tech Growth & Innovation Conference 2025, in Grapevine, TX.

Eagerly anticipating groundbreaking AI use cases and applications that will make a significant impact in the CX industry. Engage/Connect /Inquire.

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