We say we have third wave of AI — the agentic AI. What is exactly an AI agent? At its simplest, an AI agent is AI-powered software that can do a variety of tasks for you. Had it not been for the agent, the same task would have been performed by a customer service agent, an HR person or an IT help desk employee. You demand services from an AI agent, and it renders those services to you. At times, while doing so, it interacts with multiple systems and goes much beyond answering simple questions.
Perplexity has released an AI agent which assists people in doing their holiday shopping. Google’s Project Mariner as AI agent is used to find flights and hotels and shop for household items, find recipe and myriad other tasks.
Though a simple concept, it still lacks clarity. Even Big Tech has not built consensus about its role. Google considers them task-based assistants, say they do coding for developers.
An agent may act like an extra employee. Agents are also customer experience tools. They assist the customer to solve more complex problems than what a chatbot handles.
In the absence of a cohesive definition, there could be ambiguity about what an agent would be doing. Despite the various definitions, agents help us complete tasks in automated ways, with the least human intervention. All agree that an agent consists of an intelligent software system designed to perceive its environment, reason about it, make decisions, and take actions to attain certain objectives autonomously.
A number of technologies could be used to make this happen. These could be AI/ML techniques such as natural language processing (NLP), machine learning and computer vision (CV) to operate in dynamic environments autonomously or along with other agents and human users.
Agents will evolve further, and AI will evolve. There is crossing of systems which is hard. Some legacy systems lack basic API access. This is more challenging than what we think.
The challenge is to allow the machine to handle contingencies in an automated way. The true test is to allow the agent to take over and apply true automation.
There could be AI agent infrastructure — a tech stack designed specifically to create agents.
Over time, reasoning will slowly improve. Frontier models will handle more of the workflows.
Maybe, agents will be powered by multiple LLMs, rather than a single LLM.
Agentic future is not tied to a single LLM.
Industry is moving towards agents operating independently.
This is a period of transition. It is a promising field, and we are moving in the right direction.