How AI Agents Are Completely Changing The Way We Work in 2025

If you haven’t heard of AI agents, trust me you’re not alone. At the beginning of this week when my boss asked me to write a post on it I hadn’t the faintest clue what he was talking about…

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Lucky for you, that means I spent a great chunk of my time this week researching the who, what, when, why, and how of AI agents, and I’m about to divulge all. 

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What Is an AI Agent: 

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Let’s start with the basics - what on Earth is an AI agent? It essentially refers to a new kind of software program that has the ability to perceive its environment. So, unlike your traditional softwares, an AI agent is rational in the sense that it learns and adapts in order to grow smarter over time. 

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How Do AI Agents Work? 

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At this point you’re probably thinking, “that’s all well and good, but how does it actually work?” Basically, in order for an AI agent to work, you need to feed it with relevant data and also provide it with a predetermined goal.

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It’s from this information that the AI agent is able to spit out a course of action required to achieve said goal. As such, when it comes to complex tasks, they can be highly beneficial in simplifying and automating the task. And the best part? It’s set up so that the agent performs the task for you. 

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It’s worth bearing in mind that AI agents have been around for some time, but they are more so what we now refer to as basic AI agents, vs the advanced AI agents we see today.

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How are they different? Well, for starters they have the ability to extract context. Take a customer service chatbot (one of the most commonly used AI agents of today). Not only can the chatbot detect the text submission, it can also pick up on other cues to determine customer sentiment.

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This brings me to the next major difference which is dynamic decision making. By analysing historical data and collecting feedback based on their previous level of success, the AI agent is able to generate a personalised response. 

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Rule-Based vs. Learning-Based Agents: 

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When we talk about AI agents we’re really referring to 2 kinds of categories:

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(1) rule-based

(2) learning-based agents.

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While rule-based agents follow pre-determined rules, learning based agents leverage machine learning to analyse data and improve on previous interactions, making them adaptable over time. This makes rule-based agents good for simple tasks that require regular repetition, and learning-based AIs ideal for more complex outcomes. 

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How Can We Benefit From AI Agents?

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Now that we’ve got the basics down pat, let’s consider how businesses can benefit from these revolutionary agents. For one, they’re going to help from a productivity standpoint. By delegating certain tasks to AI agents, businesses will be able to free up time and resources that were once dedicated to manual labour. 

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AI agents are also going to lead to a better customer experience overall. By offering personalised recommendations and being able to respond 24/7, customers' satisfaction will likely improve, inevitably leading to more conversions for the business in question. 

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Finally, it’s going to be a gamechanger for innovative problem solving, such as detecting errors and offering suggestions for prevention prior to the problem unfolding. 

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Current Challenges With AI Agents: 

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But of course, it’s not all sunshine and daisies. Given AI agents are still in their infancy stage, there are still a handful of challenges we face while adopting the software.

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For starters, it can be quite a complex system to set up, meaning there’s a certain barrier to entry. There’s also the concern of running into ethical dilemmas that stem from inaccurate results. And then you’ve got privacy concerns. After all, for these AI agents to work properly you need to be willing to feed them a tonne of internal documents so they can understand your business at its core. This means you’re potentially storing high volumes of company data within these systems. 

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So there you have it, an introductory class on AI agents and how they’re going to help businesses work smarter, not harder moving forward. What are your thoughts? Are you worried these AI agents are going to take over the world? Or will you be implementing them into your business model ASAP? Let us know. 

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