AI agents are transforming the workplace. They are reshaping how we work as individuals, operate as organisations and interact with our customers. Imagine AI agents as digital teammates, available 24/7 and capable of processing vast amounts of information instantly.

But what are they, and how do you get the most out of them? This guide will help you understand, select and implement the right type of agent for your business. Let’s go!

What exactly is an AI agent?

Agentic AI refers to any program capable of performing tasks autonomously. It can respond intelligently based on great amounts of data, adapt over time, and execute the correct action without detailed user input. It’s like a digital assistant that can think (in a way).

An AI agent has three characteristics:

1. It can learn from mistakes
2. It has long-term data retention and recall
3. It can execute autonomously based on the user request.

The biggest difference between an AI agent and your standard AI chatbot (or an automated process) is the fact these agents can pull more weight without relying on fixed rules or inputs. They don’t just execute tasks, they can actually “think” through them. Meaning they  can be relied upon like a regular colleague – only with far superior processing power.

You’ve probably already encountered a few, as a very common use case is having an AI agent assisting customer service. While a regular chatbot might just offer scripted answers, an AI agent can interpret the tone of a message, respond with empathy, and suggest relevant products or services based on a customer’s past behavior.

How can you use AI agents?

AI agents are a huge leap beyond automation. But what’s the actual benefit, and how can you apply the technology? Here’s a few aspects to consider:

• They can increase efficiency, even with more complex tasks
  Think of any repetitive task that sucks a lot of time but can’t be fully automated away. Agentic AI can bridge that gap and perform those same tasks, equally well, in a fraction of the time.
  
  Our own agent, Magnowlia, is a good example. It lives directly in your Teams or Slack and is plugged into your data stack, so it can be used like an additional analytics team member. Precisely because it has autonomous analytics capabilities, it can offload a broad range of not just regular but ad hoc tasks: putting together a  clear report, finding insights, understanding what type of visualisation you’ll need and adding recommendations for deeper analysis.
  
  

• They can act as data driven decision enablers (or makers)
  A good agent is capable of taking action on their own, and does so based on great volumes of data. If there are simple decisions you currently need to make based on complex data analysis, an AI agent could both crunch the numbers and suggest (or even take!) a course of action.
  
  This is the exact benefit Magnowlia provides. And we can confidently say Magnowlia helps our customers understand and act on their own business data in a way that just wouldn’t be possible otherwise, removing the lag between data processing and organisational action.
  
  

• They can “speak human” in a custom way
  AI that understands natural language and can sound like a human is no longer news. What is new is that AI agents can parse natural human language with added context to adapt their tone, response and action based on your particular dataset.
  
  This allows them to adapt and solve for a broader set of conditions, much like a human would. This feature is incredibly valuable not only in customer service applications, but in any context where end users need to be able to use the AI agent without prior knowledge or comfort with AI prompting.
  
  Again using Magnowlia as an example, in practice, this means the agent can understand what your team members are asking it to do even if the user has never talked with Magnowlia before. It can also provide far more nuanced analysis as it learns from your specific dataset and team over time.

The future of working with AI agents

Agentic AI is already mature enough to provide real benefits to most any organisation, and the technology is becoming more and more sophisticated. In the next few years, we’ll probably see not only broad adoption but also more strategic applications as agents go from simple task executors to strategic colleagues.

So how do you put them to good use, today and tomorrow? The key to a valuable business application lies in understanding your own needs.

• Map out where you might need an additional colleague
  Make an inventory of where your organisation currently has its particular bottlenecks and time sinks. Is there any team or function that is overloaded, or stuck with repetitive tasks? Is there any repetitive task just beyond the reach of automation that you’d love to outsource? These are high value application areas for an agent.
  
  

• Take a look at where you need to be data-driven, not gut-driven
  Are there any decisions and actions that you need to take, at speed, based on intimate knowledge of your business? Are those decisions often taken hastily or after a prolonged (and likely stressed) period of analysis? Are most of your data questions ad hoc and burdening an overloaded analytics team? This is where an analytics agent like Magnowlia really can help.
  
  

• Inventory use cases where context and natural language really matter
  Are there any business areas that can clearly benefit from AI applications, or even already use them, but find it hard to get the AI to “work”? This is a clear sign that you need an agent that can learn and adapt to your specific needs over time, regardless of who is using it.
  
  
  

Will AI agents be able to replace human employees over time?

This is a loaded question, of course. Our own take as founders of an AI company and developers of an AI agent is nonetheless based on the experience of helping real people at real companies.

We believe that whoever learns to master and take advantage of agentic AI will never lack for success – because agents can make those who master them 10x or 100x more capable. Why would anyone say no to becoming more efficient, or free of tasks that don’t develop and challenge their unique human capabilities?

When it comes to simpler applications, simpler jobs, agents will absolutely replace human workers. This is already happening across the workforce. The more fascinating question is what autonomous technology will mean for our working life.

Unlike the shift from seamstresses to sewing machines to fully automated fabric production, agentic AI can step in and replace humans even in tasks that demand strategic decision making. It is likely (and again, already happening!) that agents will be able to collaborate with other agents.

So will we have no work to do in a few years? That, on the other hand, is not likely. Agentic AI just means we can look forward to a future where work is increasingly fun.

Because that is exactly what Magnowlia does for companies today – it helps the entire organisation talk with their data and collaborate around it, without the boring steps in between.

We hope you found this article helpful in navigating agentic AI. Want to learn more about using Magnowlia in particular for your own work? Get in touch!