What are Generative AI Agents and Why They Matter

You've probably heard about generative AI agents. They're the latest trendy topic in AI, and many experts call them the real deal. Of course, you'd be excused for feeling you've heard this before and simply rolling your eyes. But in this case, you shouldn't.

To explain why, I'll use a simple example: how to produce an article like this.

If you've used ChatGPT or any of the generic Gen AI tools, you know that you can use them to write an article.

First, if you're not like me—someone with more ideas to talk about than any AI can follow—you might start a conversation with a tool to brainstorm ideas. You'll probably go back and forth a few times until finding your theme.

Once you find your topic, you can use a gen AI like GPT Search or Perplexity to research it. The AI tools may even suggest questions to ask, but you'll also need to create your own and require many iterations before getting the material you want.

Then, you'll prompt another tool to draft the article. If you use a paid version of any major tools, you might already have a trained AI to write for you the way you want. But even then, you'll likely need a few iterations of fine-tuning and correcting the AI draft to get close to a good outcome.

Finally, if you want to adapt your content for different audiences—say for LinkedIn, a blog, or a short post—you'll need more prompts to refine the style, tone and article size.

Even if it seems convoluted, this process works, and whilst it mightn't make it substantially faster than doing all those steps yourself, you'll probably end up with much better content than you would without AI—and usually faster.

AI agents change everything. (Yes, they do)

The process I described requires constant interaction and supervision. You manage it step by step.

Now, imagine that instead of doing all that, you have a team of specialised AI agents. One AI does the brainstorming. Another handles research. Another drafts the content. A forth edits and polishes it. A final one adapts it for different platforms. They all talk to each other, coordinating to produce a result that matches your expectations. You just start the process and check the result.

AI automation has been happening like this for decades, but pre-generative artificial intelligence was rigid and could only substitute tasks with clear parameters and well-defined data. Also, they couldn't create anything new. They just generated pre-defined results.

Now, generative AIs can do all that, but like any system or person, they work better when specialised. These new gen AI agents can not only be as creative as humans in particular tasks but, because they are specialised, they can be fine-tuned and perfected to become more reliable and efficient.

While setting them up requires effort—training them with data and defining clear objectives—the payoff can be enormous. Once deployed, they can handle entire processes with minimal input.

What does this mean for you and me?

I hope this description helps you understand why generative AI agents are so important. Many businesses already understand that, and agents are spreading rapidly.

Companies are looking at workflows, identifying tasks, and designing AI agents to automate processes. Many tech consultancies and companies are also creating platforms and tools to produce and manage AI agents.

The solutions range from very sophisticated enterprise-level solutions like Cognizant's Neuro AI (a client) to tools accessible to independent developers or small businesses with no coding experience.

The vision isn't of a single all-powerful AI doing everything. It's about thousands of specialised agents working together across organisations and processes.

What does this mean for you or me? AI agents will make at least part of what we do today, so we need not only to understand how they work but also to have a much more precise view of what we do at work and where they can help—or not.

We need to focus on tasks where human skills are more relevant and less interesting to substitute. We also must be creative and think about how these agents will allow us to do more than we do today. The view doesn't need to be about fear of becoming irrelevant. It can be about the possibility of becoming better at whatever we want to do.