Will AI Agents be Taking Over Writing Soon?

Can AI Take over a Writer's Job Soon?

Writing was such a tedious task once upon a time, but now with so many AI tools, both free and paid, anyone can complete their writeups, whether fiction, academic, technical, or even creative. About 90% of content marketers already utilize AI tools while 86% students use AI in their studies. So, yes AI is definitely helping a lot, but the main question is, will it thoroughly replace writers altogether?

Generative AI for Content Generation and Agentic AI for Content Assistance

Generative AI has impacted almost every domain of job because every job requires at least some form of report writing, digital marketing, or at the very least, information support from platforms like ChatGPT. Now, with generative AI tools, you can create images, videos, or texts for your specific niche. There is no need to buy an expensive camera or master your language skills to do these cost-consuming and prolonged tasks.

While generative AI only generate your material, it only does so on pre-trained and very specific dataset. Meaning, it can’t perform creative tasks or assist in real-time novel issues. This is where Agentic AI or AI assistants take their role. These AI agents have the ability to adapt to new conditions and provide useful insights in any field including any form of writing.

Will AI threaten your job prospects as a Writer?

Generative AI is already in the market, and it can generate each and every form of writing you ask of it, while AI agents can probably do much more. The major concern is, if these tools will eventually snatch away human’s freedom of thought.

To understand this, we need to look at how exactly AI can take over the role of a writer and what are its future implications for the job industry in general.

Predictive AI can Read Complex Patterns

AI tools are trained over extensive datasets before they are available for public use, making it worthwhile for identifying patterns that might be overlooked from a human’s perspective.

For example, if you want to develop an equation using three different variables, you might need to look into which method to use and then without any software, its just a hit and trial game with available data until you can figure out the pattern. Meanwhile, AI can perform all these tasks at once to come up with an equation in just a few seconds given you’ve trained its feature of equation generation beforehand.

AI Agents can do the Task in Seconds

Do you know, on average, a person can save about one hour of work daily using AI tools? In fact, it’s not just that, it can perform all the repetitive tasks in a few seconds, saving both time and manual work.

In writing, you often come across tasks that you’ve done countless times before, say, introducing a term before talking about it, or final formatting of your write-up before submission. AI can help with all these tasks swiftly, as long as it has its prior trained data on those terms and available formatting options.

AI Agents can Automate Reviewer Suggestions

Just a few years back product developers and sellers needed extensive peer or user reviews to improve or increase their product’s quality and authenticity. This task required surveys spanning over days, sometimes even years, but with AI agents rising capabilities, it can even automate reviewer suggestions. Some developers have even introduced their custom-made AI assistants, like ArtificialIntelligence Review Assistant (AIRA).

These agents not have the ability to streamline multiple steps, including check on language quality, plagiarism detection, and identifying potential conflicts of interests to generate close-to-human review suggestions.

AI Agents can Take Over Creative Professions

Often in writing profession, the more creative the field is the more difficult it is for generative AI to provide a satisfactory answer. Take the field of economics, for example, which is creative, analytical, and dynamic. The challenges are almost always unorthodox, making simple architecture AI like ChatGPT to not produce satisfactory text generation.

AI agents, on the other hand, are built to provide assistance in such dynamic settings. It functions upon multiple variables and datasets to assist in demanding fields like medical, or economics.

Shortcomings of Agentic AI

AI agents are still under extensive research to improve its functionality and there are multifaceted issues for its immediate implementation, unlike other forms of AI. Despite its potential to revolutionize task handling, many are still suspicious of its actual support.

Potential of Bias

In agentic AI, bias can be introduced through various means, most common of which are, human or algorithmic bias. Based on the agent’s creation or equations used by the developer, it can treat one set of data completely different from another set of data. A recent study at the University College London found that AI even has the ability to intensify human bias, which may lead to completely unreliable results.

Overfitting concern

Another form of bias is data dependency, which is usually known as overfitting. Its when the AI agent is trained on a very specific dataset making it unreliable to perform on a completely different type of data. Moreover, its often difficult to avoid overfitting if the data is too vast leading to human mistakes during training phase of the model.

This makes AI agents work very similar to other types of AI in trying to analyze and regulate data from extremely practical fields like writing.

AI Transparency concerns

Most experts refer the AI agents as ‘black box’ because of its inability to provide explanation to reach a specific result. Besides field experts, even a fair amount of younger generation professionals could not trust AI as observed by the Oxford University Press Survey in 2024. Scientists are now searching for ways to adopt tools and techniques, such as explainable AI, that could permanently resolve this trust and transparency crisis.

A need for AI Literacy

For modern and upcoming writers, AI literacy has become a core requirement for producing high quality material. It would serve as a precautionary measure just to stay ahead of all the things AI agents might be taking over in the future. The tools can save them a lot of time in early-stage material development for writing and a writer can instead focus on more creative aspect of it.

Conclusion

With all the pros and cons of Agentic AI in might, we can conclude that it is highly possible for these assistants to completely replace the writers in the coming years, unless the writers keep themselves up-to-date with all the upcoming AI tools and practices.

Tasks such as plagiarism detection, improving way of expression have already fallen into AI’s hands. As a writer, you have to find things which can improve your write-ups even further.

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