How AI Writers Will Shape Academic Research in the Next Decade

by Imed Bouchrika, Phd

Co-Founder and Chief Data Scientist

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If you talk to a couple of people in academia about artificial intelligence writing programs that are currently in existence, you might get wildly different reactions from them about the usefulness of such tools. While one individual might feel they’re the best thing ever, another may feel they’re ruining the integrity of collegiate-level education.

The truth probably lies somewhere in between. One thing is certain, though: this tech has arrived, and now that the genie is out of the bottle, there’s no putting it back.

Consider how a writer might use existing tech like an AI personal statement builder. An AI personal statement generator can save someone time who is trying to create a compelling reason for a university to accept them into its undergraduate program. A personal statement generator AI writer might also come in handy for someone who’s attempting to write a persuasive argument for class. This type of essay maker might be regarded as unethical by some teachers or professors, though.

It’s becoming increasingly more difficult to find any aspect of either academia or the working world that AI is not infiltrating. An office worker who wants to maximize their productivity with digital checklists and AI can now do so. There are tools like myStylus that can write an essay that is indistinguishable from what an expert in a particular field might produce.

No matter how you feel about this kind of technology, it should be fascinating to see what it does to transform academic research over the next decade. It’s worth talking about, so let’s do so in detail right now.

What is the Point of Academic Research?

Before we plunge too deeply into the subject of how AI-infused programs might influence research in academia, it’s important to understand the point of this kind of endeavor. Academic research:

• Exists to systematically expand and explore a specific area of knowledge
• Asks questions about a certain field
• Presents findings, collects data, and analyzes relevant information   

It’s probably accurate to say that some undergrads have found it tedious over the years. If they’re pursuing potentially lucrative degrees, though, this process is probably going to enter into that.

Still, it’s hard to deny that some individuals are probably going to look at AI-powered writing tools as a godsend, even the relatively rudimentary ones that exist today. Probably their only concerns are getting caught using them if a professor explicitly forbade them from doing so.

Now, let’s get back to talking about how these kinds of programs are most likely going to make an impact over the next 10 years and beyond.

Personalized Feedback

Let’s imagine a scenario for a moment. You’re a young person fresh out of high school. You’re looking at some of the best college majors to potentially pursue, both in terms of salary and growth opportunities.

You settle on something for which you believe you have the aptitude. You find it interesting, and you think you can see yourself doing it as a career.

There’s a downside, though, or what you perceive as a downside. You need to do a lot of academic research if you are going to get a degree in this subject. It has always been that way, but it still seems pretty daunting to think about the many hours and days of studying that are going to go into your eventual BA or BS.

You feel like you’re the perfect candidate to use some of the AI-infused programs that are out there. However, some of your professors explicitly state that you will get a zero if you get caught using them.

You feel like there’s a way you can still take advantage of such an algorithm. Maybe you feel that you can write a research paper on your own. You can then use this kind of AI-powered bot to:

• Give you feedback on your writing style and the clarity of your vision
• Examine the structure of your argument and make suggestions regarding how to improve it  

In essence, this is only a somewhat more complex analysis of what a current program like Grammarly can do. In addition to checking for things like spelling, syntax, or grammar errors, you’re just getting an opinion from a bot that was made for the expressed purpose of analyzing what you wrote about an academic subject.

Language Accessibility and Translation

Let’s use that same scenario again. You’ve selected an affordable Bachelor’s degree from a reputable university, and you’ve started to take classes in it. Maybe you’re even a couple of years into getting that degree, so you’ve started to take some upper-level classes.

You have written a research paper, and you have a roommate who wants to read it. However, English is not their first language. You can feed the essay into one of these AI-powered bots. By doing so:

• It can easily translate the paper into your roommate’s native language
• It can slightly modify sections where the information isn’t as easy to comprehend through a literal translation 

With an AI-powered tool that can do both literal translations into multiple languages and can also modify any sections that might confuse readers from other cultures, you are once again putting this kind of tech to use in a helpful way.

Drafting and Editing

Maybe you’re trying to write one of these research papers based on data you’ve gathered. However, you’ve always had a hard time putting your thoughts down on paper and getting them in the right order.

You use one of these tools and attempt to collaborate with it. It’s not literally writing the paper for you. Rather, it could be said that the two of you are working in tandem. You can:

• Feed the bot a rough version of your first draft
• Ask it for help with sections like the introduction or your central thesis
• Ask it about whether it agrees with some of the methods and results that you included in the paper  

More advanced versions of existing tools should have no problems doing these things. Again, it’s not that you’re simply giving the bot a topic and telling it to create a research paper based on what others in your field of study wrote in the past. It’s a collaborative effort where the algorithm helps you write with more clarity.

You might go through this process multiple times. Each time, you think that your vision for the paper comes closer to becoming a reality. You might feel that the final version is as strong as you can possibly make it.

The Generation of Hypotheses

It’s even possible to envision scenarios where this kind of collaborative effort could go a step further. Let’s say that you’re a couple of years into your undergrad, and you’re trying to write an advanced-level paper on an area in which you now have some expertise. One of your professors has given you a challenging assignment, though.

They want you to explore a subject that has already had many books and papers written about it. You know that there’s seemingly endless research and hypotheses relating to this one particular subject. You’re racking your brain trying to come up with a fresh angle or take on which you might write a paper.

You ask the bot for help. You can:

• Feed it the subject
• Ask it to come up with a fresh list of ideas for research papers that haven’t been written before

The chances are very high that the bot is going to be able to come up with some ideas or hypotheses that no one has ever written about in the past. Remember that even the current versions of these helper bots were trained using enormous sets of academic writing and data. They have the same capabilities as supercomputers, and they also have access to data sets the size of which is hard for the human mind to even fathom.

The bot should be able to lead you in directions that never would have occurred to you on your own. Once you pick one from the list that it gave you, you can start working on a fresh direction and area of study for this topic.

Data Visualization and Analysis

If you’re researching something in an academic context, that means you need to analyze and scrutinize it in a way far beyond writing a simple book report or proposing an elementary theory. You need to go deeper, particularly if you have completed your undergrad and you’re going back for a more advanced degree.

The amount of data visualization and analysis that you can do on your own is limited by your human mind. An AI algorithm can go so much deeper, though, and it can do so effortlessly.

Let’s say you want to do a deep dive on a particular subject. You have a theory or hypothesis ready to go. Now, you need the data to back it up.

The algorithm should certainly be able to help you in this regard. You might tell it to:

• Analyze all existing data sets on this subject to which it has access
• Identify any patterns that previous researchers might not necessarily have been able to see
• Generate visualizations that support its conclusions

If you take this approach, the data you get back should be streamlined and helpful to you in a way you simply never could have achieved on your own, even if you had studied this particular subject for the rest of your life. By looking at what the bot gave you and asking follow up questions, you should be able to come up with some ideas that never would have otherwise occurred to you.

The deeper insights into the data sets that you fed the AI program should stimulate your brain cells. With your existing knowledge of the subject matter and the new presentation of this data, you might even be able to come up with a doctoral thesis idea that no one else has ever written about or explored at any length before.

Enhanced Reviews of Existing Literature

The possibility of enhancing reviews of existing literature with one of these tools is also worth mentioning. A moment ago, we mentioned how you should be able to instruct one of these bots to scan vast databases. These include thousands or tens of thousands of research papers that were written by the sharpest minds in your particular niche or field of study.

If you have an interest in a certain aspect of this niche or field, you can ask the bot to try and locate all papers that were written about it, even if the topic is relatively obscure. It should be able to do so, and probably within only a couple of minutes.

Next, you might ask it to:

• Generate a comprehensive study of a topic so you can eliminate any avenues that other researchers have already pursued
• Extract key findings that either back up or refute a theory you might have

This kind of rapid scanning and breakdown of prior academic research efforts should help you clarify your vision. If you find that no one has written about something in the exact way that you would like to approach it, then you’re probably on the path toward an original concept of which your professor would approve.

We’ve now spent some time talking about what these kinds of helpers might do for you as they become ever more advanced over the next few years. Let’s continue by running down some of the ethical concerns and potential challenges that we would be remiss if we didn’t mention.

Is It Possible to Over-Rely on AI?

Even now, when these kinds of programs are arguably in their infancy, there’s a question that’s being asked by just about every instructor, professor, and teacher. That applies to middle school and high school, not just to collegiate-level educators.

Is it possible to be over-reliant on AI? And, if it is, what can be done to avoid this when it is rapidly becoming so prevalent?

It would be disingenuous to suggest that this is not a legitimate concern. After all, if current versions of this technology can write a paper on Moby Dick for a ninth grader in 30 seconds, what might future versions bring to the table?

It’s probably best to look at it in this way. If the total prohibition of such tools is virtually impossible, then professors and teachers who allow their use but attempt to regulate it will probably be in a better position to help their students get a quality education, not to mention preserve their own sanity.

Collaboration is the Key 

How might that be accomplished, though? We already spoke about possible collaborative efforts between these new and emerging forms of AI and future students who have been tasked with the writing of research papers.

Rather than a total prohibition of their use, a teacher who tells their class that they can use the AI in a certain way, but not in others, is probably being more reasonable than one who says they will give their students a zero if they detect even the slightest use of such tools. Frankly, it’s already impossible to tell what’s AI writing and what isn’t, and the technology is nowhere near as advanced now as it’s probably going to be.

What About High-Level Research?

As for high-level researchers, such as those who already have an undergraduate degree and who are striving for a Master’s or a Doctorate, they will probably need to reach a point where they must disclose to their instructors exactly how they are using the AI, if at all. It’s probably unrealistic to ask them not to use it in some of the ways that we’ve described.

Once again, if academia is going to stop itself from becoming a total joke, it’s going to be necessary to find a middle ground, a path forward where the use of AI tools is accepted, but only within certain rigid frameworks. Researchers who have integrity should hopefully have no issue disclosing how and if they’re using such tools. That’s putting a lot of faith in humanity’s inherent honesty, though.

Should Academic Institutions Adapt Their Curricula for AI Integration?

As research becomes increasingly driven by AI capabilities, academic institutions are compelled to reexamine their curricula and pedagogy to balance technological innovation with rigorous scholarship. Institutions should consider establishing clear guidelines for the ethical use of AI while introducing specialized courses on digital literacy and data analysis that leverage these emerging tools. Such curricular updates can empower both educators and students to harness AI benefits responsibly, ensuring that research methods remain transparent and integrity is maintained. Universities may also look into innovative program structures, such as the fastest Ed D programs, to provide accelerated educational opportunities that align with this evolving landscape.

How Can Academic Institutions Strengthen Research Integrity Amid AI Expansion?

Academic institutions face the challenge of preserving research integrity while integrating powerful AI tools. To address this, clear guidelines on the transparent disclosure of AI assistance and regular verification of AI-generated outputs are essential. Institutions can implement systematic audits of AI-driven research work, using advanced plagiarism detection and manual expert reviews to confirm originality and accuracy. In addition, promoting digital literacy and offering specialized training modules focused on ethical AI practices—such as those found in programs like cheapest online masters education—will equip researchers with the skills to identify data biases and validate sources. This multifaceted approach ensures that enhanced productivity does not compromise the quality and credibility of academic research.

Is AI Making Doctoral Education More Accessible and Affordable?

As AI continues to reshape academic delivery methods, its integration into doctoral programs can significantly reduce traditional barriers—both financial and logistical—to advanced education. With tailored digital platforms that support personalized mentorship, real-time data analysis, and interactive coursework, institutions can offer more efficient pathways for candidates seeking to further their expertise. This technological shift enables prospective students to explore options that were previously cost-prohibitive, such as cheap online EdD programs, while still maintaining rigorous academic standards and research integrity.

None of This is Going to Be Easy

It would be the height of foolishness to say that any of this is going to be simple. It calls to mind the scene in Jurassic Park where Ian Malcom talks about how scientific advancement got to a point where humans shouldn’t have asked if they could but instead should have asked if they should.

That is the central question posed by artificial intelligence, and not just in the areas that we have discussed in this article. It would not be hyperbole to say that AI is the central question of our time. How smart, in fact, do we want it to get?

That is far from an easy question to answer. Only the coming years might provide some clues, but as time passes, what amounts to thinking machines are likely only going to get smarter.