Dear AI, Draft This Manuscript: The (Very Near) Future of Scientific Writing

Once Upon a Prompt 

In academic and clinical research, time is a precious commodity—and so is clarity. With artificial intelligence (AI) writing tools evolving at breakneck speed, researchers and medical writers are now asking a vital question: How far can AI take us in crafting better, faster manuscripts? The answer lies in the growing integration of AI-powered writing assistants and the complex terrain of ethics, journal policies, and return on investment (ROI). 

Let’s look at where we’re headed. 

The State of AI Writing Tools: From Assistants to Co-authors 

AI is no longer limited to spellcheck and grammar correction. Today’s tools do much more: they refine tone, suggest citations, summarize background literature, and even help rewrite awkward paragraphs. 

Researchers are turning to generative AI models to generate early drafts of sections like the introduction or methods, summarize complex datasets, and respond to peer reviewer comments (Buriak et al, 2023). While AI is not (yet) replacing expert writing, it is drastically accelerating early-stage manuscript development. 

The Trajectory: What’s on the Horizon? 

AI’s role in manuscript preparation is expanding. Here’s how its evolution might unfold: 

1 to 2 Years: Seamless Workflow Integration  

Expect deeper integration with citation managers, journal submission platforms, and manuscript templates. Imagine real-time suggestions not only for grammar but also for adherence to a journal’s scope and style. 

3 to 5 Years: Intelligent Drafting and Tailored Feedback 

We’re moving toward AI systems that understand disciplinary nuances—editing with awareness of terminology, tone, and statistical rigor. These tools may flag missing references, suggest clarifications, or even recommend target journals based on draft content. 

5 to 10 Years: Predictive and Collaborative Capabilities 

Longer term, AI may assist in interpreting preliminary results, proposing discussion points, and co-developing content across research teams. With advances in natural language generation and data synthesis, AI could serve as a brainstorming partner in generating hypotheses or proposing narrative flows. 

Challenges on the Road Ahead 

With power comes responsibility, and AI-enhanced writing is no exception. 

Disclosure and Transparency: As editors grapple with the impact of AI, journals, such as Nature, Science, JAMA, and PLOS to name only a few, are introducing guidelines requiring full disclosure of AI use to facilitate transparency (Science). To date, all journals prohibit AI from being listed as a co-author. As AI tools do not meet authorship criteria (PLOS) and cannot provide authorship consent nor respond to peer review, they are not eligible to be listed as co-authors and lack the required accountability (Nature). 

Ethical Use in Clinical Research: A growing debate surrounds AI’s role in clinical trial design. If AI significantly influences protocol development or patient communication strategies, should its involvement be disclosed in trial registries like ClinicalTrials.gov? Some argue yes, particularly to maintain reproducibility and transparency in trials (Askin et al, 2023). 

Skill Degradation and Over-Reliance: There’s a risk of losing the art of clear scientific communication. While AI can speed up writing, over-reliance may lead to manuscripts that lack critical reasoning, personal insight, or scientific nuance. 

ROI: The Numbers Make a Case 

Early adopters of AI-enhanced manuscript writing are already seeing tangible benefits (Maddali, 2025): 

• Time Savings: Drafting time can be reduced by up to 50%, especially for non-native English speakers or junior researchers 

• Improved Manuscript Quality: Cleaner initial drafts mean faster peer review and a reduced need for heavy editing 

• Higher Submission Success: AI-assisted authors have reported fewer desk rejections related to clarity or formatting 

• Cost Efficiency: Less dependency on external editing services and more bandwidth for in-house teams reduces pressure 

  
  

For medical writers and clinical trial authors, these time and cost savings translate directly into faster drug development cycles, quicker publication timelines, and increased scientific impact. 

The Bottom Line: Coexisting with AI 

AI won’t replace human authorship, but it will change how we write. It’s our responsibility as researchers, writers, and editors to steer this evolution wisely. To maximize ROI while maintaining scientific integrity, make sure to disclose AI use transparently, stay current with evolving journal policies, view AI as a tool rather than a crutch, and invest in upskilling to complement human expertise with AI’s efficiency. The future of manuscript writing isn’t just automated—it’s collaborative, strategic, and potentially transformative. 

For more insight into how AI can be used to augment your team and provide you with a competitive advantage, check out our related blogs on AI’s hidden KPIs and other applications of AI within your medical writing department. 

Sources 

Artificial Intelligence (AI). Springer Nature. Accessed on July 10, 2025. https://www.springer.com/gp/editorial-policies/artificial-intelligence--ai-/25428500 

Askin S, Burkhalter D, Calado G, El Dakrouni S. Artificial Intelligence Applied to clinical trials: opportunities and challenges. Health Technol (Berl). 2023;13(2):203-213. doi:10.1007/s12553-023-00738-2 

Authorship. PLOS One. Accessed on July 10, 2025. https://journals.plos.org/plosone/s/authorship 

Buriak JM, Akinwande D, Artzi N, et al. Best Practices for Using AI When Writing Scientific Manuscripts. ACS Nano. 2023;17(5):4091-4093. doi:10.1021/acsnano.3c01544 

Change to policy on the use of generative AI and large language models. Science. Accessed on July 10, 2025. https://www.science.org/content/blog-post/change-policy-use-generative-ai-and-large-language-models 

Maddali MM. Pro: Artificial Intelligence in Manuscript Writing: Advantages of Artificial Intelligence-Based Manuscript Writing to the Authors. Ann Card Anaesth. 2025;28(2):198-200. doi:10.4103/aca.aca_6_25