From Tool to Collaborator: How GenAI Is Transforming Academic Writing

Earlier this year I had the privilege of attending the European Conference on Education Research (ECER), the annual meeting of the European Educational Research Association (EERA). I attended as a representative of my doctoral program in Educational Sustainability and also gained insights to support my role as a Strategic Relationship Development Manager at Autodesk Research, where I help build connections between higher education, industry organizations, and our team. I went with a dual purpose: to represent my program and to bring back learnings from my European colleagues, especially about AI.

One panel session I attended centered AI’s use in university level writing competencies. The panel discussed entry level university writing competencies all the way to dissertation and post-doctoral work. Following the panel, a debate started after one audience member asked, “We may want to take a step back and ask ourselves, what is writing?” This one question challenges the traditional skillsets and competencies considered requirements for the act of writing. The collective group quickly realized that the act of writing has always been dependent on the tools at hand.

The question – what is writing? – exposes a tension that the academic community has yet to resolve in this moment of rapid technological advancement. We continue to evaluate the act of academic writing as an isolated act of pure human action, when it has always been a collaboration between our own thinking and the tools available to us. With the emergence of generative AI, this collaboration with tools has become more visible and impossible to ignore.

We can take that question a step further and ask, what do we mean when we are discussing academic writing and writing for research’s sake? My initial answer centered around sharing or communicating facts, findings, research processes, results, or a set of ideas. Just for fun, I posed a question to both Claude AI and ChatGPT, asking what is academic writing?

Both platforms provided similar responses, focusing more on the idea of academic writing than the content of such papers. They shared that academic writing aims to present research findings and ideas that use evidence-based, structured formats, with objective tone. Furthermore, academic writing tends to use technical terms and engages with existing scholarship to contribute to an academic field. It is a formal style of writing that leverages formal citation systems. There was no focus on the actual act of writing; instead, both platforms emphasized the impact of this form of communication.

If we lean into the impact focus or the goal of academic writing, we can tease out an evolved version of the skillsets required to do academic writing that can incorporate new tools like GenAI. If GenAI can become a collaborator, or even a tool like word processing, then the focus of the skills can lean more into the ability to appropriately convey research outputs. And, similarly to software coding, isn’t academic writing a prime candidate to be positively impacted by GenAI as the formal citation systems provide so much of the standard writing style and frameworks?

Reflecting on my own academic writing journey, I’ve begun to use AI often and GenAI has really become a great partner for me. As a self-proclaimed math and science girl, I’ve never much enjoyed writing, at least not in the same way I enjoy math. But I’ve found a friend in GenAI to help me when I get stuck or need a nudge to continue my flow of thinking. I often use GenAI to have conversations about the ideas I’m developing with my writing. And occasionally to help with the flow of a sentence. I had never thought about GenAI writing my full dissertation or even how that might work. But there might be a future world where the act of writing is heavily assisted, and our focus is on the communication of the findings.

The real opportunity isn’t to police AI’s presence in academic writing, it is to design systems whose use is transparent, collaborative, and ethical. Peer review within journals should evolve to assess the root of reasoning and responsibility. Additionally, the use of AI in academic writing can support clearer and more accessible academic research thereby widening the audience for academic thought. Academic writing can be quite dense and often difficult to read and consume. What if AI can help bring clarity and remove unnecessary jargon that is claiming authority and often obscuring true meaning? With AI as a co-author rather than a ghostwriter we may see improved positioning of research results and a more democratized academic community.

The AI train has left the station, and we cannot just ignore it. We must jump onboard. However, like many previous historical moments of technological advancement, we can intentionally build systems to navigate how humans and AI will work together. The question isn’t whether AI can write a dissertation — it’s whether academia and the research community can evolve fast enough to remain honest about how all writing, human or not, actually happens. Writing has never existed without tools; writing has evolved through them. Now it is our turn to evolve too.

These ideas are grounded in my own experience as both a researcher and practitioner. They are intended to contribute to the broader conversation around academic writing and AI, and should not be taken as official positions of Autodesk.