As ALBA turns 16 this year, I am increasingly asked how the company continues to operate in the age of AI.
When ChatGPT entered the mainstream at the end of 2023, a close friend and regular client called me and said, “ALBA’s finished.”
It was a fair question. The nature of editorial work had changed almost overnight.
When I founded ALBA in 2010, things were more straightforward. We received documents, corrected mistakes, improved grammar, and strengthened the overall flow of the writing for a particular audience. It was skilled work, but often relatively formulaic.
That is no longer the case.
How AI Has Changed Academic Writing
Today, some clients still arrive with work that is clearly their own: careful, rigorous, and closely tied to the literature they are engaging with. But a growing number of documents now come to us after some degree of AI intervention. Sometimes the effect is light. Sometimes it is far more substantial. In many cases, the real difficulty lies in working out where the author’s own voice begins and where the machine has flattened or diluted it.
This is now one of the central challenges in academic editing.
The Problem with AI “Polish”
Many texts we receive have been through some form of AI “polish”. That creates immediate problems. Was the draft generated from scratch, or was it a carefully researched piece of writing that was passed through AI at the end? Once AI has left its mark on a text, the answer is not always obvious. The result can be writing that sounds superficially competent while losing the precision, individuality, and intellectual texture that serious academic work requires.
A senior journal editor recently put it to me very bluntly: “As things stand, one sniff of text generated by AI, and the manuscript’s rejected.”
That may sound harsh, but the wider point is clear enough. Editors are under pressure, journals are flooded with submissions, and anything that feels generic, artificial, or insufficiently aligned with submission requirements is vulnerable very early in the process.
That is why ALBA’s work has changed.
What ALBA Now Focuses On
In many cases, our role is no longer simply to improve the language. It is to recover the author’s real voice, restore precision, and make sure that the text reads like the work of a serious researcher rather than the output of a machine. Sometimes that requires a light editorial touch. Sometimes it requires much deeper excavation.
At the same time, the shift has sharpened our focus on the parts of editorial work that matter most. We are able to pay closer attention to argument, structure, tone, and journal requirements. We can look more carefully at whether a manuscript truly meets submission guidelines and whether it is ready to be taken seriously by editors and reviewers.
That matters because journals are not only assessing the quality of the research itself. They are also making quick decisions based on presentation, tone, and compliance. A manuscript that feels generic, overprocessed, or out of line with a journal’s style and conventions is at risk before its argument has even had a proper hearing.
ALBA is therefore focused on three things above all: restoring the author’s real voice, providing substantive editorial guidance, and ensuring strict adherence to submission guidelines.
In that sense, AI has not made serious editorial work obsolete. It has made it more necessary, and more exacting, than before.
