Should an AI writing assistant chime in before you've started, mid-sentence, or after you're done, and who decides?

This explores when in the writing process an AI should offer suggestions, and which timing approaches the corpus supports. There is no head-to-head test of, say, suggesting on a pause versus only on request, so nothing here names one best schedule. The material does agree on three points: timing is a design choice of its own, it should track where the writer is in the process, and the writer should help set it.

Timing gets less attention than it deserves. One line of research splits AI support into three independent axes, type, timing and scale, and finds that they jointly decide whether help helps or harms. Most work tunes only the type of support and leaves timing and scale at whatever the default happens to be, which is where the real impact turns out to sit (When and how much should AI interrupt human reasoning?). So how often and how early a suggestion arrives is part of what the suggestion is.

Stage is the most useful guide. In one study, writers leaned on LLMs most heavily during ideation, then when organizing thoughts, then when drafting. They also came back to the AI for ideas whenever they hit a block, and unexpected outputs often sent them in new directions (How do writers use AI through different creative stages?). That points to early suggestions, plus suggestions on demand when the writer is stuck. A separate one-week study found that writers could set up proactive AI partners in advance by choosing the partner's role and how proactive it should be. They then used the suggestions to generate ideas and to keep an eye on their own writing (Can writers benefit from configuring AI writing partners in advance?). Here the writer sets the timing before writing starts, so the system doesn't have to guess.

The caution below is my inference from these studies. None of them tested timing directly. Writers edited AI-generated paragraphs only 23% of the time, and the edits left the text about 96% similar to the original (Do writers actually edit AI-generated text before publishing?). That text pushed the writer's voice in a consistent direction across all 29 measured dimensions, including sounding more extreme, more confident and more privileged (Does AI writing assistance change how readers perceive the writer?). A suggestion that arrives as ready-to-paste prose at the drafting stage therefore tends to go through nearly untouched. An idea offered at the ideation stage has to be rewritten by the writer before it becomes text, so more of their own voice survives.

The last piece is that nobody knows the ideal moment. A human-agent system study says so outright. It found no ground truth for the best time to defer to a human, so it spread the decision across several touchpoints: planning together, checking actions before they run, and verification (When should human-agent systems ask for human help?). For writing, that suggests offering several low-cost entry points, such as a planning stage, help on request, and a review pass, rather than one perfectly timed nudge. The model won't find the moment for you either. Its text generation is sequential but has no reflective pause built in (Does AI text generation unfold through temporal reflection?). Any sense of when to speak has to come from the interface or from the writer.