AI Video Editing for YouTube: My Complete Workflow

my youtube workflow now uses ai for pretty much every stage of production and honestly it’s changed how fast i can turn around videos. not in a “replace the creative work” way – more like it handles the boring repetitive stuff so i can focus on the parts that actually matter. been running this setup for about 8 months now across 40+ videos so i have some actual data on what works and what’s a waste of time.

## scripting and pre-production

this is where ai saves me the most time, probably 2-3 hours per video. i start by feeding in my rough notes and a loose outline, then iterate on the structure before i ever hit record. a few things i’ve learned:

– don’t let it write full scripts word for word. the output sounds like a robot wrote it and your audience will feel that even if they can’t name why
– use it to generate a “question bank” – like 15-20 questions your target viewer probably has, then build your script around answering those
– have it punch up your hook specifically. first 30 seconds is where retention dies and it’s genuinely good at generating 5-6 hook variations fast
– run your draft script back through and ask it to flag anything that sounds too formal or corporate. weird prompt but it works

## b-roll sourcing and rough cut assembly

this part surprised me. i describe scenes or concepts and have it generate shot lists with specific visual directions – things like “wide establishing shot, soft morning light, subject in left third of frame.” it won’t find the footage for you but it makes you so much more intentional when you’re actually searching or shooting. cuts my b-roll hunting time in half because i know exactly what i’m looking for.

for the edit itself, i use ai-assisted transcription to do a paper edit first. i read through the full transcript, mark cuts in text, and then the edit basically assembles itself from those decisions. if your video is 12 minutes long, you’re editing maybe 25-30 minutes of raw footage. doing a paper edit drops my actual timeline assembly from 3+ hours to under 90 minutes consistently.

## thumbnails are where people get lazy about this

hot take: most creators use ai for thumbnails wrong. they generate a full image and slap it on. what actually works is using it to brainstorm the concept first – what emotion should this thumbnail trigger, what’s the visual contrast, what’s the text hierarchy. then you can shoot a photo specifically for that concept or build it properly in a design tool.

things i test every upload now:

1. curiosity gap vs. direct value thumbnails (curiosity wins about 60% of the time for my niche)
2. face vs. no face (still varies wildly, no consistent winner for me)
3. text overlay length – i keep it under 5 words max and that’s helped ctr noticeably

the whole workflow together has gotten my average production time from about 14-16 hours per video down to 7-9 hours. the quality hasn’t dropped – if anything consistency has gone up because i’m less burned out when i actually get to the creative decisions.

one thing i’ll say: the environmental cost of running all this inference adds up and it genuinely gets overlooked in these “ai changed my workflow” posts. worth thinking about how much you’re actually running vs. what’s providing real value vs. what’s just novelty.

what part of your workflow is still eating the most time right now? curious if anyone’s cracked the post-production audio cleanup piece better than i have because that’s still kind of a mess for me.