How to Pick AI Design Tools by the Job, Not the Feature List

Search "best AI design tools" and you'll get twenty lists that all rank the same twelve products out of ten. It's a useless exercise. A tool that scores 9.2 for a social media manager can be completely wrong for someone preparing a carton for press — and the score never tells you which one you are.

We run packaging, print and campaign work out of Sydney and Wollongong, so tools get judged here by whether they survive a real job: client artwork, a printer's spec, a deadline. What follows is how we actually decide — and the ten jobs we sort every tool into.

Why feature lists mislead

Feature parity is now cheap. Almost every major platform generates images, removes backgrounds, upscales and writes captions, because most of them are calling the same handful of underlying models. What differs is the last ten percent — the part that decides whether the output is usable.

That last ten percent is invisible in a feature table. Does the "vector export" hand back real paths, or a traced bitmap wearing an .svg extension? Does the upscaler invent detail that quietly changes a logo's letterforms? Is the training data licensed in a way your client's legal team can live with? Those are the questions that decide a project, and none of them fit in a comparison grid.

The ten jobs

Sorting tools by job makes the choice obvious. These are the ten we use, and they map directly to our AI design tools directory:

1. Upscaling and enhancement — rescue a low-res file or push a render to print size.
2. Image generation — create an original image from a brief.
3. Vector and logo output — get a file that scales without falling apart.
4. Typography — render words that are spelled correctly and read cleanly.
5. Editing and retouching — change something in an image you already have.
6. Mockups and packaging — show a design on a product before it exists.
7. Video and motion — put movement behind an approved key visual.
8. Brand systems and colour — build or stress-test an identity.
9. UI and product design — go from idea to working interface.
10. Workflow and agents — chain the steps instead of doing them by hand.

Where the honest differences are

Aesthetic ceiling vs. prompt obedience

Midjourney still produces the most striking imagery straight out of the box, which is why it lives in our concepting stage. But it's not obedient — ask for a specific product on a specific angle with specific copy and you'll fight it. Models that follow instructions literally look duller in isolation and behave far better inside a layout.

Raster output vs. real vectors

This is the single biggest trap for anyone doing print or packaging work. Recraft is genuinely unusual in returning editable SVG; most "vector" features are auto-trace with a nicer interface. If the asset is going on a pack, a vehicle wrap or a billboard, test the export in Illustrator before you commit to a tool.

Invented detail is a liability

Upscalers don't recover detail — they generate plausible detail. That's fine on a moody background and unacceptable on a nutrition panel, a barcode or a registered trademark. We keep creativity settings low on anything regulated, and reach for a conservative, photography-focused upscaler when the source is a real camera file.

Provenance is a client question, not a tech one

For ASX-listed and government clients, "where did the training data come from?" arrives before "does it look good?". That single question rules out several otherwise excellent tools and makes licensed-content models the default on those accounts.

Connections matter more than features now

The most useful shift of the last year isn't a better image model — it's tools being able to read your actual project. The Model Context Protocol (MCP) lets an AI assistant pull the real brief from Notion, the real frame from Figma and the real approved file from Drive, instead of guessing from a prompt. An average model with your genuine brand rules beats a brilliant model with none.

We've written up how to set those connections up safely on our connections page — each one authorised by you, scoped to what you choose, and revocable from the provider.

A stack that actually works

A small marketing team rarely needs more than five tools: one generalist subscription, one specialist upscaler, one vector tool, one mockup tool, and whatever their files already live in. Everything past that is subscription drag. Our Stack Builder will name one tool per job based on the work you actually do and the budget you actually have.

The part AI still doesn't do

None of this replaces judgement. AI will produce fifty on-brief options; deciding which one earns shelf space against six competitors, in the two seconds a shopper gives it, is still a human call informed by having watched it play out before. The tools got faster. The standard didn't move.

If you'd rather not audit thirty products yourself, start with the directory — or talk to our team and we'll tell you what to keep, cut and consolidate.