The AI Digital
Assets Handbook
Create production-ready digital assets with AI: the tools, the setup, the prompts, and the workflows that actually ship.

Eighteen chapters, five parts.
Foundations
- 1The New Studio
The 2026 landscape, what AI digital assets are, and an honest map of what works and what still fails.
- 2How the Machines Make Pictures
Diffusion and latent space in plain language, and the model families worth knowing.
The Toolkit
- 3The Hosted Generators
A working tour of the cloud tools and when to reach for each.
- 4Your Local Studio
Which interface fits you, and the hardware honesty nobody puts in the tutorial.
- 5Getting Models
Where the models live, the file types you juggle, and how to spot a good one.
The Craft
- 6Prompting
The six-slot brief, the tokens that actually steer a model, and the parameters worth touching.
- 7Control
Going beyond the prompt with ControlNet, IP-Adapter, and reference images.
- 8Consistency
The same character, style, and brand look across image after image.
- 9Refinement and Cleanup
img2img, inpainting, upscaling, and finishing in a real editor.
Producing Real Assets
- 10Logos, Icons, and Vectors
Clean, editable vector marks and coherent icon sets.
- 11Textures, Patterns, and Materials
Seamless tiling and full PBR material sets.
- 12Product Mockups and Packaging
Staging a shot you did not photograph, and the line to a print-ready file.
- 13Characters and Mascots
Design a character once and get it back, on model, pose after pose.
- 14Backgrounds, Scenes, and Environments
Wide, deep, believable spaces without the duplicate-subject trap.
- 15UI, Illustration, and Web Assets
On-brand spot illustration and icon sets across a whole product.
- 16Stock-Style Photography
Believable photographs that were never taken.
Studio to Business
- 17Workflows and Pipelines
Turning a pile of renders into a repeatable pipeline.
- 18Rights, Licensing, and Ethics
Who owns an AI image, and how to stay on the right side of a fast-moving line.
Straight answers.
Is AI-generated art copyrightable?
In the United States, purely AI-generated images generally are not, because copyright needs human authorship; your selection, arrangement, and hand-editing can be. It varies by country. The book has a full, honest chapter on it (not legal advice).
Which AI image tool should I start with?
It depends on the job. The book maps hosted tools (Midjourney, GPT Image, Firefly, Ideogram, Recraft and more) and the local stack (ComfyUI, Forge, FLUX, SDXL) to what each is genuinely best at.
Do I need an expensive GPU?
No. You can go a long way on hosted tools with no GPU, and the book covers realistic local VRAM tiers plus cloud options if you want to run models yourself.
Can I sell what I make with AI?
Often yes, but it depends on the tool's licence and where you sell. The book breaks down the commercial-safe models and the stock/marketplace policies as of 2026.
Is this for beginners or pros?
Both. It starts from the mental model and goes through to production pipelines, so a curious beginner and a working designer both find their level.
The rights and licensing chapter goes deeper — see the process breakdowns and the toolkit.