How to Achieve Quality AI Rendering: The Essential Checklist
The good news is that producing quality AI visuals doesn't require reinventing creation. If you're used to managing photoshoots, you've already done most of the work.
What changes is not the creative process, it's the way we execute it.
1. A Clear Brief — Without Ambiguity
Like any photoshoot, everything starts with a precise brief.
Campaign objectives, message, tone, constraints, formats, final uses.
With AI, the absence of a brief is unforgiving.
Without a framework, the model "explores" and produces inconsistent, difficult-to-use results. Without a clear brief, AI works randomly.
2. Strong Artistic Direction (and Owned)
This is the non-negotiable point.
Artistic direction doesn't disappear with AI — it becomes even more central and cannot be diluted.
A quality AI photoshoot requires a clearly identified Art Director, whether internal or external to the brand.
Their role is to be the guardian of creative intent, visual consistency, and respect for the brand's DNA, from brief to final delivery.
AI doesn't create a vision. It executes it.
Without an AD to arbitrate, eliminate, adjust, and reject what doesn't work, visuals go in all directions.
With an AD engaged in the process, AI becomes an accelerator, not a substitute.
The Art Director is also responsible for critical review in post-production: they spot inconsistencies, artifacts, style deviations, and ensure that each visual is aligned with the brand's standards.
3. Anticipate Resolution and Final Uses
A point often underestimated in AI: resolution.
Models generate images in limited native resolutions (1K, 2K).
However, requirements are not the same depending on the medium:
- social media,
- e-commerce website,
- POS materials,
- OOH (Out Of Home) or point-of-sale display.
Anticipating final uses from the brief allows:
- avoiding unpleasant surprises,
- choosing the right tools,
- planning necessary post-production steps.
4. Identify Technical Limitations Upfront
Like a traditional photoshoot, an AI photoshoot requires anticipating its constraints upfront.
Each product vertical presents specific challenges that AI models don't all handle the same way.
In jewelry, for example, the main challenge lies in:
- faithful reproduction of stone colors,
- managing reflections,
- precision of materials and settings.
An approximate rendering, a slightly distorted stone, or an inconsistent reflection is enough to discredit the entire visual.
This is typically a case where the approach defined upfront is decisive.
Our collaboration with the premium jewelry brand ZEINA provides a concrete illustration, detailed in the case study accessible here.
The methodological choices made from the start ensured the fidelity of stones, consistency of reflections, and precision of materials throughout the creative pipeline.
In beauty, the issues are different:
- AI models still struggle with text on packaging,
- certain skin textures or cosmetic materials can appear artificial,
- poorly controlled post-production can ruin lighting that was originally correct.
These limitations don't make projects impossible.
But they require choices: adapting the brief, adjusting creative direction, planning corrective steps.
Anticipating these constraints allows:
- avoiding unnecessary iterations,
- ruling out unrealistic approaches,
- securing final quality from the start.
5. Choose the Right Partner
In a still very noisy ecosystem, choosing the right partner is decisive.
A credible AI partner, an AI agency must:
- master the models and their uses,
- understand the vertical and the product,
- know how to say what is feasible and what is not,
- integrate real creative direction,
- ensure rigorous quality control.
The most successful AI projects are conceived as real campaigns — not as a series of isolated tests.
6. Apply a Proven Methodology
An effective AI photoshoot follows a familiar logic:
- preparation and framing,
- production,
- post-production,
- quality control.
The big difference lies in iteration.
With AI, changing direction is fast, inexpensive, immediate.
This iteration capability is one of AI's main assets — provided it's guided by clear intent.
Conclusion
Producing quality AI visuals doesn't come down to a good tool or an isolated prompt. It relies on a structured approach, inherited from traditional photoshoot standards, and adapted to AI's specificities.
This checklist synthesizes the essential principles to respect for integrating AI into visual creation without compromising brand standards.
This checklist summarizes the fundamentals:
1. A clear and unambiguous brief
2. Strong and embodied artistic direction
3. Anticipate resolution and final uses
4. Identify technical limitations upfront
5. Choose the right partner
6. Apply a structured methodology