Wilson
a proposal for the wilson ai creative technologist role

Scale creative
assets without
lowering brand standards.

An AI-assisted production layer that adapts approved Wilson campaigns across retail, ecommerce, social and marketplace surfaces while preserving brand consistency, creative review and existing QA standards.

AI-assisted variation generation can support testing, optimization and retail adaptation workflows.

All visuals below are AI-generated campaign extensions inspired by the Marta Kostyuk Wilson campaign aesthetic. Illustrative only.

Focus

scalable production

Method

ai assisted

Priority

brand consistency

Posture

supports existing teams

Wilson tennis campaign reference
Wilsonref
illustrative
Where AI helps

adaptation, variation, formatting

Where humans lead

concept, brand, sign off

What stays in place

DAM, PIM, approval chains

00operational context

Why this matters operationally.

Modern creative teams are expected to deliver significantly more campaign surfaces, retailer variations, localized assets and format adaptations than traditional production cycles were originally designed to support.

AI can assist by reducing repetitive production work while allowing creative teams to maintain control over brand standards and approvals.

pipelineproduction flow
stage 01

Approved campaign master

Creative approved by brand and legal.

stage 02

AI adaptation layer

Generate scalable format variations.

stage 03

Format + market variants

Retail, channel and locale outputs.

stage 04

QA + brand review

Human review remains in place.

stage 05

Retail / channel deployment

Files prepared for DAM and partners.

AI sits between approved creative and channel deployment. It scales formats, not decisions.

01the premise

Wilson already runs a strong creative engine. The question is where AI fits.

category

Campaign adaptation

Adapting approved campaign work across surfaces and seasons.

category

Ecommerce production

PDP imagery, product crops and template aligned outputs.

category

Retail formatting

In store, retailer and marketplace ready specifications.

category

Localization support

Market variants prepared for review by local teams.

category

Metadata preparation

Captions, tags and naming drafted for the existing DAM.

category

QA assistance

Pre review checks for brand, channel and retailer specs.

category

Asset organization

Versioning, structure and DAM ready handoff.

category

Concept exploration

Visual iteration during early creative thinking.

02ai inside the workflow, not replacing the team

A practical map of where AI could sit alongside the people doing the work.

ai assist

Campaign extension from approved hero imagery

ai assist

Retail crop adaptation across formats

ai assist

Mobile-safe framing adjustments

ai assist

Alternate composition generation

ai assist

Ecommerce-ready product isolation

ai assist

Localization preparation for regional markets

ai assist

Retail export preparation

ai assist

Metadata and naming prep for DAM upload

ai assist

Rapid variation prep for creative review

ai assist

Concept expansion without reshooting

AI assists repetitive production work. Teams still approve final creative.

03scaling approved creative

Scaling approved creative without rebuilding every asset manually.

approved mastersigned off
Approved Wilson campaign master frame
campaign master · approved
starting point

One frame. Signed off by brand and creative.

talent

release on file

brand

color and type approved

Every brand and legal decision inside the master is inherited by the variants that follow. The work below it is mostly repetition, which is where an AI assist becomes useful.

Retail crop
Social tile
Ecommerce crop
Mobile story
Email module
Vertical retail
Retail tile
Collection banner
Marketplace crop

Every output above derives from the same approved master. The work is in the adaptation, not the recreation.

04end to end

From approved campaign to scalable retail deployment.

step 01

Approved master

Signed off campaign frame from the existing creative team.

step 02

AI-assisted adaptation

Format, crop and surface variants generated from the master.

step 03

Human review

Brand, legal and retail specification checks led by the team.

step 04

Deployment ready outputs

Files prepared for DAM, retail partners and ecommerce surfaces.

05quality control remains human led

AI assists repetitive production tasks. People still own the standard.

approved assetscampaign reference
human reviewled by the team
  • Brand consistency review
  • Retail specification validation
  • Crop and safe zone review
  • Localization review
  • Product visibility validation
  • Export dimension check
  • Marketplace formatting review
  • DAM organization alignment
  • Accessibility and readability review
final approvals remain human-led
05how this fits

An AI layer that sits inside the team. Not a replacement for it.

what stays the same
  • The DAM as the source of truth for approved assets.
  • PIM and product data ownership.
  • Brand and legal sign off authority.
  • Creative direction and campaign concepting.
  • Athlete and talent relationships.
  • Retailer and partner agreements.
what an ai layer would add
  • Variation and format adaptation from approved masters.
  • Pre QA against brand, channel and retailer specifications.
  • Localization preparation for market and legal review.
  • Lighter manual export and metadata work.
  • Faster concept iteration during early creative thinking.
  • More room for the team to focus on judgment over repetition.
06implementation perspective

A realistic way to introduce this, in stages.

stage 01

Listen and map

Sit with the creative team. Map the actual workflow, not the documented one. Identify where time is being spent on repeat tasks.

stage 02

Pilot one workflow

Pick one bounded use case, for example resizing across channels for a single campaign. Measure the assist against the existing baseline with the team.

stage 03

Build brand guardrails

Codify the brand standards into prompt scaffolds and pre QA checks so the assist behaves consistently across users.

stage 04

Expand carefully

Add adjacent workflows once the first one is trusted. Variation, metadata, localization prep, export. One at a time.

stage 05

Integrate with existing systems

Connect cleanly to the existing DAM, PIM and approval tools. The assist should feel like an extension of those, not a parallel system.

stage 06

Measure what matters

Track time recovered, consistency of QA outcomes, and team feedback. Adjust based on what the team actually experiences.

08closing

Where I see the opportunity.

The opportunity is not replacing creative direction. It is reducing repetitive production overhead so approved campaigns can scale faster across channels, formats and markets while maintaining brand standards.

  • Scalable adaptation of approved campaign systems.
  • Faster retail and channel deployment cycles.
  • Operational support for the existing creative team.
  • Quality control and brand consistency preserved.
  • Human approval systems remain the source of truth.
Wilson campaign reference
Wilsonreference concept
illustrative · ai campaign extension

Inspired by the existing Wilson / Marta Kostyuk campaign aesthetic.