AI in Action: How L'Oréal Puts AI to Work in Everyday Ad Production
Global marketing has shifted from big hero campaigns to constant delivery. Volume, speed, and consistency now decide who stays visible. That pressure is why L'Oréal uses AI inside day-to-day production-especially for video and visual work-to keep content moving without bloated cycles.
The goal isn't to replace creative teams. It's to cut friction between idea and asset so marketers can refresh content across platforms without starting over every time. In creative functions, speed and control matter as much as originality, and AI helps on both fronts.
Scaling content without scaling production
Digital channels need an endless stream of assets: social cuts, ecommerce visuals, regional variants, and platform-specific edits. Traditional models strain under planning, shooting, editing, and approvals for each new request.
AI lets teams reuse footage and extend it into new formats fast. Think polishing clips, resizing, reframing, swapping backgrounds, generating versions for TikTok vs. YouTube, and automating subtitles. Humans still guide direction and approve the final cut, but the path from brief to delivery gets shorter.
The real win isn't novelty. It's producing enough on-brand, usable content to match the pace of distribution.
Tight creative control protects the brand
At scale, small inconsistencies become big problems. Visual identity, tone, language, and claims must be precise, and enterprise brands can't afford drift.
L'Oréal treats AI as a support layer. Outputs go through the same review gates as any other asset, keeping accountability with internal teams and agencies while speeding execution. In practice, AI assists production-people own the brand voice.
If you're tightening governance, frameworks like the WFA's brand safety guidance can help set clear rules for approvals and risk checks. See the WFA Brand Safety Guide.
Cost, speed, and repeatability
Budgets are under pressure, platforms change their rules, and audiences expect frequent updates. AI reduces the marginal cost of each additional asset by stretching the value of every shoot.
Quick-turn edits, localized versions, and last-minute tweaks stop requiring full production support. Savings aren't a single big cut; they compound across hundreds of small decisions. Over time, that changes how teams plan, scope, and allocate spend.
What this signals about enterprise AI maturity
This is less hype, more operational fit. AI is slotted into predictable tasks where quality can be measured and errors can be caught before launch.
Most of the value sits between concept and distribution: adaptation, enhancement, and formatting. AI works best where there's data, rules, and existing review processes. Creative direction stays with people; scale comes from tools.
What marketers can do now
- Map the workflow: find bottlenecks in versioning, resizing, color/tone fixes, subtitles, and compliance text.
- Pick 1-2 repeatable use cases (e.g., short-form video variants, ecommerce image refresh) and define clear acceptance criteria.
- Set guardrails: brand kits, approved prompts, rights checks, and human approval gates before publishing.
- Build a reuse library: footage, product shots, motion templates, and UGC with documented usage rights.
- Instrument metrics: cycle time, cost per asset, error rate, and percent of assets produced via reuse.
- Localize with intent: templated variants with on-brand copy; add cultural and claims review steps.
- QA every output: logo placement, disclaimers, captions for accessibility, platform policy compliance.
- Vet vendors: data handling, content rights, model provenance, and indemnities.
- Upskill the team with focused training on creative AI workflows. Consider the AI Certification for Marketing Specialists.
Metrics that matter
- Time to first draft and time to final approval
- Cost per asset and percent of assets reused or adapted
- Revision cycles per asset and compliance pass rate
- Channel performance lift from fresher, more frequent creative
The quiet impact
At L'Oréal, AI isn't the headline-it's part of the process. It reduces friction, keeps consistency intact, and makes content volume manageable without overhauling creative roles.
That's the signal for enterprise marketing: use AI where it speeds delivery and lowers risk. Let people lead the story; let AI make more of it, faster, one asset at a time.
Your membership also unlocks:
