Lumen Technologies
genAI content supply chain (producing on-brand assets at scale)
Lumen Technologies cut its B2B campaign launch time from 25 to 9 days (about 3x faster) by generating on-brand copy and visuals in Adobe GenStudio for Performance Marketing with Firefly and Custom Models.
Key points
- genAI production of B2B campaigns: per-persona copy and on-brand visuals.
- Adobe GenStudio, Firefly and Custom Models on Lumen's IP, approval via Workfront.
- Campaign launch time cut from 25 to 9 days, about 3x faster.
- Evidence B, confirmed status: Adobe announcement and customer story from June 2025.
Objective
Reduce the time between a B2B campaign concept and its go-live, while keeping assets on-brand and legally approved.
The deployment
Lumen Technologies, a US B2B telecom operator, produces its campaigns (paid social, display, banners, emails) in Adobe GenStudio for Performance Marketing. The application generates copy tailored to each persona and, via Firefly and Custom Models trained on Lumen's IP, the campaign visuals. The assets are ingested into Adobe Workfront for legal and brand approval before distribution. The same space is used to generate, test and adapt the creatives.
Results Proof B
Official Adobe announcement picked up on BusinessWire and documented in an Adobe customer story, with figures consistent across the three. All sources come from Adobe or its press wire (interested parties), hence B and not C.
How it works
Documented architectureThe stack in detail
- plateforme Adobe GenStudio for Performance Marketing single space to generate, test and adapt campaign assets (per-persona copy + visuals)
- llm Adobe Firefly image generation model trained on commercially licensed content, used for the campaign visuals
- llm Firefly Custom Models Firefly models fine-tuned on Lumen's IP and brand guidelines to keep generation on-brand
- outil Adobe Workfront brand and legal approval workflow for the generated assets before distribution
- outil Adobe Express fast versioning and adaptation of the creatives by the marketing teams
How it runs, concretely
For ops teams-
1Framing the brief and personas Marketing team
Marketing defines the campaign, the audiences and the message per persona.
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2Asset generation AI (GenStudio / Firefly)
GenStudio produces the per-persona copy; Firefly and the Custom Models generate the visuals within brand rules.
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3Brand and legal review Creative / legal team
The assets are ingested into Workfront for approval before distribution.
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4Distribution and adaptation Marketing team
The creatives go out in paid social, display, email; the team tests and adapts in the same space.
The campaign brief and target personas feed the generation. The brand guidelines encoded in the Custom Models ensure the generated content stays on-brand; without them, production loses its brand consistency.
How your customers perceive this type of use
Sourced studiesUn ecart net separe les annonceurs des consommateurs : 77% des annonceurs voient l'IA positivement contre 38% des consommateurs (Yahoo/Publicis, 2024). Les mesures implicites confirment le rejet declare : en EEG, les pubs generees par IA produisent une activation memorielle plus faible que les pubs traditionnelles et sont decrites comme agacantes, ennuyeuses et confuses (NIQ, 2024). La disclosure a un effet ambivalent : elle augmente fortement la confiance quand elle est remarquee (Yahoo/Publicis), mais 27% des jeunes consommateurs disent faire moins confiance a une entreprise dont la pub est creee par IA (IAB, 2024).
Acceptance conditions
- Une disclosure visible : quand la mention IA est remarquee, la confiance globale envers l'entreprise augmente de 96% (Yahoo/Publicis 2024)
- Une qualite visuelle suffisante : les visuels IA de basse qualite augmentent l'effort cognitif et distraient du message (NIQ 2024)
Red lines
- Le contenu IA non declare puis identifie : 72% des consommateurs disent que l'IA rend l'authenticite difficile a etablir (Yahoo/Publicis 2024) et les marques utilisant des pubs IA sont plus souvent jugees inauthentiques ou non ethiques par les consommateurs que par les dirigeants (IAB 2024)
- Les mannequins et personnes generes par IA : 46% des consommateurs n'en veulent pas dans la publicite, l'inquietude premiere etant les standards de beaute irrealistes (Attest 2025)
Sources: Yahoo / Publicis Media (terrain Ebco) 2024 · IAB (avec Attest) 2024 · NIQ (NielsenIQ) 2024 · Attest 2025
How to replicate
Inference, not sourcedData prerequisites
- brand guidelines and IP assets usable to train Custom Models
- personas and target messages
- reference creative library
Org prerequisites
- brand and legal approval workflow
- creative team able to frame the models
- governance over generated content
Possible stack
- Adobe GenStudio + Firefly + Workfront
- any genAI content supply chain with fine-tuning on brand IP and an approval step
The plan, step by step
- Step 1Map the current concept-to-go-live cycle and locate the brand/legal bottlenecksDeliverable: Cycle map with time per step (the 25-day baseline)
- Step 2Gather brand guidelines, personas and IP assets usable for trainingDeliverable: Structured brand kit, validated by creative
- Step 3Train the Custom Models and configure generation in GenStudioDeliverable: On-brand copy + visual generation validated on a test batch
- Step 4Wire in the brand and legal approval workflow (Workfront or equivalent)Deliverable: End-to-end generation, review then distribution flow operational
- Step 5Launch a pilot campaign and measure cycle time against the baselineDeliverable: Before/after comparison of launch time + expansion plan
First step: Map the current concept-to-go-live cycle and identify where brand/legal approval blocks, before plugging on-brand generation into it.
Sources
- S1 Lumen Technologies Scales B2B Personalization with Generative AI Innovations in Adobe GenStudio Interested party archive pending
- S2 Lumen Technologies Scales B2B Personalization with Generative AI Innovations in Adobe GenStudio (BusinessWire) Interested party archive pending
- S3 Lumen fuels growth marketing with Adobe GenStudio Interested party archive pending
An error, newer info, a source?
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