Case Study

L’Oréal Is Using AI For Product Shots of All Shades and Textures

L’Oréal partnered with Pencil and The Brandtech Group to explore how AI could enhance their creative production process across three divisions: Luxe, PPD (Professional Products Division), and CPD (Consumer Products Division), with the brands It Cosmetics, Redken, and L’Oréal Paris. The goal was twofold: to leverage AI for efficiency through automation and templating and to explore AI's potential in creative origination, determining whether AI-generated visuals could match the quality of traditional photoshoots. 

The Challenge

L’Oréal wanted to assess whether AI could replace a percentage of product photoshoots while maintaining high creative standards. Specifically, they wanted to focus on different types of product shots and the potential efficiencies gained by transitioning from traditional methods to AI-led image generation.

The Creative

For Redken, we used in-camera product images as references to generate similar visuals in Pencil. This included dynamic imagery like Redken products splashing underwater, bottles being held up against the sky as a background, and Redken bottles wrapped in pink ribbons set against pink backdrops (originally created using CGI).

Our approach started with an ideation phase, generating a variety of AI images using stand-in products. We then refined these with expert prompting, incorporated Redken products, and completed post-production enhancements. In the beauty industry, AI isn’t a one-click solution - it requires craft, expert prompting, and retouching to achieve high-quality results. Finally, we integrated the assets into a template and scaled them across all aspect ratios.

For the Luxe division, AI was used primarily for templating, including resizing and adaptation, significantly streamlining the process. While for L’Oréal Paris, we explored product shots as well as AI’s ability to capture textures and colours, from glossy lips to matte and satin shades of lipstick.  [Could potentially do with some more detail / context on these two projects?

The Results

The full AI-driven process - from prompt creation and ideation with stand-in products, to final image generation and post-production - took approximately 33 hours (four days). Traditional methods, including photoshoots, typically took the L’Oreal team 13 business days.

  • For Redken, AI saved 167 hours in production and editing time, achieving a 62% time savings compared to traditional workflows.
  • For the Luxe division, AI-driven resizing proved to be a major efficiency gain, reducing time spent on adaptation by 90%. The projected annual time saved was 2,600 hours, equating to a 40% reduction in production time.
  • For L’Oréal Paris, AI streamlined the process, saving 12.25 hours per project, equivalent to a 65% time reduction.

The Challenge

The Creative

-
-

Conclusion

Case Studies

Case Study

Diageo uses AI to Create Content for Every Occasion

One of the biggest advantages of AI in creative work is the ability to produce more specific, tailored content for different moments throughout the year.

Case Study

Google is Adapting its Workflows to Take Advantage of AI

‍Google piloted a series of AI-led content creation workflows across different regions and marketing teams.

Case Study

L’Oréal Is Using AI For Product Shots of All Shades and Textures

‍L’Oréal wanted to assess whether AI could replace a percentage of product photoshoots while maintaining high creative standards.

Case Study

Unilever Is Using AI to Rethink Asset Creation

‍To fully capitalise on the efficiencies AI offers, Unilever recognised that rethinking their marketing workflow was just as important as adopting the technology itself.