Revisionist History – Smart Talks with IBM: "L’Oréal and IBM: AI-Powered Beauty"

Date: August 28, 2025
Host: Malcolm Gladwell, Pushkin Industries

Overview

In this episode, Malcolm Gladwell explores the unexpected partnership between cosmetics giant L’Oréal and technology titan IBM. The discussion dives into the science behind lipstick innovation, the complexities of product formulation, and how AI—specifically custom models developed with IBM WatsonX—promises to revolutionize not just products, but the nature of beauty R&D itself. Through firsthand accounts inside L’Oréal’s North America Research and Innovation Center and insightful conversations with leaders from both companies, listeners gain a rare look at beauty as a data-driven, technological frontier.

Key Discussion Points & Insights

1. The Hidden Complexity of Lipstick

• Malcolm Gladwell starts by challenging the assumption that lipstick is a simple, straightforward product. Instead, it's an intricate result of years of research, evolving trends, and behavioral insights.
• [01:04] "Lipstick is a high performance product born from years of research, consumer insights, and precision science." – Malcolm Gladwell

Predicting the Future of Lip Trends

• Nadine Gomez (VP, Research and Innovation, L’Oréal) explains that anticipating trends takes years and sophisticated analysis.
  • [02:23] "We see slow signals from fashion houses and social media... we kind of see that trend evolving a little bit, and then we know, five, six years, it's going to become big." – Nadine Gomez

The Single-Step Matte Ink Breakthrough

• Problem: Most matte liquid lipsticks had been two-step products—heavy, uncomfortable, requiring a top-coat balm.
• Solution: L’Oréal's team, led by chemists like Alex Good, adapted an “elastomer” from foundation technology to make a one-step, comfortable, long-lasting lipstick.
  • [05:12] "We have this elastomer that can give you more comfort... like a cushion." – Alex Good
  • [07:19] Malcolm summarizes: "Once for the day and you're good. That's a liquid lipstick revolution."

The Rigors of Product Testing

• Testing extremes: L’Oréal simulates years of use, extreme climates, and consumer conditions.
  • [08:19] "We simulate in 45 degrees Celsius... Like if you leave your lip gloss in a car in Arizona, it's 112 degrees for three days. Is it still going to perform?" – Nadine Gomez

2. Beauty as Tech: The Data Behind the Glam

Virtual Try-On & Augmented Beauty

• Malcolm tries on lipstick—virtually—using L’Oréal’s augmented beauty platform.
  • [10:05] "You can try on L’Oréal products virtually. They call it augmented beauty." – Malcolm Gladwell

L’Oréal: A History of Scientific Innovation

• Mathieu Cassier (VP Digital and Transformation, L’Oréal) recounts the company’s history as a science- and data-driven innovator, from inventing sun filters to pioneering skin reconstruction and digital R&D.

3. The L’Oréal–IBM Collaboration

Why Work Together?

• Collaboration began in late 2023-early 2024—not as a simple vendor relationship, but as a joined R&D and digital transformation initiative.
  • [13:06] "We wanted to bring... two R&D together... Here, the concept was totally different." – Gabriel Bertolli, Chief Digital Transformation Officer, L’Oréal

The Data Challenge

• L’Oréal possesses 16,000 terabytes of product and market data, much digitized over the last 40 years.
  • [14:29] "If we have 16,000 terabytes of data... with the new technology, maybe by aligning those and using best in class technology, you can solve that problem." – Gabriel Bertolli

AI for Accelerated Formulation

• Traditional product development is limited by countless variables: ingredient selection, quantities, performance, safety, sustainability, etc. AI can simulate and propose optimized combinations, vastly accelerating innovation.

  • [16:25] "This is 10 on the power of 25... hundred billion of years for a human... You can only do this by using technology." – Gabriel Bertolli

• Mathieu Cassier clarifies that AI is a tool to augment, not replace, scientific intuition.

  • [17:03] "We don't want to replace the intuition of the scientists. We just want to make sure that this intuition is really augmented by some calculation power..."

4. Custom AI Models: Why Not Just Use ChatGPT?

Smaller Is Better

• Maryam Assuri (Senior Director, IBM WatsonX): Custom models are specifically tuned to the unique data and needs of an organization, making them more efficient, less expensive, and more environmentally sustainable than huge general-purpose models.
  • [18:44] "Enterprises started grabbing a much smaller model, customize it on their proprietary data... applicable to a real world use case... a fraction of the cost." – Maryam Assuri

Full Customization

• Companies "pick a base and customize it," tailoring AI to their domain for the best results.
  • [20:09] "One model doesn't fit all use cases... pick the right model for the target use case." – Maryam Assuri

5. The Next Frontier: What Could AI-Accelerated Beauty Enable?

Dream Products and the "Holy Grail"

• Tricia Iyegari (Global GM, Maybelline):

  • Shiny, Long-Wearing Eyeshadow: Impossible to create with current methods—real, consumer-friendly glossy shadow is the "Holy Grail."
    • [22:38] "We're unable to create a shiny, long wearing eyeshadow... It's like the Holy Grail." – Tricia Iyegari
    • [23:06] "They layer Vaseline over [eyeshadow]... within five minutes... it's all over their face or being washed off."
  • Semi-Permanent Makeup: Thin, comfortable, multi-day-wear makeup for realistic, durable beauty transformations.
    • [23:38] "Really, really comfortable, thin film makeup... that you can sleep in and that it will last a couple of days... that would be amazing."
    • [24:10] Tricia admits these have been on her wish list since at least 2010.

• Malcolm Gladwell summarizes: The promise of AI is to help close the "gap between what we want and what we can actually have," making once-impossible innovations graspable.

Notable Quotes & Memorable Moments

• On the complexity of lipstick:
  • "Lipstick isn't simple. It's incredibly complex." – Malcolm Gladwell [01:04]
• On trend prediction:
  • "Our chemists are working on five, six years down the line. We predicted that consumers wanted more of a softer look on their lips..." – Nadine Gomez [02:14]
• On product testing:
  • "We simulate in 45 degrees Celsius. And that can be something like a three year shelf life... Is it going to look rancid?" – Nadine Gomez [08:19]
• On data scale:
  • "This is 100 years of the L’Oréal data based on the last 40 years of data in the systems." – Gabriel Bertolli [14:57]
• On AI’s real value:
  • "We don't want to replace the intuition of the scientists. We just want to... augment it by some calculation power..." – Mathieu Cassier [17:03]
• On AI-enabled dreams:
  • "The goal of this model is to tame the complexity of the formulation." – Guillaume Lewoir Malin [21:05]
  • "There is one [product] that I think could be really amazing..." – Tricia Iyegari [22:34]

Timestamps for Important Segments

| Timestamp | Segment/Topic | |-----------|---------------------------------------------------------------------| | 00:07 | Gladwell introduces L’Oréal’s R&I Center—lipstick complexity | | 02:03 | Nadine Gomez on trend prediction, long development cycles | | 04:47 | Alex Good describes scientific innovation behind matte ink lipstick | | 08:19 | Nadine Gomez on rigorous product testing | | 10:05 | Virtual augmented beauty try-on demo | | 11:26 | L’Oréal’s history as a science-first company | | 12:47 | First steps of L’Oréal–IBM collaboration | | 14:29 | L’Oréal as a beauty data powerhouse (16,000 terabytes!) | | 16:25 | Scale of formulation problem (10^25 combinations) | | 18:44 | Maryam Assuri on why custom AI models matter | | 20:59 | Guillaume Lewoir Malin: what custom AI can accomplish | | 22:34 | Tricia Iyegari’s wish-list products: shiny shadow, semi-permanent | | 24:10 | Impossible dreams and AI’s potential to make them possible |

Conclusion

This episode paints a vivid picture of L’Oréal’s transformation from a cosmetics company to a “beauty tech” powerhouse, leveraging AI and data on a scale comparable to any major scientific field. From the intricacy of a single lipstick to the prospect of long-dreamed-of products, it’s clear that the intersection of beauty and artificial intelligence is opening up new realms of possibility, closing the gap between dream and reality—one algorithm at a time.