- 4 hours ago
AI is collapsing the distance between insight, creation, testing, and execution. Product development cycles are accelerating, consumer feedback is becoming continuous, and companies can now iterate on experiences, services, and campaigns in near real time. For large organizations, the opportunity is enormous—but so is the operational challenge. How do you scale experimentation without overwhelming the business? Where does human judgment still matter most? And as AI reshapes the mechanics of innovation itself, how do companies avoid moving faster than they can actually absorb change?
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TechTranscript
00:00Three very different industries, one shared challenge.
00:05So do prepare to welcome Nigel Vaz, who leads Publicist Sapient,
00:13Drew Pagnotu, who is Chief Marketing and Innovation Officer of Keurig, Dr. Pepper,
00:19and Delphine Viguier, who is Chief Innovation Officer at L'Oréal.
00:25Moderating this invigorating session, we have Ana Rold, Diplomatic Courier.
00:32Please welcome them on stage.
00:56Welcome.
00:57Good afternoon.
00:58Good afternoon to you all.
00:59Thank you for being with us.
01:00So our subject matter today is from idea to market at AI speed.
01:06I don't know who said this, so I'm going to just percolate the saying,
01:12but there's a saying that's been going around that now we see change happen not in months,
01:17but you see decades happening in months.
01:20And I would be remiss if I didn't say that out loud, AI is now already compressing what
01:27used to take months into days when it comes to our industries here.
01:31But here's what I also keep hearing from leaders.
01:34The tech is not the hard part.
01:36I keep hearing this all the time.
01:38The tech is the easy part.
01:39But it's really the hard part is the management and the orchestration.
01:44So how fast can we absorb this change that AI makes now possible?
01:50And this is a change we're going to talk about.
01:52So before I continue waxing lyrical even more about this, I have three experts who are doing
01:57this in real time and they're hot seats.
02:00So I'm just going to go directly to you and I'm just going to put you all in the hot
02:03seat
02:04one by one.
02:05Thank you for being with me.
02:06Okay.
02:06And then, so I'm going to start with jokes about who's first, who's last.
02:10Drew, you think you're last, but you're first.
02:12Oh, all right.
02:13Okay.
02:13I'm going to go with you first.
02:15What has AI actually changed about how you get from idea to market?
02:22And what hasn't really changed that much?
02:26What hasn't changed is meeting the consumer where they're at.
02:30The pace of that has gotten incredibly faster.
02:33And I would say in our industry, hey, AI, you heard it from a lot of speakers, it's about
02:39data.
02:40In our industry and beverages, and it's one of the reasons I love being in this industry,
02:46is beverage data is created all the time because people consume a lot of beverages, which is
02:53great because we want everyone to be hydrated.
02:55She's about love.
02:56We're about hydration.
02:57The world should be about love and hydration.
02:59But social media has become an incredible place where people are interacting with beverages,
03:07creating, innovating beverages.
03:10One of our brands, Dr. Pepper, is the number one brand on TikTok.
03:13We're the number one most food and beverage-engaged searched product on TikTok.
03:20And if you are on TikTok, any minute of the day, you will see consumers creating things like
03:26dirty soda.
03:27They are actually taking our product and innovating around it.
03:32They're creating protein soda by taking milk and putting it in with one of our products,
03:38coconut, Dr. Pepper, which we should all try.
03:41And so when the world's innovating at that pace and all this data is being generated, and
03:48I call it non-transactional data, our ability to harness non-transactional data radically changes
03:56how fast you can innovate, how you can meet consumer needs, and how consumer-obsessed you
04:02can be as a company.
04:03And so in our space, that's how you win.
04:07And again, it's happening every minute.
04:10It is amazing, whether it's Instagram or TikTok, people love talking about their beverages, whether
04:17they're alcohol, non-alcohol, whether they're healthy beverages, not-so-healthy beverages.
04:21And when you get that level of engagement, it fundamentally changes the AI flywheel.
04:27And you said that, and it's so interesting to me, obviously, because we tie our consumer
04:32choices to authenticity, to our personalities.
04:38And then you mentioned data, which is so interesting in another way for me, because all I hear about
04:43is we don't have enough data or we need more data.
04:45And you're saying we have plenty of good data.
04:48And so I wanted to go, Delphine, to you next, because this is part of everything you do.
04:53I will answer a bit differently to the question, because to me, it's not a question of speed.
04:59It's a question of depth.
05:01The real difference with AI is that you are building your product, your advertising, whatever
05:08you want, on much more data than you used to do before.
05:12In L'Oréal, we have been aggregating all the scientific data we have from the clinical
05:18tests to even the discussion by mail between two scientists.
05:23To really recreate a data pool managed by AI to make sure that when we ask a question,
05:30we have the maximum depth of data to answer a question or to do a product.
05:36What is the best SunCare product?
05:38And then you have the extraction of all the data you can have on the best filter, the one
05:43that resists to water, the one that is OKUS, the one that the Japanese like, and the one
05:49that those consumers think it's a better.
05:51And now you aggregate that and you can create your product.
05:56We are not so much obsessed by faster.
05:59But for sure, you can create it better.
06:02And to me, that's a big difference compared to what we were doing before.
06:06Absolutely.
06:08And still, the intuition is important, but you have much more data and points and signals
06:15to build your intuition.
06:17So scientifically speaking, it's very solid.
06:19It's very solid.
06:20And I do think it depends on category.
06:23Like in our space, a lot of our brands are driven by Gen Z and Gen Alpha.
06:30We get continued feedback and surveys that say, Gen Z, in our category in beverages, they
06:36want to try new beverages, 69% of them every month.
06:39You think that they have only old people?
06:41No, no, no, no, no.
06:42I'm just saying the appetite of that generation in our space is they constantly want to try
06:48new things to drink.
06:49And so if we're not keeping up with that velocity, which is every month, three quarters
06:55of your prime cohort, want to try something new, then you're going to fail.
07:02You're going to miss things.
07:04Other people will find a way to satisfy those desires.
07:08That's why in our space, I think the more that we democratize innovation, it's different.
07:14You know, I used to work at Pfizer.
07:15You're not going to democratize innovation, right, in a drug company.
07:18But in a food and beverage company, democratizing innovation is not a bad concept.
07:24And that's where the power of data and AI, I think, take you to different places.
07:29You know, what I'm hearing from both of you is that feedback loop with the consumer is
07:33now much faster.
07:34And you have to match that agility that you probably couldn't do that before without the
07:40data set and the analysis you get from AI.
07:43So you two are in the hot seat in that you're doing this every day.
07:47This is your daily job.
07:48So I was going to go to Nigel and ask you, OK, let's backtrack a little bit, go a little
07:52bit further back and see this from the orchestration organization perspective.
07:58And I was looking at this data point that says only 10% of companies say that AI is truly
08:06core to how they operate.
08:08And about 70, despite 73% of them using it on the regular.
08:13Why that gap?
08:14I think the gap, you know, comes very much from if you listen to the conversation we've
08:19been having, there is a consumerization of data, there's a consumerization of product
08:24development, of connecting different data sets in order to create more value, right?
08:29That continuum is accelerated by AI.
08:32But I think one of the things we have to ask ourselves is if you took away AI from many
08:38organizations today, what percentage of their P&L, what percentage of their cost or growth
08:44line would it affect, right?
08:46Just as a hypothetical, if you did that across companies, I think what you'd find is that
08:50there's a lot of people experimenting with AI, but how do you actually get it to scale
08:54to where it's meaningfully creating value in the P&L, either through growth, where, you
08:59know, if we said, OK, if you took AI away from us, sales are going to be down 20%, or
09:04if
09:04you took AI away from us, costs are going to be up 20% or 30%, whatever those numbers
09:08are.
09:09And I think so what you have is, I think, do things from an organizational perspective.
09:13It's an easy comment to throw out saying it's not about the technology.
09:17And I would frame that as it's not just about the technology.
09:21It is about thinking about the incentive structures.
09:24It's thinking about the organizational leverage that you get from AI, because AI is only as good
09:30as allowing you to reimagine how you do things today.
09:33So if your silos are still, this person makes the product, that person markets the product,
09:39this other person does the service around the product, and those silos stay, and the
09:44data that we're talking about is fragmented, like Delphine was saying, and it's not connected
09:48across those, you're still going to get the same answers, maybe slightly better, maybe
09:54slightly faster, but similar answers.
09:56I think when you take a step back and you actually start to say, what if we were to reimagine
10:01how we do things today differently?
10:04So to Drew's point about product development connecting to marketing, and product development
10:08and marketing connecting to innovation pipeline of new products, or boring stuff, like how
10:15do we take out 20 or 30% of our technology costs using AI, right?
10:20That's when you start to see the value gap get closed between folks who are experimenting
10:26with AI, and folks that are truly getting leverage with AI.
10:30And I think the areas of real leverage started in cost, and started primarily in technology,
10:37because software development could be so much faster.
10:39At Sapient, we built enterprise AI products to essentially drive managed services, so you're
10:46not managing IT systems with people, you're managing it using AI, or our Slingshot platform,
10:52Sapient Slingshot, is building software five times faster than our best engineers could.
10:57And those things are taking meaningful costs out of, say, your technology spend, to be able
11:03to reinvest it in other areas to do things differently.
11:06And I think the hamstring of, we've got really tight operating budgets, we are not able to
11:12free up enough costs to invest in the places we want, so the easier solution is, I'm going
11:17to experiment in 20 places, show lots of proofs of concepts that look interesting to people,
11:24but not really see meaningful leverage to the bottom line or the top line.
11:30So this is a fascinating part of you, when you kind of sit back and think, because one
11:38of the main questions of this session is, where does a human fit in this loop?
11:41And that would have been sort of my next round of questioning, you kind of started answering
11:45that for us.
11:46It's, for both of you, is this the kind of game that you can do?
11:51Yes, I think we ask ourselves the question in L'Oréal very much in advance, because we
11:58create in 2021 what we call an ethical committee for AI, and we have six, seven principles.
12:06And the two major to me are, number one, there is always a human decision for the big decision
12:13we have to take, is the product good, the formula, the advertising that we put on air,
12:19on social, et cetera, you have a human decision, point number one.
12:22And point number two, we never represent the beauty through an AI visual, through a generated
12:28AI visual.
12:29We can have fun visual in Viva Tech, in the L'Oréal booth, but every time we have a consumer
12:35facing product, advertising, visual, it's a real woman shot by a real photographer with
12:42a real product we've been developing.
12:44And we really stick to that.
12:46And it's not easy, because we are in many countries, and many people are doing content
12:50everywhere, but I can tell you that the people in the room here doing content, it's real woman.
12:56Real woman from all age, all skin color, and we are obsessed by this visualization of the
13:01beauty.
13:02But then, of course, AI is creating so much value.
13:05We augment so much the people with AI that it's first useful and irresistible.
13:09Our researchers are fantastically augmented.
13:13We were discussing last week with my president and saying that for the number of molecules
13:19we discovered this year, and that will be in the plan for the year to come, we will have
13:24worked 20 years.
13:25Right.
13:26And we've done it in six months.
13:28The choice, I mean, of the molecule, because we have been testing with AI model much faster.
13:37So that's true, it's fast, but it's also deep.
13:39That's why I want to...
13:40Right.
13:42And it's that acceleration.
13:43I really want to...
13:45It's not only fast, it's incredibly complete and global.
13:52Voilà.
13:53And it's exactly that.
13:54It's being able to do things much faster than, again, what I was saying in the beginning.
13:59Yeah, maybe you can say we can do faster.
14:00I say we can do at all.
14:01But it's a bit the same.
14:02No, no, no.
14:03The two of you.
14:05Everyone should just move at the speed of their consumer, right?
14:08Again, I say when you're in the beverage world, you've got to move at the speed of
14:13chenzennials, but it's not just about speed.
14:15Go back to your question around what is the human factor to all of this?
14:21And we always say this, technology raises the ability for marketers or scientists to play
14:29at the highest level of their card.
14:31Of course.
14:32Fundamentally, what we're seeing, and we're working through this, we don't have a perfect
14:36solution, but we'll take marketing.
14:40Marketing is in service of connecting to the customer, right?
14:44With things moving faster, that's one element.
14:49But two, and even more important, is we now are building relationships with consumers unlike
14:55ever before.
14:56If you're a CPG company, most CPG organizations still organize this way.
15:02They're like, well, they don't think about relationships and two-way conversations.
15:07It's about, hey, I'm going to do one campaign after another campaign and after another campaign.
15:11And I get this question a lot, particularly with a brand like Dr. Pepper.
15:17It's like, how did you become the number two soft drink in the U.S. versus Coke and Pepsi
15:24and they outspend you eight to one?
15:26And part of it for us is building relationships, we call them with raving fans, which technology,
15:33data, and everything that we've talked about enables us to do in ways that we couldn't
15:38before.
15:38And I would say this, because I've been in multiple different industries.
15:44Every business generally is healthy based on the top 20% of their customers.
15:50That is usually true.
15:53McKinsey has verified it.
15:54And so if the top 20% are literally the economic flywheel for a brand, you should be in the
16:00relationship business.
16:01And so in our side, I would say in the beverage side, that's not been the case.
16:06It's been like one big sponsorship, one big, you know, broad campaign, probably different
16:12in beauty because they've had a different orientation.
16:15It's very interesting to have the point of view.
16:16I think we are number one because we are doing good products.
16:19Yeah, but that's my point of view.
16:22And we do good products also now, thanks to AI.
16:25And then, of course, we build the relationship with the consumer.
16:28And it's interesting to see how much AI can be used in various fields.
16:33And that's true.
16:36We start by putting AI where we were the best.
16:40It was science and formula and efficacy.
16:42So I think everyone is using it to do better what they do good already.
16:48That would have been my question to you directly earlier.
16:52You know, what has changed now that you have this direct relationship with the consumer?
16:56You're getting the feedback loop much faster, but you do not need any intermediaries.
17:01And that's the same for L'Oreal to have a direct conversation, especially with younger
17:06generations, which I'm assuming everybody wants to reach.
17:09No, no, we have all a direct conversation now.
17:11Oh, yeah.
17:11Everyone has a direct conversation with the consumer.
17:14I'm thinking, you know, which of these groups, you know, care so much about authenticity and
17:20the relationship building and all that?
17:22You have to show up.
17:24It changes your marketing model because I say this, like innovation is all about sparking
17:30that relationship and bringing people into a flywheel with us as kind of the brand owner
17:37and the consumer and us showing up as a fan.
17:40When you're in a relationship, you're a fan of each other.
17:43And so we celebrate our consumers, our creators.
17:48There was a big creator called Romeo that broke the Internet in January that brought a wonderful
17:55jingle on behalf of Dr. Pepper.
17:57Remember, we've been like in this kind of fan led model and it makes marketers or makes
18:05us start behaving in ways that sometimes just about agility, because if you're going to grow
18:11a relationship, great relationships aren't always predictable.
18:15You got to let the other person take you to a wonderful place that you may not have seen.
18:19And then your marketing team has to be agile.
18:22And that is the trait that we are constantly looking for in our teams.
18:27If you don't have that agility, then none of this, you can't leverage any of this stuff.
18:34And so the human element is finding employees that can have that agility.
18:39We're going to be louder than this.
18:40The AI is not managing the sound.
18:43Yeah.
18:45What I've heard you both, everything I've heard so far is AI is a great tool to do everything
18:50we're already doing.
18:51We know how to do well, just helps us accelerate, make it faster and all that.
18:56And so I was thinking, Nigel, for you, I was thinking about this analogy as you guys were
19:01talking about the Iron Man, right?
19:04I'm a little bit of a nerd.
19:05So Iron Man is the man.
19:08The suit alone is just the tech.
19:11The person alone has limits.
19:13The value is Iron Man together.
19:16So the question that I had for you, I was so proud of this analogy.
19:21What does it actually take to get that design right?
19:26To be sort of not just the suit, not just the human, but the Iron Man?
19:30I mean, when I talk about that analogy of like suit and person, to me, it's a little bit
19:34like enabling what Drew and Delphine are talking about, right?
19:38Because if you think about a beverage company would just have been a one-way transactional
19:43relationship with the customer.
19:44We make a product, it's great, you buy it.
19:46But actually what we're starting to see is the engagement with the data, the information
19:51from the data being used to harness new products.
19:55Or in the case of L'Oreal, who's been innovating with technology, even in the work that we've
19:59done over the years, for years to create an intersection between great products and
20:05the way you consume those great products together to add more value to consumers' lives.
20:09I think about, you know, Makeup Genius all those years back.
20:12You know, like really powerful examples.
20:14Or in the case of Keurig, the devices themselves and the intelligence that comes out of them.
20:20In that world, right?
20:23This is where I think the Iron Man analogy is really true, is you can't have a superhero
20:28in that example without the technology being very different than what it used to be.
20:33But you also have to make investments in people because your people can't keep doing, to the point we've been
20:38making, exactly what they used to do.
20:40And if you combine a new way for your people to work and you combine it with cutting-edge technology,
20:46the outcome trajectory with AI is dramatically different in the context of creating more value.
20:53To your point about molecules that would have taken 20 years to be decisioned and deployed in the context of
20:58products happening in a matter of months.
21:00It's a function of you doing things differently and the technology or, you know, your examples of the same kind.
21:08I love the idea of the augmented people.
21:10The people are augmented with AI.
21:13You are augmented in, that's true, that even beauty genius, which is a way to choose your beauty routine.
21:18You talk with an AI of L'Oreal Paris and she tell you, bah, you have some wrinkle or no
21:24wrinkle, a bit of acne.
21:25You download your apps, et cetera, and it gives the power to the consumer to choose whatever she wants.
21:31We are not giving any aesthetic advice or comment, of course, but you empower the consumer to choose what she
21:38wants.
21:38And I love the fact that use AI when you empower someone or when you create really a value.
21:44I love to make the link between AI and the new man guy, whether it's a consumer or the people
21:48that are working on the bench and doing the formula, et cetera.
21:51Yeah, and I would say, like, in our world, you know, the ability to leverage digital twins in marketing, but
21:59also now in R&D.
22:00In the food and beverage world, we still do this.
22:03Like, you have sensory panels.
22:05People come in and they taste something and they're like, I like it or I don't like it.
22:09The ability to digital twin that sensory panel so that your scientists can go back and, you know, do iterations
22:17faster, that's game changing.
22:19The fact that there's still a lot of this stuff, particularly in food and beverage, which, you know, I'd say
22:24is using old math.
22:26If we could use new math, which is power of AI, that spider chart around different sensory vectors of how
22:33something tastes on your tongue totally opens up possibilities and allows you to innovate differently.
22:38And to me, that would make a food scientist's position be really exciting, right?
22:44And so I think it's unlocking those.
22:46Yeah, and, you know, just to build on that, right, I think if you think about AI, almost the conversation
22:51about AI is a layered cake, right?
22:53This is kind of where I think these conversations sometimes happen in isolation.
22:57So there's a lot of conversation around AI at the bottom of the stack, you know, energy, compute, models.
23:03And then there's a separate conversation about AI in the context of business use cases, which we're talking about.
23:08And the reality is both of those things are part of that same stack.
23:11If you don't have the infrastructure and if you don't connect the stuff that you're innovating up here into the
23:17heart of the organization, it becomes a pilot or proof of concept that, you know, just fades away after a
23:23few months or whatever.
23:25But you have to wire that into the systems, the processes, the platforms that allow you to evolve.
23:31Because in so many of these examples, this is something you have to build on top of.
23:36It can't just be we did this little thing over here, you know, with Beauty Genius, but actually all of
23:41the data that the consumer gives us or that person, we lose it and we forget about it.
23:45It doesn't go anywhere or, you know, in the context of sensory panels and creating new tastes, it doesn't actually
23:52wire into product development.
23:53It just goes into a Word document survey or Google Docs that somebody reads, you know what I mean?
23:58As opposed to like thinking about how do you wire those experiments and those business use cases into the core
24:04infrastructure around AI that you put in the company, because those connections are what makes it repeatable.
24:10You have to connect the dots together. Otherwise, you continue to work in silo.
24:15And the fact that AI can tap in many different fields, whether it's consumer feedback, research, expertise of a guy
24:24somewhere in the labs or in a country, very strong, etc. It's where it's interesting.
24:30That's where augmented intelligence comes in, which I think it's going to be our new AI. Augmented intelligence is artificial
24:36intelligence.
24:37I love that you said that.
24:38We say augmented human in L'Oréal, but that's the idea. The idea is globally, you can also, you can
24:44back up your intuition.
24:45When you have an idea, it's much, it's much faster. I'm sorry. I said faster.
24:51When you have an intuition, at least you can, yes, you can much faster discover if it's true or not.
24:58Well, you mentioned, Drew, and that just perked me up a little bit. The digital twin.
25:03Yeah.
25:04Say more.
25:05So we've been using digital twins across, you know, my world and other parts of the company to just give,
25:12you know, each brand has a digital twin, an agent.
25:17Sweepstas, Canada Dry, all of our brands. And it allows us to just ask questions. Do you like this idea?
25:23Do you like this creative? What do you think about this new product? What do you think about this packaging?
25:29It allows, that's the stuff that now happens in minutes versus months. And that's great because it allows us to
25:36move through and then marketers could think about other ways that they can drive the business.
25:41And again, in the food and beverage world, people want new, right? You win a lot in the margins, right?
25:50Our product is one of our biggest media assets.
25:54And so changes you make to how that product looks on shelf is dramatic in the beverage space.
26:00And so that's where some twins come in. Now we're going to go on the R&D side and say,
26:06how do we take end to end, have a fully, you know, agents enabled R&D process that allows us
26:15to get to, you know, innovation faster because functional benefits are really making.
26:21And unlike before, a big impact in terms of what people are drinking. So protein, GLP-1, all these things
26:29are affecting beverages and the ability to kind of a digital twin to guide us through, you know, should we
26:35put protein in water?
26:37We have a brand called Core. Well, yes or no, what does that look like? What should that functional water
26:43product look like?
26:44A digital twin will make us much more effective at solving that problem and positioning that brand for a consumer.
26:52And our marketers love that because it allows them to push where they might not have pushed before and have
26:59more confidence because there's another partner to that innovation process.
27:05Digital twin are also very much used to predict what the product will do on you, the efficacy.
27:11We have in the booth of L'Oreal, you can see the digital twin for hair.
27:14So you have your digital twin that is coloring her hair for 30 years using this and this product, this
27:22color, this lens, et cetera.
27:24And then you can really modelize probably the structure of the hair after so much, I don't know, hair color,
27:31lens, sun exposure, whatever.
27:35And then you can predict which product will work the best and will fix the best on the surface of
27:40the hair.
27:41So the digital twin really helps the production.
27:45I love this, the predictive modeling and the digital twin feels like science fiction, but it's happening right out here,
27:52which is so fascinating.
27:53You know, I had a question for all of you and you kind of answered it, but I want you
27:58to make it.
27:59We're good. We're so good.
28:00We're done. Not yet.
28:01But I was thinking about, and I know Delphine didn't like the word speed, but it is about speed because
28:07you can now do things faster and more quality.
28:11The quality has changed because of it. But for the three of you, from your vantage points, when it comes
28:19to speed and authenticity and one cannot be done with the other, how do you reconcile that?
28:26So sometimes you have to go super fast, but you have to be authentic.
28:30You have to keep that human in the loop. You have to slow down a little bit.
28:33How do you reconcile that in the actual work you're doing?
28:35I think in the context of maybe, you know, thinking not just about authenticity in the context of marketing, but
28:42thinking about like Delphine's example of what are the things that are true to you as a company and what
28:47you want to stand for, right?
28:48I feel like in the context of AI, it becomes even more important to think about what those guardrails are.
28:53Like you mentioned, the use of actual real people in imagery.
28:56That's a strategic decision. That's not an AI decision.
28:59But in a world where AI is enabling so many of your communications, if you don't make that a strategic
29:05decision, that then essentially can proliferate in a way that you don't want.
29:09So I think the way I think about this in the context of a lot of the work we do
29:14with clients is thinking about, you know, what are those guardrails?
29:18What are those principles that are not on a, you know, on a piece of paper that are internalized, but
29:25that are systematized in systems that allow you to, at the speed of interaction, reflect your brand or reflect the
29:34strategic choice you've made.
29:36You know, in the context of, you know, healthcare as an example or areas which are regulated, we build, as
29:43an example, human-in-the-loop moments just for validation.
29:48We could easily have enabled an agent to take the entirety of the workflow out, but you say, no, actually,
29:55you know what?
29:55We're talking about making decisions about whether we want to give somebody a mortgage or not.
29:59Or we're talking about a healthcare interaction where an agent is going to drive shipping somebody, an inhaler, because air
30:08quality is deteriorating.
30:09In those moments, a simple validation step is, again, part of the ethos of what you have to build in,
30:14because that's what's important to you.
30:16And I think it's different by organization in terms of how you do that.
30:19And is it the same for the two of you?
30:22No, but I would say between being fast and authentic, I think that we put, as you said, many points
30:29of control and a lot of ethical positioning.
30:33And then sometimes you have to be fast to be ethical.
30:37As you probably know, L'Oréal took a stake in Galderma, which is a medical company.
30:41And sometimes when you can fastly try several molecules, you have many people that you can save at a moment.
30:49And the fastness is also sometimes a way to be trustworthy or useful and authentic.
30:57That's why it's not only about shampoos or drink or the AI can really make good in many different fields.
31:06And that's why it cannot be systematically opposed, you know, the fastness and the ethics.
31:13And this is the discovery part.
31:16The discovery part is also fascinating.
31:18You talked about it from a science perspective, but also how you get to the consumer what they want faster.
31:23Yeah.
31:24They are upheating.
31:25What I was going to say is, you know, it's all in service of consumer obsession, doing what's right for
31:31the consumer.
31:32And in some parts, there's progress over perfection because our channel is taking us there.
31:39So, for example, on the marketing side, you know, the leaders in driving AI, I mean, Amazon has a big
31:46$70 billion ad business.
31:48Netflix has jumped into the ad game.
31:50The people that are driving the tech are monetizing on advertising, and the pace of change of how advertising and
31:58AI are happening in that intersection with brand marketers is just happening at an incredible speed.
32:04That's something that we have to learn fast and move fast in because, you know, particularly in the U.S.,
32:10it's different outside the U.S., but retail media is a dominant driving force of how you connect and learn
32:17about your customer.
32:19And so that's where we're moving with exceptional speed because of agentic shopping and the fact that you have, you
32:25know, Walmart and Amazon who are two Goliaths driving us there.
32:29And other areas where we don't have them driving us, the R&D side, we'll take a more measured approach
32:37but still move in ways that we could have moved before in order to get to a better answer.
32:44So speed of, you know, learning loops and getting to amazing products to have more breakout hits, that serves the
32:54customer and serves the company.
32:55So it's a balance.
32:56It's a good, I think it's a good summary.
32:58You go faster to a better answer.
33:01Yes.
33:01That's it.
33:02Huh?
33:03That's it.
33:03You said that.
33:04I want the T-shirt.
33:05I want the T-shirt.
33:06I want the T-shirt.
33:07You go faster to a better answer.
33:08So, in fact, you know, we harmonize everything.
33:12We try to resume your paradox, Anna.
33:15This is a perfect ending.
33:17We're all going to make T-shirts with Delphine's new models.
33:19I will do it.
33:20I will do it for you.
33:21Thank you for your time today.
33:23Thank you, Anna.
33:23Thank you to all of you.
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