Katia Walsh, SVP and chief strategy & AI officer, Levi Strauss & Co.

Levi’s AI chief Katia Walsh on lifting women and fighting algorithmic bias

Katia Walsh, Senior Vice President and Chief Strategy & AI Officer, Levi Strauss & Co.

When Katia Walsh, SVP and Chief Strategy and AI Officer at Levi Strauss & Co., was a young college student, a teacher told her that math “isn’t for girls.”

It wasn’t until years later that she worked on her Ph.D. in strategic communications at the University of Missouri-Columbia, which involved some applied math and statistics, that she discovered a love—and aptitude—for numbers.

“So many women have been left out,” Walsh said. “I was in my twenties before I realized, wow, this is fun, I love doing it and there are so many uses.”

STEM careers are more welcoming to women and people of color, but progress requires continued investment.

Last year, Levi’s launched an in-house machine learning boot camp to help employees who do not have a formal data science background learn about AI and develop new digital skills. More than 450 people applied for just 60 spots in the program.

About two-thirds of the first class were women.

“I wouldn’t say we were surprised and that we didn’t favor women — it was a very rigorous application process,” Walsh said. “But because we’ve made sure that women are encouraged and because women are just as capable, it showed in the numbers.”

This year about half of the class consists of BIPOC participants.

Inclusion has been part of the culture at Levi’s since the beginning. Fun fact: The company founder, Levi Strauss, who immigrated to the US from Bavaria in the mid-1800s, created a scholarship program at UC Berkeley in 1897 for aspiring designers and fashion entrepreneurs.

Twelve of the first-round scholarships were awarded to women at a time when it was not only rare for women to attend college, but more than 20 years before women were given the right to vote.

Walsh spoke to AdExchanger.

AdExchanger: When I told someone that I was interviewing the chief of AI at Levi’s, they said to me, “Why does a jeans company have a chief of AI?” So why is doing a jeans company have a head of AI?

KATIA WALSH: It’s amazing how much data is associated with everything we produce. Even a store manager handles a ton of data, and I learned that because I spent some time working in the back room unloading boxes, taking orders, putting on the shelves, and actually using the replenishment app my team created to to see how well it works.

I have worked at larger companies from a technology perspective: Fidelity Investments, Prudential Financial, Vodafone. Fidelity is like the original fin-tech. But none of those companies have the powerful global brand that Levi’s has, and I believe brands have an incredible opportunity to make a difference in society. In this job I can make an impact.

We look at the data flow and there are so many possibilities for automation.

Where does AI play a role at Levi’s?

Our ambition is for AI to touch everything and permeate the entire enterprise. It is a process. We’ve only really been working on it for the past two and a half years.

But take marketing for example. We want to make sure our customers feel close to us, which is why we’ve invested a lot in targeting consumers with relevant messages and making sure there’s no waste in our marketing dollars.

How do you do that?

We look at three aspects: targeted email messages, the online experience in our app and the website and the buying experience.

On the website in particular, we personalize search so that the results people see are as relevant as possible to them based on everything we know about their browsing and buying behaviour.

It’s not easy for people to search by category, especially when it comes to clothes. People may want a loose fit or baggy or skinny – and these terms can be subjective. We recently started experimenting with visual search so that people can search our site by uploading images. It’s an experiment. We’ll decide whether to keep it based on how much consumers use it, but we always try to provide these kinds of opportunities.

Levi’s is a 170-year-old brand undergoing a digital transformation. What does that mean?

People have been using the term ‘digital transformation’ for years, but for us it’s more about how a 170-year-old company remains relevant? We just keep evolving and today it’s about digital technologies. But inventions and innovations are part of our heritage. As a company, we have survived two world wars and multiple pandemics, including the Spanish flu.

Why is diversity such an important part of this transformation?

It’s about relevance. A brand should reflect its customer base and its employee base. The world is diverse and that’s why we need to be diverse to stay relevant. It is a business necessity that also applies to technology and especially artificial intelligence.

There is a problem with bias in algorithms that is pronounced when only limited data is available or when it is based on a particular agenda. We want to avoid perpetuating bias, of course, but we also want to minimize it. I don’t think it will ever be possible to completely eradicate prejudice – the world around us is inherently biased – but it is imperative that we do our best as people and as professionals.

Can you share some practical examples of how Levi’s is applying AI to the business today?

Everything in life is a network. There are physical networks connecting us through our phones, as well as human ones. When I first started at Levi’s, I remember thinking, “I wonder if our products are networked too?”

We did analytics that started in China – we’ve since applied this around the world with other products – to understand how our products compare and which ones are complementary, so we can make recommendations beyond personalization. For example, when people buy certain products, it encourages the purchase of others, such as a black T-shirt that encourages people to buy the same in white and other colors. We also learned that some products cannibalize each other.

We’ve taken what we’ve learned and used on our site, in our app, and in our stores. None of this is theoretical.

This interview has been edited and abridged.

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