How Retailers Can Use AI To Compete—and Win—This Holiday Season

Meet the women harnessing AI to help retailers fight fraud, simplify discovery and unlock data-driven growth.

Retailers are under mounting pressure to fight fraud, simplify overwhelming product choices and make smarter decisions with their data. While industry giants have long set the pace, a new wave of women leaders is showing how AI can level the field. From detecting fraudulent returns at scale to powering more intuitive fashion discovery and unlocking real-time insights for beauty brands, executives at Narvar, Lyst and Daash Intelligence are proving that AI isn’t just transforming retail—it’s equipping every retailer to compete and win.

Fighting Fraud While Protecting the Shopper Experience

Customer loyalty in retail often hinges on smooth, convenient returns, but that convenience comes at a massive cost. Returns across the industry are a growing crisis, costing $890 billion in 2024 alone. Of that massive number, a whopping $103 billion were fraudulent.

This is where Anisa Kumar, CEO of Narvar, steps in. “You build trust and loyalty not just when things go right but by taking care of your customer when things go wrong,” she explains. Narvar, which works with more than 1,500 retailers including Gap, Sephora and Levi’s, has defined the “post-purchase experience” space, the critical period after a customer clicks buy.

Narvar’s AI-powered solutions like Shield and Assist detect fraudulent returns and delivery claims while keeping transactions seamless for trusted customers. By analyzing billions of consumer interactions and patterns from QR code generations to dark web activity, Narvar flags fraud in real time and personalizes responses.

“We’ve been building this AI for the last two years,” says Kumar. “It’s based on ten years of 42 billion touch points a year in terms of consumer interactions.” Narvar uses AI to analyze huge data sets and put them into patterns that enable prediction of intent. “This gives us a human-centered approach to putting in friction where the intent doesn’t look great and ensuring the brand operates with efficiency when the intent looks real. AI is that bridge between scale and humanity.”

The result is millions in recovered revenue for retailers and fewer frustrations for shoppers. Narvar gives retailers the ability to deliver the same level of precision and protection once reserved for only the largest players.

Making Fashion Discovery Smarter

Endless product assortments can overwhelm shoppers. For consumers, online shopping often feels like too many choices with too little clarity. With more than 27,000 brands and nine million products hosted on its platform, Lyst is using AI to tackle this challenge head-on.

“Shoppers face sprawling options scattered across hundreds of sites, which can make finding what you want feel painful,” says Emma McFerran, Lyst’s CEO.

Lyst uses AI to power smarter search and discovery. Instead of forcing users into rigid categories, its joint image-and-text embedding models understand product similarities the way a shopper might. That allows Lyst to recommend relevant items, whether through visual matching, natural language searches or curated edits, making fashion discovery feel less like endless scrolling and more like a personal consultation.

“AI already helps us process millions of signals from trends, availability, price movements and customer behavior,” McFerran explains. “We combine those models with editorial judgment so the output is a smartly considered edit of just a handful of strong choices.”

Through its Lyst Index, which distills billions of data points into quarterly reports on what’s trending globally, the Lyst platform has also become a trusted authority in fashion retail. “Our positioning and scale give us a unique vantage point on consumer behavior, tastes and trends as they evolve globally,” McFerran says.

Giving Brands a Data Advantage

Big retailers have long leveraged vast data resources to optimize pricing and assortments. Indie brands rarely have that luxury, especially in fast-moving industries like beauty where trends shift overnight. Melissa Munnerlyn co-founded Daash Intelligence to level that playing field.

“Few industries move faster or compete harder than beauty,” she explains. “We saw a clear gap: many independent brands were making high-stake decisions without knowing how competitors were performing on shelves or online.”

Daash uses AI to unify fragmented data, giving brands weekly visibility into sales performance, pricing shifts and consumer preferences. Its models track performance at the SKU and store level, turning scattered information into actionable insights.

“AI lets us cut through the noise,” Munnerlyn says. “We can now show how specific ingredients, formats or claims are trending in real time across brands, retailers and categories.” For example, Daash might detect an early surge in vitamin C serums or pinpoint which haircare products are maintaining price points despite consumer pullback. This enables brands to adjust pricing, optimize assortments and innovate more strategically.

Instead of relying on manual spreadsheets or guesswork, Daash enables brands to compete with the clarity once reserved for retail’s biggest players. “The best parts of my days are when teams immediately spot stories in our platform and start building on each other’s takeaways,” Munnerlyn says. “I can just let the data speak for itself.”

The Future of Women Leading AI in Retail

A new wave of women leaders is proving that AI can help retailers win. Still, breaking into tech has been harder than climbing the ranks in traditional retail. “Retail women leaders broke the glass ceiling earlier,” Kumar says. “There was more acceptance in retail than there is in technology. Tech is still a little bit of a boys’ club, but it is changing every year as more women founders and CEOs scale businesses.”

At Lyst, McFerran says women make up 54 percent of its workforce and hold more than 40 percent of tech-focused roles. Munnerlyn, who has always been “rooted on the tech side,” believes women still feel constant pressure to excel. “I’ve been fortunate to be in beauty tech for the last eight years. There’s always pressure to stay ahead, to be on the defining forefront of what’s next, while focusing on delivering something truly valuable for our users and brands.”

Together, these leaders show that women are not just participating in AI-driven retail innovation, they are defining it. And as AI becomes the backbone of everything from fraud prevention to product discovery to business intelligence, their leadership is showing how retailers of every size can compete, and win, against the giants.