AI-first startups aren’t the only ones using machine learning to scale to massive size. From pasta sauce to miniskirts, consumer companies are fueling growth with the latest tech.

The Forbes Under 30 list is ripe with technological disruption. Sure, the usual suspects of software start-ups, biotech and finance are betting billions machine learning and generative AI will revolutionize their worlds. A surprising number of consumer brands are embracing the hottest tech tool to turbocharge their product development, logistics operations – even creativity.

Take Troy Bonde, 26, and Winston Alfieri, 25, the founders of New York-based pasta sauce company Sauz. The 2026 Forbes Under 30 Food & Drink company is out to bring new flavors and a younger vibe to an industry that generates roughly $2.5 billion in annual U.S. sales but has looked largely the same for decades.

To date, Sauz has raised nearly $23 million from investors including CAVU Consumer Partners, Strand Equity and even Norwegian record producer Kygo’s Palm Tree Crew. Founded in 2023, the brand has rapidly expanded its footprint, landing shelf space at major retailers such as Whole Foods, Sprouts, Target and Kroger, while also building a direct-to-consumer business through its own online store.

By 2025, Sauz surpassed $10 million in annual sales, but that growth wasn’t driven by flavor innovation alone. Behind the scenes, the company relies on AI to stay lean while still scaling. With just 10 full-time employees, AI helps them oversee manufacturing, manage logistics and ensure its jars are consistently produced and delivered across more than 8,000 retail locations nationwide.

At the center of their tech stack, says CEO Bonde, is an “enterprise resource planning” system called DOSS. This system allows Sauz to keep all its business functions on one platform, especially useful for automating tasks like forecasting inventory, coordinating with vendors and keeping accounts of finances. Information flows through this shared system, and Sauz then dedicates a small team to act on the necessary tasks. The platform also includes analytics and tools that help the team see performance trends and make faster, more informed decisions.

“The strongest startups generally use tech to eliminate operational friction,” Bonde says. “Automation and AI enable teams to stay capital-efficient, move faster and focus human effort on product quality, brand and customer experience.”

Automation and AI is also powering Kelly Pan, the 2026 Under 30 Social Impact lister and founder of meatless fish company Impact Foods, to convince the market that plants can replace protein. Pan, 25, developed her idea for vegan “tuna” and “salmon” while taking a class focused on alternative meats at UC Berkeley. Teaming up with a biochemist and computer scientist, and then raising some $2 million from investors, Impact Food’s sushi-grade products are now being served in restaurants in California and New York, including at well-known chains like Pokeworks. Plus, Impact Food has brokered deals with food service partners like Japan Airlines Sakura Lounge in Honolulu. Now the startup is focusing on international expansion, starting with the Japanese market.

While Pan depends on cutting-edge manufacturing to make her complex products, she points to backend technology as key to growing the business. “Scale does not always mean adding volume or headcount. Often, the bigger challenge is avoiding constant restarts,” she says. “We built our backend systems to make food development repeatable rather than dependent on any one person, facility or moment in time.”

Similar to how Sauz operates on a central hub, Pan says Impact Food has created a system that allows it to keep shared records of every recipe change, production run, sales conversation, marketing effort and customer comment, so everyone in the company can see what decisions were made and why. The startup has been doing its own manufacturing from early on, and pairing it with this system has made it possible to tweak texture, cost and format from one run to the next without relying on external vendors. “The most valuable technologies are the ones that help teams capture decisions and learnings — product formulations, operational insights and sales strategies — so progress keeps building instead of resetting as the company evolves,” she says.

Fashion brands, too, are leaning on AI to expand their brands and stay current on the breaking trends. Ramin Ahmari, the founder of fashion brand Finesse, relies on machine learning to design and advertise miniskirts and shoes to his direct-to-consumer customers.

Finesse uses AI to continually analyze trends and consumer habits from across social media platforms, Google trends and more to identify what’s viral (or on the rise) at any given moment. Based on this data, Finesse designers draft 3D renderings — using generative AI tools — of the items they think will sell. These digital variations are then shared across the Finesse app and through polls on social media where shoppers can vote directly on what they’d purchase. The most popular designs win, and only those go into production.

“In terms of pure data potential, it's incredibly valuable because I'm asking you, as a consumer who's already following us or interacting with us, what do you want to buy?” Ahmari, who made the Under 30 Art & Style list in 2024, said. “No data is better than first-party data.”

This process doesn’t just give Finesse a leg up in knowing what’s popular, but allows the startup to save time and money on designing items that won’t end up selling. And it significantly limits waste since fewer garments go unsold.

Finesse has raised $56 million in funding since its launch, and now has offices in the U.S., London and Guangzhou, China. Up next, they’re working on ways to use AI not just for consumer-led designs, but co-creation between them and their shoppers.

“It starts with the technological infrastructure underneath it, that's really our bread and butter,” Ahmari said.