Traditionally, many American consumers have been dedicated to the “Made in the U.S.A.” label as a patriotic symbol. But a new shift shows that brand loyalty to “Made in the U.S.A.” labels is slipping. Consumers are being lured by other considerations when making purchases. Experts agree that this shift is part of a bigger trend where efficiency is dwarfing brand loyalty.
Why Loyalty To ‘Made In The U.S.A.’ Labels Is Fading
A new study of 3,000 adults from The Conference Board shows that U.S. consumers are less likely to factor country of origin—even the U.S.—into their product buying decisions than they were just three years ago. The report finds that only 50% of U.S. adults are more likely to buy American-made products, down from 60% in 2022, an 18% dip as consumers increasingly prioritize price and value over where they’re made.
“Country-of-origin cues still matter—but their influence is slipping,” according to Denise Dahlhoff, author of the report and director of marketing and communications research at The Conference Board. “As price concerns intensify, many U.S. consumers appear to associate ‘made in’ labels with elevated prices due to generally higher domestic production costs as well as tariffs on foreign-made goods. Increasingly, consumers prioritize value and affordability over emotional affinity for certain countries, including their own.”
You can also blame AI for the shift in consumer loyalty. Whether a product is ‘Made in the U.S.A.’ or not, Joe Hudicka, author of The AI Ecosystems Revolution, is convinced that AI is moving us from a world where brands won’t just wait for you to shop, they’ll predict what you want, get it to you fast and earn your trust.
Hudicka told me that predictive AI is already capturing the rules of brand loyalty. He told me that in a value-first economy, it can deepen trust when it saves people money, time and frustration. But he adds that it can just as quickly destroy trust if it feels manipulative. He argues that the real challenge in the AI age is balancing personalization with privacy and turning data into a transparent, mutual value creator instead of a one-way manipulation.
The shift boils down to AI demands over “made in America” labels. Hudicka cites a nationwide study by Lightyear, reporting that AI has become woven into daily life of the average American, and it now dominates other factors to consider.
The poll of 1,000 U.S. workers revealed that 35% of Americans are now turning to ChatGPT, image generators or smart tools like Siri and Alexa every single day. For some, it’s just asking a smart speaker a quick question. For others, AI powers multiple aspects of their routine.
Some of the shift is fear-based over higher prices and inflation worries. Hudicka points out the fact that fear still motivates the American workforce to prioritize AI over brand loyalty is reflected in the Lightyear findings:
- 49% fear AI will replace their jobs.
- Only 10% are actively upskilling to stay competitive.
- Gen Z bucks the trend—67% are learning AI skills for work.
- 25% of workers already use AI tools daily.
- 14% have earned a raise from learning new AI skills.
Another factor, according to Hudicka is the change in how people shop. He says Americans have seen a 2.4% rise in consumer prices over the past month as tariffs kick in. “So if quality and price are the two biggest factors in whether to purchase a product, consumers may by default opt to buy more items made in America. The challenge is that manufacturers today are tied into the global economy, so even a largely American-made product may get some of its parts from overseas.”
He argues that in a value-first economy, predictive AI will only strengthen brand loyalty because it clearly saves customers both money and time without eroding their sense of choice. “Brand loyalty will remain a strong factor, but AI-recommended alternatives will raise our competitive awareness. If enough of us try and have great experiences with competitive products, a tipping point will occur, shifting the competitive power balance.”
Why Trust In AI Dwarfs ‘Made In The U.S.A.’ Labels
Hudicka is convinced that the future of brand loyalty in the AI age will be decided by trust, and he insists that trust is not given in business, it’s earned. He raises the question, “Will brands use AI to serve customers or to exploit them?”
He posits that the lynchpin in all of this comes down to privacy. “To achieve that more perfect data set upon which predictive AI depends, we’ll all need to share more about ourselves and our lives than ever before. Will we do that?” His experience with United Airlines illustrates the point.
“I became one of their best customers, flying worldwide every week or so for years. I completely stopped considering alternative carriers—I trusted them to give me not only a fair price but perhaps even reward me for being such a loyal customer. But one dark day in 2023, I had to make a last-minute trip to Germany. United quoted me roughly $11,000, and out of time, I bought.”
A few months later, when he had to return to Germany, United again quoted him that $11k price—even with 60 days’ lead time. He declares this is how he learned about the dark side of predictive AI: surveillance pricing.
“United knew I was buying from them on blind trust, and rather than helping me, they leveraged AI against me, squeezing every last penny out of me. Business class shifted from a perk to a bidding war. And I caught them by checking their Star Alliance partner pricing. Lufthansa amazingly offered me a price that was more than 50% cheaper—on the very same United plane.”
A Final Word On ‘Made In The U.S.A.’ Labels
In the past, patriotic Americans have been loyal to the “made in the U.S.A.” brand. Hudicka suggests that predictive AI has the potential to give rise to the ultimate loyalty engine—anticipating needs, saving time lowering costs—but only if it’s paired with transparent, opt-in data practices that respect privacy.
Whether or not AI usurps “Made in the U.S.A.” labels hinges on American consumers putting their trust in AI. He predicts that the moment they feel AI is being used against them, trust will collapse. “And once that trust is gone,” he concludes, “no algorithm in the world can win it back.”