Schlitz became America’s top beer by showing consumers how it made its product. In the early 20th century, the company rose from also-ran to number one among American beer-makers with a brilliantly simple advertising strategy. It started telling customers about its brewing process in vivid detail: water from artesian wells, elaborate pulp filters, and meticulously sterilized bottles. The strategy worked spectacularly.

The brewing process itself was not especially novel. Every serious brewer did something similar. What Schlitz had that its competitors lacked was not a radically better product, but instead radical transparency. People trusted what they could see and understand, and as a result, the campaign took Schlitz to the top of the American beer market.

The campaign was the work of Claude Hopkins, an advertising executive with a passion for rigorous testing and measurable results. Eventually, Hopkins would go on to write Scientific Advertising, which became one of the most influential books in the history of the industry.

Now, in 2026, the same principle will either make or break companies seeking to transform themselves with AI.

Our research on the behavioral science of change shows that successful transformation depends on whether people trust and participate in the change. After all, all AI changes are people changes.

At companies we’ve advised through change, we’ve seen that people are more inclined to start using new tools when they understand at least something about how they work.

For example, a financial analyst provided with an AI-generated risk assessment will be more inclined to use it if they understand which factors drove it. The same is true of a customer service agent deciding whether to follow an AI-generated response suggestion, or a procurement manager evaluating an AI-ranked list of suppliers.

Leading AI companies are also embracing the proven principle of transparency. Popular models like Claude now show their reasoning before delivering a final answer, letting users watch the model work through a problem step by step. Schlitz Beer would have approved.

The companies that win using AI will do so Schlitz-style. They’ll explain how their applications work, show where humans remain accountable, and bring people into decision-making rather than presenting them with contextless results from a black box.

Schlitz won by making the invisible visible. AI leaders can do the same. In every era of transformation, trust, not technology, is what drives adoption.

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