Artificial intelligence is becoming more widespread, but many people are wondering: Who is most likely to adopt AI in their daily lives? Many believe that tech-savvy people—those who understand how AI works—are the most eager to adopt it.

Surprisingly, our new study, published in the Journal of Marketing , finds the opposite. People with less knowledge about AI are actually more open to using the technology. We call this difference in willingness to adopt new technology “low literacy—high receptivity.”

This link is found across different groups, contexts, and countries. For example, data from Ipsos , covering 27 countries, reveals that people in countries with lower average levels of AI knowledge are more receptive to AI adoption than those in countries with higher levels of knowledge.

Similarly, our survey of US undergraduates finds that those with a lower understanding of AI are more likely to say they would use it for tasks such as college assignments.

We believe this counterintuitive link between literacy and appetite comes from the way AI is now performing tasks once thought to be reserved for humans: When AI creates a work of art, writes a heartfelt response, or plays a musical instrument, it can feel almost magical, as if it is entering human territory.

Of course, AI doesn’t actually have these human qualities. A chatbot can generate an empathetic response, but it doesn’t feel empathy. People with more technical knowledge about AI understand this.

They know how algorithms (sets of mathematical rules used by computers to perform particular tasks), training data (used to improve the functioning of an AI system), and computational models work. For them, technology is less mysterious.

For those who have a lesser understanding of how AI systems work, however, it can seem like something magical and impressive. We believe that it is this sense of magic that makes these users more open to using AI tools.

Moreover, our studies show that the link between low knowledge and high appetite is stronger for the use of AI tools in areas that people associate with human traits, such as emotional support or advice.

Conversely, when it comes to tasks that don’t evoke these human qualities – for example, analyzing test results – the pattern is reversed: people with a higher level of AI knowledge are more receptive to these uses because they focus on the effectiveness of AI rather than its “magical” qualities.

Our relationship with AI is not a question of capacity, fear or ethics

Interestingly, while people with low AI literacy are more likely to view AI as less capable, less ethical, and even a little scary, this link between low digital literacy and greater receptivity persists. Their appetite for AI seems to stem from their amazement at its capabilities, even as they clearly see its downsides.

This finding offers new insights into why people react so differently to emerging technologies . Indeed, some studies suggest that some consumers are supportive of new technologies, a phenomenon called “algorithm liking,” while others report skepticism, or “algorithm aversion .” Our research suggests that perceptions of AI’s “magic” are a key factor shaping these reactions.

These findings pose a challenge for policymakers and educators. Efforts to improve understanding of AI may – unintentionally – dampen people’s enthusiasm for using AI by making it seem less magical. This creates a delicate balance between helping people understand AI and keeping them open to its adoption.

To harness AI’s potential, businesses, educators, and policymakers must strike this balance. By understanding how the perception of AI as a “magic” technology shapes the public’s appetite for AI, we can help develop and deploy new products and services that take into account how people perceive AI—and help them understand the benefits and risks of AI.

And ideally, this will be done without losing the sense of wonder that drives many people to embrace this new technology.

Author Bio: Chiara Longoni is Associate Professor, Marketing and Social Science at Bocconi University, Gil Appel is Assistant Professor of Marketing, School of Business at George Washington University and Stephanie Tully is Associate Professor of Marketing, USC Marshall School of Business at the University of Southern California