Trust in AI - Why Acceptance is higher in the Beauty Market than in the Healthcare Sector

Artificial intelligence has long since become part of everyday life. It recommends products, analyses skin images, prioritises diagnoses and structures data. Nevertheless, it is not accepted everywhere in the same way. While AI is often perceived as a driver of innovation in the beauty market, consumers are much more cautious about it in the healthcare sector. The difference lies less in the technology itself tha

n in the context in which it is used.

Trust as the Key Currency in the AI Age

Trust determines whether AI is used or rejected. A key reference point for global trust research is the Edelman Trust Barometer, published annually – an international study that has been examining trust in institutions, companies, media and technologies for over two decades. The results consistently show that trust is highly context-dependent, especially when it comes to sensitive issues such as health and data processing. Technologies are generally perceived as progressive, but as soon as personal health data or medical decisions are involved, mistrust increases significantly.

In addition, studies on so-called algorithm aversion according to Dietvorst show that people trust algorithms less when decisions are perceived as risky. Even if systems work more accurately statistically, machines are blamed more for errors than humans. AI is therefore not evaluated in isolation, but in relation to the perceived risk.

In beauty, AI is experienced as enhancement - not as risk. (Credits: Bobbi Brown)

Beauty: Performance, Experimentation and low Risk

This risk is significantly lower in the beauty market. Here, AI is mostly experienced as a performance tool for example, in skin analyses, product recommendations or virtual try-ons. In the worst case, incorrect recommendations lead to an ineffective product purchase, but rarely to serious consequences. Consumers are more willing to experiment, and innovation is perceived as added value. Social media socialisation, influencer culture and digital habituation have further increased the acceptance of technological support. Beauty decisions are more lifestyle- and performance-oriented, which is why AI is understood as an optimisation tool – as technological support for better results. The perceived fall height remains limited, the potential improvement visible.

Healthcare Sector: Safety, Regulation and Responsibility

Different standards apply in the healthcare market. Here, the focus is on diagnosis, therapy, data protection and potentially irreversible consequences. Risk perception is higher, and expectations regarding evidence and regulatory safeguards are correspondingly more pronounced. Studies on consumer confidence in the healthcare sector show that patients expect clear evidence of validation, transparency and human control mechanisms. The anchor of trust remains with doctors and pharmacists, not technology platforms. AI can provide support, but must not appear autonomous. While beauty consumers see AI as an additional option, healthcare consumers see it as a co-decision-maker in a highly relevant context.

Psychological Differences

The differences can be explained by perceived risk theory: the greater the potential negative consequences of a decision, the greater the priority given to certainty. In the beauty market, the risk is low, while in the health sector it is high. Accordingly, there are increasing demands for transparency, human-in-the-loop models and comprehensible decision-making logic. Studies also show that black box systems increase scepticism, especially in sensitive areas of application. Trust is not created by technological complexity, but by explainable processes and visible control.

What this means for Providers

For companies in the beauty market, the focus is on performance, user experience and speed. AI should be visible and convey innovation. In the healthcare sector, on the other hand, the focus is on validation, data protection, certification and integration into existing trust structures. Here, AI must be positioned as a supporting infrastructure, not as a substitute for human expertise.

Conclusion

AI is not evaluated uniformly. Its acceptance depends on the context, the perceived risk and existing trust architectures. In the beauty market, AI is seen as an optimisation tool, while in the healthcare sector it still has to prove its legitimacy. Therefore, it is not only the performance of the technology that is decisive, but also how transparently, integrated and responsibly it is used. Trust is not created by innovation alone, but through context, communication and control.