In the era of artificial intelligence, pharmaceuticals need to correctly understand privacy

AI has been in the pharmaceutical industry soon and professionals see obvious value – from shortening drug development timelines to matching patients to more relevant trials. But despite the acceleration of innovation, consumer trust in the technology remains behind.

Pew found that one in five Americans feel uncomfortable with health care providers that rely on AI, and another 37% believe that AI use in health care will worsen the safety of patient records. But the challenge is not the lack of innovation. This is the technology moves faster than the privacy framework can support. This is an issue that cannot be ignored in the pharmaceutical industry.

The risks nowadays are not only how AI is performed, but how patient data is processed and agreed to at each step.

How to balance trust, progress and privacy

Companies want to move quickly, and patients want to control their information. Both are possible – but only if we consider privacy as part of how the system is built, not in order to be compliant.

Data is now flowing in from all directions: applications, trial portals, insurance systems, patient communication. Pharmaceutical companies need to agree to infrastructure that can manage the preferences of the entire ecosystem and keep pace with changing global regulations. Without this, they are posing risks to their business and service personnel. Once trust erodes, it is difficult to rebuild – especially in areas where participation and outcomes depend on it.

Perform dispersion tests. These models rely on AI-powered tools such as wearables and remote monitoring, many of which send data through systems other than HIPAA traditional protection. The same goes for direct-to-consumer health tools, which often collect data across platforms with imbalanced privacy protection. HIPAA does not apply in these cases, but 81% of Americans believe that digital health applications are covered by law. This leaves many people unaware that their personal data can be legally sold to third parties.

This is why privacy is not reactive. It needs to be built into how an organization operates and launches its AI tools. This includes rethinking how to capture, update and respect consent forms in clinical, operational and patient systems using the technology. In many cases, this also means that consent will be aligned with communication preferences: the messages people want to receive, when and how.

The good news is that patients want to share data when they control and understand how to use it. This is not achieved by burying information in intensive policies or hard to find settings. It is done by providing clear, actionable options – such as the ability to exit the data used to train AI and make these choices easy to act on. Here, a strong consent strategy is at the heart of patient trust.

Privacy beyond legality

When using sensitive patient information across AI systems, privacy cannot be considered a legitimate box to check or paste it onto the role of the security team. It must be seen as a competitive advantage – it can build loyalty and flexibility in the way a company operates in different markets. It directly affects the way people interact with companies and when ignored, it quickly becomes a corporate risk.

The point is simple: AI has the potential to change the development of pharmaceutical methods and provide care, but this shift depends on whether privacy can keep up. Privacy needs to be seen as a core business function, not a legal afterthought. This means making it a constant transparent conversation between industry organizations and their audiences. When patients believe that their information will remain secure in the AI era, this means better engagement, better data sharing, and feedback loops between products and patients.

Leaders in the Pharma AI era will not be remembered for moving at the fastest speed, but for making money and keeping trust. Privacy will determine which companies move forward and which ones lag behind, making it one of the biggest tests in the industry. Those who see it as the core of their operations, rather than the hindsight, will be the most important ones.

Photo: Flickr user Rob Pongsajapan

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