AI has quickly been moving through the pharmaceutical industry, where professionals are seeing clear value – from shortening the drug development timeline to matching patients to more relevant trials. But while innovation accelerates, consumer trust in the technology is lagging behind.
Pew found that 3 in 5 Americans would be uncomfortable with their healthcare providers relying on AI, and another 37% believe AI use in healthcare would worsen the security of patient records. The challenge isn’t a lack of innovation, though; it’s that the technology is moving faster than privacy frameworks can support. And it’s a problem that the pharmaceutical industry can’t afford to ignore.
What’s at stake now isn’t just how AI performs, but how transparently companies that use it handle patient data and consent at every step.
How to balance trust, progress, and privacy
Companies want to move fast, and patients want control over their information. Both are possible – but only if we treat privacy as a part of how systems are built, not something tacked on for compliance’s sake.
Data now flows in from all directions: apps, trial portals, insurance systems, patient communications. Pharma companies need consent infrastructure that can manage preferences across this entire ecosystem and keep pace with changing global regulations. Without that, they’re creating risk for both their business and the people they serve. And once trust erodes, it’s hard to rebuild – especially in a field where participation and outcomes all depend on it.
Take decentralized trials. These models rely on AI-powered tools like wearables and remote monitoring, many of which send data through systems outside of the traditional protections of HIPAA. The same is true for direct-to-consumer health tools, which often collect data across disconnected platforms with uneven privacy protections. HIPAA does not apply in these instances, yet 81% of Americans incorrectly believe digital health apps are covered under the law. That leaves many unaware their personal data could legally be sold to third parties.
That’s why privacy can’t be reactive. It needs to be built into how organizations operate and launch their AI tools. That includes rethinking how consent is captured, updated, and respected across clinical, operational, and patient-facing systems that use this technology. In many cases, it also means aligning consent with communication preferences: what messages people want to receive, when, and how.
The good news is that patients want to share data when they feel in control and understand how it will be used. This isn’t accomplished by burying information in dense policies or making settings hard to find. It’s done by offering clear, actionable choices – like the ability to opt out of data being used to train AI – and making those choices easy to act on. That’s where a strong consent strategy becomes central to patient trust.
Privacy beyond legality
When working with sensitive patient information across AI systems, privacy can’t be treated as a legal box to check or be tacked onto the role of a security team. It has to be treated as a competitive advantage – one that builds loyalty and flexibility in how companies operate across different markets. It directly affects how people interact with a company, and when ignored, it quickly becomes an enterprise risk.
The takeaway is simple: AI has the potential to transform how pharma develops and delivers care, but that transformation depends on whether privacy can keep up. Privacy needs to be seen as a core business function and not a legal afterthought. That means making it an ongoing, transparent conversation between industry organizations and their audiences. When patients trust that their information will be kept safe in the AI age, that means better participation, better data sharing, and a stronger feedback loop between product and patient.
Leaders in pharma’s AI age won’t be remembered for moving the fastest, but for earning and keeping trust along the way. Privacy will determine which companies pull ahead and which fall behind, making it one of the industry’s biggest tests. Those that treat it as core to their operations, rather than an afterthought, will be the ones that come out on top.
Photo: Flickr user Rob Pongsajapan
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