Healthcare’s AI Challenge Is Ultimately About Trust

AI in healthcare promises to reduce administrative workloads, support clinical decisions and improve patient communication. However, healthcare organisations must balance these benefits with patient trust, data privacy and cybersecurity. As AI becomes part of everyday healthcare delivery, organisations face two connected challenges. They must protect sensitive patient information while ensuring technology strengthens, rather than weakens, the relationship between clinicians and patients.

Jo Salisbury, Regional Director Growth & Performance, APAC, LevelBlue, says healthcare organisations need to consider trust from the beginning of their AI adoption plans. This means understanding how AI systems handle patient data and whether they genuinely improve the care experience. While AI could help clinicians spend less time on administrative tasks, it also introduces questions about how healthcare providers collect, access and use sensitive information.

Salisbury said, “Healthcare is one of the clearest examples of AI’s double edge. The technology can help clinicians work more efficiently and potentially give them more time with patients. However, it also changes how sensitive information is collected, accessed, and used.

“The opportunity is significant, although healthcare organisations need to think about trust from the beginning. Patients shouldn’t have to trade confidence in how their information is handled for the benefits AI can provide.”

Protecting Patient Data as AI in Healthcare Expands

Healthcare organisations handle some of the most sensitive personal information, including medical histories, diagnoses and patient records. Introducing AI creates additional considerations around how organisations collect, access, store and share that information. These concerns become increasingly important as healthcare providers move beyond isolated AI trials and integrate the technology into routine clinical and administrative operations.

Before introducing an AI application, healthcare leaders need to understand what information it requires, where that information originates, and how systems process it. They should also identify where data is stored, who can access it, and whether third-party systems are involved. This visibility helps organisations assess privacy and security risks before introducing new technology into healthcare workflows.

Jo Salisbury said, “The AI conversation often starts with the application itself. Healthcare organisations also need to look underneath it. Where is the data coming from? Where does it go? Who has access to it? These questions are fundamental when organisations are dealing with information that patients expect to remain private.

“Good AI governance isn’t about slowing innovation down. It’s about making deliberate decisions on where AI belongs and putting appropriate safeguards around how it is used.”

AI Could Give Healthcare Professionals More Time With Patients

Patient trust involves more than protecting personal information. It also depends on the quality of care and the relationships patients build with healthcare professionals. Administrative responsibilities can consume a significant portion of a clinician’s working day, and AI-supported tools could reduce some of this workload. In turn, healthcare professionals may have more time to focus on patients rather than documentation and routine administrative processes.

However, faster processes do not automatically translate into better healthcare experiences. A system might reduce the time needed to complete a task without necessarily improving the interaction between a clinician and a patient. Healthcare organisations therefore need to assess whether AI reduces administrative distractions, supports meaningful communication and allows healthcare professionals to maintain the human connection that remains essential to patient care.

Jo Salisbury said, “AI doesn’t create empathy. What it can do is give people more space to provide it. If technology reduces the amount of time a clinician spends looking at a screen or completing administrative work, this can create more opportunity to listen, explain and connect with the patient in front of them.

“This is an important way to think about AI in healthcare. The goal shouldn’t simply be to automate more. Organisations should consider where technology genuinely improves the experience and where human judgement and connection remain essential.”

Responsible AI Governance Requires More Than Technology Teams

Healthcare organisations should evaluate AI applications based on their intended use, sensitivity and potential risks. Not every process requires automation, and different applications demand different levels of oversight. Introducing AI simply because the capability exists can overlook important questions about patient privacy, clinical workflows and whether the technology delivers meaningful improvements.

Effective AI governance also requires involvement from across the organisation rather than leaving decisions entirely to technology teams. Clinical leaders can assess whether an application supports healthcare workflows and patient needs, while privacy and cybersecurity teams can evaluate how systems handle sensitive information. Executive leaders must also consider the wider organisational implications of introducing AI into healthcare delivery, including how its use aligns with patient expectations.

Bringing these perspectives together helps organisations make informed decisions about where AI adds value and where human judgement remains essential. This approach also challenges the assumption that adopting more AI necessarily produces better outcomes. Healthcare providers need to consider the practical benefits of automation alongside privacy, security and patient experience rather than treating these issues as separate responsibilities.

Jo Salisbury said, “Healthcare organisations are still defining what responsible AI adoption looks like in practice. The answer won’t come from treating security, privacy and patient experience as separate conversations.

“Trust connects all three. Healthcare organisations that keep this principle at the centre of AI decisions can focus on using the technology where it adds genuine value while protecting the qualities that patients already expect from healthcare: privacy, judgement and human connection.”

Patient Trust Must Remain Central to Healthcare AI Decisions

AI offers healthcare organisations opportunities to improve efficiency, reduce administrative burdens and support patient care. However, these benefits depend on how organisations introduce and manage the technology. Protecting sensitive information requires clear visibility into data access, storage and third-party involvement, while improving patient experiences requires careful consideration of how technology affects interactions between clinicians and the people they treat.

The central challenge is not simply determining which healthcare tasks AI can perform. It is deciding where the technology provides genuine value while maintaining patient privacy, clinical judgement, and human connection. For healthcare organisations, trust must remain part of the decision-making process from the outset, not an issue addressed after deployment.