More than ever, it’s critical to pay close attention to the real-world outcomes that AI is actually delivering for clinicians, patients, and leaders of healthcare organizations. The 2026 Future Ready Healthcare survey report delves into the current value that doctors, nurses, and their patients are experiencing because of AI, and examines areas where more can be done with the help of AI to enhance the overall care experience. It also exposes the simple fact that while AI is showing up everywhere in healthcare, trust is struggling to keep pace.
Below are some of the key findings.
Understanding how patients, nurses, and doctors are using AI
AI use is increasingly becoming part of patients’ and clinicians’ daily experience, and this steady adoption is transforming the care experience. Some 52% of patients surveyed say they use AI to research health conditions or diagnoses, and 54% say they use these same tools to look up potential side effects or drug interactions. This always-on access to medical information is creating a new dynamic between patients, doctors, and nurses. In fact, 60% of clinicians say they are now spending appointment time reviewing and discussing AI-generated health information that their patients bring with them. This trend is helping to spur more dialogue around conditions and treatment options, and 70% of patients and clinicians agree that AI is enabling better patient health literacy and engagement.
Not surprisingly, both doctors and nurses are using AI more themselves, with the majority leveraging these tools for high-burden but low-risk activities that enhance their productivity. For instance, 54% of doctors say they currently use AI to summarize medical literature, and 49% say they use it for medical literature-based discovery. This underscores the vital importance of clinical research integrity and validation—in short, the information generated has to be right. Similarly, 43% of nurses say they are using AI tools to summarize medical literature or analyze data, and 41% are using AI to generate patient education materials. This illustrates a subtle, but important shift in the care experience: clinicians are using AI-derived clinical literature summaries and explanations to enhance their patient conversations.
The impact of AI in healthcare and the widening trust gap
While the ability of AI to surface information and summarize content is opening new and exciting doors to address burnout and enhance the patient-clinician relationship, it is also introducing some complicating factors.
A recent study published in Nature Medicine found that ChatGPT under-triaged about half of health care emergencies in a test performed by researchers. Misinformation in health-related AI searches can be extremely dangerous and, despite 69% of patients saying they are concerned about AI hallucinations, 74% are still extremely or somewhat confident that the answers they get to their health questions from general-purpose LLMs are accurate. Interestingly, despite their own confidence in the AI-generated health answers they receive to their queries, 78% of patients expect that their doctors are validating any AI-derived information against other sources.
Clinicians, on the other hand, are well aware of the potential risks of bias and hallucination when it comes to AI. More than half of doctors and nurses agree that AI tools for clinical use should be built by a trusted medical resource, not a tech company; and 77% say they “always” or “often” validate any AI-generated health information. This is an important finding as the use of Shadow AI tools in healthcare is on the rise, some of which may use questionable data, outdated content, or hallucinate. In fact, when it comes to AI, 92% of doctors and 90% of nurses believe it is “very important” or “somewhat important” to have the sources and AI systems used to generate clinical content validated by a human expert-in-the-loop.
AI trained on trusted sources will bring the best return on investment
As clinician burnout levels remain high, patient volumes continue to rise, and financial pressures deepen, healthcare systems can’t afford to wait on the sidelines. The continued investment in AI solutions is a leading indicator that health organizations are looking for immediate relief with tangible returns on their investments. In fact, 90% of physicians and nurses say that the implementation of technology to enhance efficiency is a top trend they anticipate impacting their organizations over the next three years. This is followed by technology that enhances professional development and clinical training, and AI that reduces time spent on EHR-related tasks.
It’s clear that clinical-grade AI, when pointed at specific high-burden/low-risk use cases, is having a positive impact in saving time, easing workloads, and helping clinicians reconnect with what matters most: their patients. But it’s also clear that trust is fragile. When AI lacks transparency, reliable sourcing, or proper oversight, the risks are too high to ignore. And if clinicians are constantly needing to recheck AI outputs and validate them against other sources, is it really an effective productivity tool?
The opportunity ahead isn’t about chasing the next shiny AI application. It’s about how healthcare organizations thoughtfully adopt and responsibly deploy AI to assist with specific, well-defined use cases. This includes understanding where and how clinicians and patients want to use AI in the clinical setting and then ensuring it meets the standards of clinical rigor and integrity. Leaders who prioritize AI trained on trusted sources, with human oversight, and seamless workflow integration will be best positioned to see meaningful returns, both for their clinical teams and the patients they serve. At a moment when access to care and system sustainability are under real threat, using trusted AI to support better care outcomes is one of the most important decisions healthcare leaders can make.