Patients are waiting months to see specialists, while 77% of healthcare workers waste time searching for data, according to the Philips Future Health Index 2025 report. 84% of respondents believe that AI can automate repetitive tasks, and 82% say that AI and predictive analytics will enable more effective treatment thanks to accelerated diagnosis.
In the 16 countries surveyed, 73% of patients waited in line to see a specialist, with an average wait time of 70 days. In some countries, the average wait time reached up to 131 days. In Canada and Spain, it was even four months or more. Long wait times significantly reduce the effectiveness of treatment; the condition of patients waiting for an appointment often worsens. Due to delays, as many as 36% of cardiology patients who could be treated in an outpatient clinic end up being hospitalized.
Meanwhile, healthcare workers are working at the edge of their endurance, paradoxically, because a vast portion of their working time is consumed by system inefficiencies and bureaucracy. A total of 77% report they waste valuable time (on average, 45 minutes per day) due to unavailable or incomplete patient data. Over a year, this amounts to four weeks of work lost due to an inefficient system.
The second issue is the excess of administrative duties. 35% of healthcare workers report that they are spending ever more time on paperwork, leaving them with less time for patient care. This often leads to burnout and chronic frustration.
Can AI eliminate inefficiencies?
How can these problems be solved, given that previous reforms and digitization efforts have failed? Healthcare workers agree that a broad application of AI might be the solution. 84% of respondents believe AI can automate repetitive tasks, 78% think it can help serve more patients, and 76% say it will reduce waiting times.
Eight out of ten doctors are convinced that predictive analytics will reduce the gap between the onset of symptoms and the start of treatment, and three out of four hope that new technologies will reduce the number of hospital admissions.
The study reveals that doctors anticipate AI to streamline workflows, including optimizing surgery schedules, triaging patients, and consolidating data from various sources, thereby reducing the need for manual verification of test results or review of electronic medical records.
Another benefit of AI is enhancing the skills of less experienced staff, which is particularly important in rural areas that often struggle with staffing shortages. Specialist doctors hope that AI can improve diagnostic precision, especially in high-risk specialties such as cardiology, where thorough data analysis and early disease detection are crucial.
There are also financial savings. Data from the US suggests that widespread use of AI could save $200–360 billion annually, which translates to about 5–10% of healthcare spending. This figure includes reductions in hospital readmissions and unnecessary procedures, which are currently performed due to a lack of data and the automation of administrative tasks.
Doctors are optimistic, patients are cautious
As many as 79% of healthcare workers believe that AI will improve patient outcomes. Patients do not share this enthusiasm – only 59% of them agree.
Patients are used to going to a human doctor they have known for years and thus are very skeptical of AI. Although they accept the use of AI in administrative tasks such as scheduling or registration, their trust drops sharply when AI is used in the doctor's office, for example, to create medical documentation, triage, or support diagnosis. Patients are afraid that AI will eventually replace their doctor (52% of respondents). These concerns are consistent across countries and age groups. Paradoxically, the most cautious patients are those who know the most about AI.
Responsibility, trust biggest barriers to AI implementation
Healthcare professionals’ optimism decreases when it comes to the details of using AI in daily clinical practice. Only 38% believe that AI tools are designed with their work in mind. A major obstacle to implementing AI is poor integration with existing workflows. As a result, technological solutions often hinder rather than help.
Furthermore, 76% of doctors fear legal liability in the event of an AI system error, and 61% are concerned about algorithmic bias that could deepen inequalities in healthcare. The report’s authors also point out arguments that can help build patient trust in AI. The most persuasive include improved health outcomes, fewer medical errors, faster access to doctors, and more time for conversations with doctors.
Conclusion: patients are not opposed to artificial intelligence, but somewhat cautious and pragmatic. If AI brings them tangible benefits and is not a threat to the human aspect of care, they are open to its use. Who should educate them about AI? The answer is simple: doctors. 86% of patients trust information about the use of artificial intelligence in treatment when it comes from doctors.
AI implementation plan
The summary of the Future Health Index 2025 report includes five key recommendations for implementing artificial intelligence in healthcare in a way that benefits both doctors and patients, and builds trust in AI technology:
- Put people first in AI design. AI tools must be designed based on the clinical processes performed in healthcare facilities and patient needs, not on abstract technical ideals.
- Strengthen human-AI collaboration. AI should assist, support, and expand the clinical knowledge of healthcare workers, not replace them. This requires AI-focused training programs.
- Prove the effectiveness and safety of AI before implementation. Every AI solution must be supported by scientific evidence proving that it works reliably across diverse patient populations and is not biased.
- Ensure legal clarity in AI usage. Without appropriate regulations that ensure safety in AI usage, doctors will be reluctant to adopt it. Safe implementation of AI should be based on so-called regulatory sandboxes. In addition to national regulations, global harmonization is also necessary.
- AI development requires cross-sector partnerships. Effective AI solutions do not emerge in silos, but rather result from collaboration among doctors, medical facilities, technology providers, regulators, and patients.
The report highlights the significant hope that is placed in AI by the healthcare sector. This is a result of the sector’s unsolved problems, rising costs, unequal access to care, and administrative load on healthcare professionals. All these have been leading to fatigue and a search for a “quick fix”.
This decisive vote of confidence in AI is both a major opportunity and a significant responsibility. Delaying AI implementation means ignoring the growing problems in healthcare that negatively affect the health of both patients and frontline workers, such as doctors and nurses.
The Philips Future Health Index 2025 is based on two large-scale, online surveys conducted between December 2024 and April 2025 across 16 countries. The study includes responses from 1,926 healthcare professionals and 16,144 patients, collected via Computer-Assisted Web Interviewing (CAWI) and translated into local languages as needed. Healthcare professionals surveyed represented a diverse mix of doctors, nurses, and physician assistants across various specialties and sectors, while patient respondents were demographically representative, with 99% having seen a doctor within the past two years. The data was statistically weighted to ensure global representation and comparability, and results are reported with a 95% confidence level and clearly defined margins of error.
