The future of healthcare: Clinicians predict technology driven changes by 2027

As we move into 2026 and look toward 2027, clinicians around the world are anticipating how artificial intelligence (AI) will redefine patient care, diagnosis, and the broader health ecosystem. Drawing on insights from Elsevier’s global survey of more than 2,000 doctors and nurses, we explore the key AI-driven trends shaping the future of healthcare.

AI could be at the heart of diagnosis

Clinicians see AI becoming an essential partner in diagnosis. Nearly two-thirds of those surveyed believe that by 2027, AI will play a routine role in identifying a wide range of conditions. This evolution promises to enhance accuracy, reduce human error, and enable earlier, more effective interventions—ultimately improving outcomes for patients.

AI-powered systems are also expected to relieve pressure on healthcare professionals by analyzing complex data sets—from imaging scans to genomic profiles—more quickly and precisely than ever before. As these tools mature, they will support not just clinical decision-making, but also help manage growing administrative demands. According to the report:

• 56% of clinicians think that AI will analyze all medical images to identify abnormalities in the next two to three years.

• 70% of clinicians predict that AI will save them time in the next two to three years.

• 54% of clinicians believe AI will enable them to make more accurate diagnoses.

Self-diagnosis will continue to rise

Clinicians also predict a continued rise in patient self-diagnosis. With AI-driven symptom checkers and digital health platforms, patients are arriving at appointments more informed—and sometimes misinformed—than before. While this brings challenges, it also creates opportunities for more collaborative, informed care.

Many clinicians see value in integrating AI tools that guide patients toward credible information and facilitate shared decision-making. When used responsibly, these tools can strengthen the patient-clinician relationship and improve engagement in long-term care.

• 38% of clinicians think that most patients will self-diagnose with AI tools available online rather than see a clinician in the next two to three years.

• 59% of clinicians say medical misinformation is hindering patient compliance with recommended treatments.

• 22% of clinicians whose care is impacted by lack of time report that patients have numerous questions, with this rising to 34% in North America.

AI will enable an increase in personalized and home-centered care

AI is accelerating the shift toward more personalized and home-centered care. By 2027, clinicians expect that treatment plans will increasingly reflect an individual’s genetic, lifestyle, and environmental factors—making personalized medicine the norm rather than the exception.

Meanwhile, the boundary between hospital and home is blurring. Remote monitoring, telehealth, and AI-enabled health management platforms are allowing patients to receive continuous, high-quality care wherever they are. This approach not only enhances patient comfort but also helps health systems optimize resources.

• 40% of clinicians believe most of their patients will receive personalized treatment plans generated by AI in the future.

• 31% of clinicians believe most healthcare will be delivered in the patient’s home.

• 51% of clinicians agree that hospital stays will be shorter, and 41% expect hospitalization rates to be lower in the near future.

Clinicians will continue to require a foundation of trust

As AI becomes more integrated into clinical practice, healthcare professionals stress the need for continuous training, strong data governance, and ethical oversight. Collaboration between clinicians and technology partners will be vital to building trust and ensuring that AI serves patients safely and effectively.

• 68% of clinicians say that automatically citing references would increase their trust in clinical-specific AI tools.

• Only 40% of clinicians globally believe AI tools developed to support clinical decision-making are trustworthy.

• 65% of clinicians want AI tools to be trained on high-quality peer-reviewed content to increase trust.