Demis Hassabis, head of Google’s artificial intelligence division, has suggested the current AI revolution could be ten times larger and ten times faster than previous industrial revolutions. If this is true, healthcare will inevitably be affected: AI already analyzes medical images, processes research findings, reduces administrative burdens, accelerates drug development and predicts certain risks. McKinsey estimates that generative AI could create up to $370 billion in annual value for healthcare and pharmaceuticals globally.
Yet technology alone is not a panacea. An algorithm can detect an abnormality, but that detection does not by itself make a patient healthier; living longer does not automatically mean living better. The decisive question for the coming decade is therefore not only what AI can do, but what professional processes and systems we build around it.
Longer life—and the rise of chronic conditions
Medical advances over recent decades have increased life expectancy, while the prevalence of many comorbidities—especially musculoskeletal disorders—has risen sharply. Low back pain remains a leading cause of work incapacity worldwide. Sedentary lifestyles, obesity and aging populations place growing strain on health systems.
In Hungary, hundreds of thousands of people live with chronic musculoskeletal complaints that degrade quality of life and cause economic loss. AI can assist here: it can support early risk assessment, enable prevention, personalize rehabilitation and surface relevant correlations more quickly. But AI will not do the physiotherapy for patients, rebuild muscle strength for them, or create healthy habits on their behalf.
AI is not a substitute for clinical systems
Public debate often reduces to whether AI will replace doctors or therapists, but that misses the key issue. AI can produce strong clinical recommendations; healthcare requires more than correct outputs. Decision logic must be transparent, auditable and traceable. For diagnoses or rehab plans, it matters not only what the answer is but what data, professional rules and inferential paths led to it.
The future is about collaboration between AI and standardized professional systems. AI will not replace well-designed care models; instead, it can make them more consistent, measurable and scalable. Providers that first organize their processes and then layer AI on top will gain the most.
Breakthroughs will likely happen in the background
Many expect the most dramatic changes to appear in patient rooms, but the real revolution may take place in background processes. When an organisation’s workflows are well-defined, documented and based on unified professional standards, AI can flag documentation gaps, highlight deviations and even nudge compliance with standards while records are being created. This is not about limiting professional autonomy but ensuring that patients receive the same high-quality care each time. Although less visible than an AI-made diagnosis, predictable operation, uniform documentation and standardized processes can have greater business and clinical impact.
Data assets will be the key competitive advantage
An AI system is only as reliable as the data it uses. In healthcare, patient data are both highly valuable and tightly protected. Compliance with the GDPR is a baseline, but it is equally crucial to know the provenance, authenticity and integrity of the data used by AI: what knowledge base it draws on, which data were used, how trustworthy they are and whether their origin and any modifications are demonstrable.
In the coming years one of the most important competitive advantages will be a validated, well-structured and trustworthy data asset—not the algorithm alone. Technologies that ensure provable data integrity and traceability may play a key role. AI becomes more reliable not merely because models improve, but because the data feeding them improve.
Therapists’ roles and patient behaviour will change
AI will also reshape patient expectations and behaviour. Increasingly—especially among younger generations—patients arrive with AI-generated exercise plans or rehabilitation suggestions. This creates opportunities and responsibilities for therapists. Therapists must evaluate whether AI recommendations suit an individual’s condition, what assumptions underlie them, which information is missing and where adjustments are needed.
A new skill set gains importance: communicating effectively with AI. Just as a clinician needs accurate information from a patient to form a reliable diagnosis, AI is useful only to the extent we can describe our condition, goals and constraints precisely. Therapists may expand their role to teach patients how to use AI consciously and critically.
Humans remain central
The next decade of healthcare will not be about AI alone but about human–technology cooperation. Algorithms will become faster, diagnostics more accurate and administration simpler, but these advances do not automatically create more empathy, greater trust or stronger motivation to recover. The aim of healthcare is not to maximize the amount of AI used but to maximize years lived in good health. AI’s true value lies in improving the system in which people treat people, not in replacing those people.
