AI is already transforming healthcare. But who trains those who have to use it?
June 18, 2026
The data speak clearly: artificial intelligence saves clinicians the equivalent of 16 working days a year. Half of health professionals say they have more capacity to attend to patients. 39% have already seen AI identify or prevent potential medical errors at least three times in the last three months.
Impressive results. And yet, there is a growing problem that threatens to make them unsustainable.
The Philips Future Health Index 2026, the largest global survey in its field, with more than 2,000 health professionals and 20,000 patients across 10 countries, reveals a paradox we cannot ignore: 70% of professionals consider that AI training at their workplace is inadequate, inconsistent or outright non-existent.
You read that right. Seven out of ten clinicians use AI tools without the training needed to do so safely and effectively.
Adoption is accelerating. Training lags behind.
Two thirds of professionals (65%) have increased their use of AI tools at work. At the same time, nine out of ten (90%) believe there must always be a human in the process, and 86% argue that all AI outputs require human oversight.
This is not a contradiction. It is a wake-up call. Health professionals are not rejecting AI. They are adopting it with pragmatism and a critical mind. But they are demanding something fundamental: to be trained to exercise their judgment over it. Not to replace the technology, but to govern it.
Training is not an add-on. It is a condition.
When we deploy AI in clinical settings without adequate training, we are not accelerating digital transformation: we are creating systemic risks. Human oversight, which nearly all professionals demand, cannot be effective if professionals do not know exactly what they are overseeing.
Health organizations that want to tap the real potential of AI, fewer errors, more clinical time, less stress for professionals, better care for patients, must invest in continuous, contextualized and practical training. Not generic courses. Training anchored in the reality of each service, each role, each workflow.
The 16 days saved per clinician per year are not achieved by installing a tool. They are achieved when people know how to use it, question it and improve it.
At InnoHealth, this is one of our most urgent concerns.
We believe that digital transformation in health is only sustainable if it is accompanied by a transformation in people’s competencies. Deploying technology is not enough: we must build critical capacity, practical knowledge and professional confidence to navigate it.
That is why we work actively on AI training programmes for health professionals: designed from clinical reality, action-oriented and centred on human judgment as a non-negotiable element.
If you share this concern, let’s talk. The gap between adoption and training does not close on its own, and with each passing day the risks grow. Get in touch with us or leave a comment. Let’s build together the capacity the system needs.
Source: Philips Future Health Index 2026 — survey of 2,011 healthcare professionals in 10 countries
