How Is AI Changing Healthcare In 2026?

In only a few short years, artificial intelligence (AI) has become a huge part of our lives. Nowhere is this more apparent than in the world of healthcare. As 70% of healthcare organisations report they are now using AI, and with the AI healthcare market expected to grow from US$18 billion to US$80 billion by 2036, it’s no longer a question of if AI will transform healthcare, but by how much.

As a patient, it’s important you know what to expect from AI in healthcare, because the next time you visit a doctor or medical professional you may encounter AI being used throughout your own healthcare experience.

In this article, we’ll look at some of the ways healthcare providers around the world are already integrating AI into the delivery of their services – from diagnosis to treatment, and even in the field of mental health.

Remember: this is only the beginning. By the time you finish reading this article, there may already be new AI developments making headlines. But until then, let’s jump right in.

How is AI helping to diagnose diseases?

Let’s start from the beginning. We’ve written before about how AI is becoming an essential part of the diagnostic process. In 2026, the use of AI in diagnostics is no longer science fiction, but an everyday reality for many healthcare providers around the world.

Right now, AI is already being deployed in the diagnosis of some of the most critical diseases including cancer, heart issues and neurological diseases. AI models have been trained to analyse vast data sets, inspect images from scans and create predictive algorithms to model future scenarios and potential outcomes. In some cases, researchers have found AI tools can greatly outperform human clinicians in terms of accuracy.

Like any new technology, some people are sceptical of AI – but the vast majority seem to be in favour of AI supporting healthcare. Research by Teladoc found 64% of patients in the US are supportive of medical professionals utilising AI, while 65% of doctors say they can see the long-term benefits of incorporating AI into their profession.

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How is AI used to give a diagnosis?

If you are undergoing a diagnosis for a major illness, it’s becoming increasingly likely AI will be involved at some stage of the process. Nuffield Trust found that around 3 in 10 GPs are already using AI to support diagnoses, while the Royal College of Radiologists in the UK reports that AI is utilised in as many as 54% of radiology departments.

That’s not to say that AI is handling the entire process. Rather, medical professionals tend to utilise AI to improve their own decision making. Doctors and clinicians are using AI to scan their initial data in search of anomalies. If any are found, it’s still up to a doctor to make a judgement on whether these are consistent with a disease.

In other words, it’s not AI making the diagnosis – it’s the doctor. But AI is handy for helping those doctors reach more accurate and informed decisions faster.

Can I use AI to diagnose myself?

In a word, no. While many tools exist that claim to be able to support you in making an independent self-diagnosis, AI is simply not yet capable of performing an accurate diagnosis independently.

A 2025 meta-analysis of AI diagnostic tools “reveal[ed] significant gaps in understanding the key areas of development, implementation, impact, and oversight of digital self-diagnosis tools.” There is also still a high risk of AI ‘hallucinating’ — meaning it will report false positives with great conviction.

For now, the only way to obtain an accurate diagnosis is to consult a medical professional, who will guide you through established procedures to make accurate decisions.

Worryingly, there are many people who have actually been discouraged from talking to their doctor after speaking to an AI chatbot. A study from King’s College London found that 15% of people had used AI to assess their symptoms instead of speaking to a doctor, and 10% had used AI in lieu of seeking mental health support.

On the other hand, many people have found AI tools to be useful in tracking their health and well-being, and identifying anomalous symptoms. Once spotted, these can then be referred to a doctor for a formal diagnosis. In the future, it’s likely that AI will help people to consult a doctor earlier, potentially leading to improved outcomes.

Are AI symptom checkers safe?

A number of dedicated AI symptom checkers exist online. These are often in the style of chatbots that will ask you questions much the same as a GP would. Based on your answers, these symptom checkers claim to be able to compile an accurate diagnosis for you.

However, independent reviews have found AI symptom checkers to be severely lacking in accuracy. One review, published in 2025, found that physicians achieved accuracy rates of up to 97%, while AI symptom checkers could only achieve accuracy rates of up to 54%.

The British Medical Journal has previously made the suggestion that AI symptom checkers could potentially lead to patient harm in cases where a mis-diagnosis is given.

So, while AI symptom checkers could help you to understand the potential risks associated with your symptoms, you should not rely on them to provide an accurate diagnosis.

AI symptom checkers can be a useful starting point, but they should never replace professional medical advice.

If you or someone else is experiencing severe symptoms, such as chest pain, difficulty breathing, signs of a stroke, severe bleeding, loss of consciousness, or any other medical emergency, seek immediate medical attention or contact your local emergency services.

How is AI being used in mental healthcare?

In much the same way as other healthcare professionals, many mental healthcare practitioners are using artificial intelligence to improve diagnostics, ease administrative burdens and improve the quality of their care.

Among the many use cases for AI in mental healthcare are its ability to:

Detect mental health disorders earlier
Provide personalised treatment plans
Act as an automated therapist

AI is also being used to train mental health professionals and assist in other time-consuming processes that take place behind the scenes.

The American Psychological Association found that 29% of mental health professionals are already using AI as part of their regular workflow.

Should I use an AI therapist?

Many people around the world are turning to ChatGPT and other AI-powered LLMs (Large Language Models) in lieu of visiting a therapist, psychologist or other mental health expert. Studies have found that as many as 37% of people in the UK have used an AI chatbot to support their mental health or well-being.

There are a growing number of AI-powered tools developed especially to provide mental health support. It’s estimated these tools have around 40 million monthly users worldwide.

Commentators have noted that, by turning to AI, these patients are easing the burden on overstretched mental healthcare services. They have also noted that some patients are more inclined to use AI because it bypasses the natural patient stigma associated with going to a real person.

However, commentators have also raised a number of issues with the proliferation of people turning to AI for mental healthcare. They note the lack of oversight and a regulatory framework to ensure AI is providing an adequate level of service and taking steps to protect patients, which a mental health professional would do instinctively.

They have also highlighted inaccuracies and biases in AI responses that have the potential to lead to patient harm, and the fact that AI does not respect patient confidentiality, meaning private mental health conversations may ‘leak’ into the public domain.

Worryingly, clinicians have noted an increasing number of psychosis cases, many of which can be linked to the use of AI. In some cases, suicidal patients have been convinced to kill themselves by AI chatbots.

Suffice to say, there is a big ethical debate around the use of AI in mental healthcare, with many practitioners arguing that the risks currently outweigh the benefits.

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How is AI being used in cancer treatment?

Perhaps one of the most exciting applications of artificial intelligence is its use in the field of cancer research and treatment. Advanced AI models are being deployed to crunch vast amounts of data from imaging, genomics and clinical research to accelerate research and support in early detection. This is already leading to the emergence of innovative diagnostic and therapeutic approaches, with the promise of even greater advances in the future.

One study by the University of Aberdeen found that breast cancer detection rates had improved 10% thanks to the implementation of AI in screening. Another study found improvements to be as high as 23% compared to only having a radiologist assess the scans.

Elsewhere, the American Journal of Managed Care has identified five ways AI is improving research and patient outcomes where cancer is concerned:

Keeping up with new research – researchers, clinicians and doctors spend an enormous amount of time keeping up to date with new advances in cancer care from around the world. AI makes it easier for them to find and digest this research, helping them learn faster and deliver improved care.
Imaging and pathology – by using AI to support their research, clinicians have seen improved rates of cancer identification and lower rates of missed signals. AI is helping them to detect cancer earlier and with greater accuracy.
Decision support and precision oncology – when it comes to treatment, clinicians are able to use data from AI to analyse their patients’ genomes in order to more accurately predict the kinds of treatment that will be effective. With less guesswork involved, treatment could be faster and more effective.
Matching patients to clinical trials – AI is helping to make clinical trials faster and more precise by removing the burden of manual review. This is especially apparent in the field of administration, where AI is helping to greatly accelerate onboarding and other tasks.
Patient tools – the final benefit mentioned is that AI is helping patients to access essential information (including in the form of symptom checkers). This is helping patients to seek timely treatment and guiding them through their treatment independently.

It may be too early to start talking about AI helping to discover a ‘cure’ for cancer. But early signals are promising, with clinicians and doctors seeing improvements across the board.

AI is helping researchers crunch, combine and analyse data in quantities that were not previously possible, improving our knowledge about cancer at a faster rate than ever before.

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How is AI improving healthcare access abroad?

The benefits of artificial intelligence are not localised to the Western world. All around the world, AI is helping to level the playing field in terms of access to healthcare. As an expat, you may stand to gain from AI advances in healthcare.

The key benefits of AI in healthcare globally will be in its ability to:

Help healthcare providers deliver faster, more efficient care by reducing administrative workloads and improving patient access
Ease pressure on crowded hospitals and clinics
Provide medical professionals around the world with access to cutting-edge tools and knowledge that helps to accelerate diagnoses, treatment and more

What hurdles will countries face?

Of course, some countries face a longer process to fully integrate AI into their healthcare systems.

1/ Data storage capacity

One major hurdle will be data storage capacity, which will be needed to harness the big data power of AI. The World Economic Forum points out that Africa contains 18% of the global population, yet holds only 1.3% of the global data storage capacity. Gaining access to AI advances in healthcare must begin with huge infrastructure improvements if every country hopes to benefit in the same way.

2/ Regulation

Another avenue of difficulty will be regulation. Right now, different countries are looking to apply different standards of regulation to AI, and these restrictions could end up impacting the health sector. Patient data is highly sensitive, so countries must manage a delicate balancing act to harness the power of AI without compromising the rights of their citizens.

3/ Data bias

The third and final issue on the horizon is data bias. Because existing health datasets have been widely trained on patient data in Western countries, the quality and availability of data in some parts of the world is severely lacking. This could lead to potential biases in which AI defaults to the model of Western patients, thus overlooking and ignoring diverse populations in other countries. Fixing this issue will involve a protracted effort to gather, store and process data more widely.

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What are the risks of AI in healthcare?

As with any big technological shift, there are risks associated with the AI revolution in healthcare. This is one of the key issues holding AI back – Teladoc Health write that more than half of medical professionals cite risk as a key source of apprehension when it comes to adopting AI at scale.

We’ve already covered some of the key risks associated with misdiagnosis, so let’s cover some of the other risks that have been identified.

Patient confidentiality

As a patient, you rely on your healthcare providers to maintain strict confidentiality with your medical records. In an era where new artificial intelligence products are being rapidly integrated into health systems around the world, there is a risk that your health data may be leaked or stolen.

Moreover, since AI requires the use of patient health data to enhance its learning, this risk may be heightened as research companies share and transfer information across AI platforms.

As we move forward, it’s important to consider the role AI plays in safeguarding, anonymising and encrypting patient data. Thankfully, technology companies are already making strides in this field. In fact, in this case, AI is being turned back on itself – with machine learning helping to improve the safety of patient records better than ever.

Healthcare fraud

AI has improved access to knowledge like never before. This will inevitably be a net benefit for doctors in the long term. But, at a time where AI is still finding its feet, it also opens the door to bad actors to take advantage of the system.

The medical community has already noted AI’s ability to produce fraudulent medical research, while medical insurers have noted a rising number of scams related to AI.

There are also more direct risks to patients. It’s not beyond our imagination to think of ordinary people posing as medical doctors with AI as their source of information, or companies releasing untested AI-powered medical products onto the market. One research firm has already noted the case of a pharmaceutical company posing as prescribing professionals to promote counterfeit medications online.

Over reliance on AI

The big question we must ask is: what will the world look like if AI becomes the primary source of our healthcare?

Will it open up a new world of innovation – or will we be inundated with so-called ‘slop’ throughout the healthcare world? The ethical dilemma incumbent with AI has been widely discussed in the medical world, but no firm consensus has yet been reached.

We may even need to ask ourselves: will AI replace doctors? We’ve already seen how a growing number of people are turning to AI in lieu of consulting mental health professionals. Is it possible that one day we will seek other forms of healthcare directly from an AI chatbot?

The medical community believes that scenario to be unlikely, saying instead that AI will become a powerful tool in every doctor’s arsenal without undermining their profession. Indeed, we may start to see a proliferation of virtual healthcare services combining the expertise of doctors with the information-gathering and data-processing power of AI, leading to faster service and improved outcomes.

But as with all things, only time will tell.

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How Is AI Changing Healthcare In 2026?

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