AI trends in medicine you will see in 2026

AI has found a new ally in medicine. As a new McKinsey report points out, 85% of medical leaders have already taken a step forward in adopting this technology, and many have already implemented it. This confirms that current AI trends in medicine are driving the sector towards modular platforms that enable data sharing, process automation and optimised diagnosis and treatment.

For this reason, today we are telling you how AI in medicine can become a safe bet for gaining agility, optimising processes, reducing times and improving the quality of care that patients receive.

What is the current situation of AI in the healthcare sector?

In the first quarter of last year, in March 2025, McKinsey published a study reflecting how generative AI is being integrated into the healthcare sector. Although the survey focused on 150 US healthcare leaders in subsectors and is based on similar samples of 100 leaders from the first and second quarters of 2024 and the fourth quarter of 2023, the advances are still obvious.

The survey, conducted in the fourth quarter of 2024, found that 85% of respondents were exploring or had already adopted certain generative AI capabilities. Most of them responded that they were in the implementation stage, not the proof-of-concept stage, which would have a faster positive impact on their organisations. However, 15% reported that they had not yet begun to develop proof-of-concepts, which, compared to the vast majority, could delay their operations.

But why all the fuss? Well, in practice, generative AI can bring great value in areas that can significantly improve the quality of patient care, as well as streamline operations to generate cost savings, improve administrative efficiency and clinical productivity.

Current applications and trends in AI in medicine

In this landscape of digital transformation and innovation, AI trends in medicine can be a very useful tool in the healthcare sector. In practice, there are already numerous cases of implementation, which are expected to continue growing in the future:

Image-assisted diagnosis

AI in medicine already plays a very important role in diagnostic imaging. In hospitals, for example, it could become an extra aid for healthcare workers by analysing X-rays, MRIs and CT scans with great accuracy. In fact, experts point out that Artificial Intelligence is capable of quickly detecting things that the human eye cannot see (especially in the diagnosis of certain types of cancer):

“This type of algorithm has a triple impact: for patients, it improves the quality of care received and reduces waiting times; for professionals, it allows them to prioritise the most high-risk cases, helps save time in report preparation and improves efficiency; and for organisations, it improves care flows and optimises times,” Alfonso Martínez, managing director of Incepto for Iberia and Latin America and spokesperson for Incepto in Spain (20minutos).

Accelerated medication development

Did you know that the entire process of developing a drug can take between 10 and 12 years? This is according to a report published in June 2025 by FarmaIndustria. Technically speaking, developing medicine is a very long process consisting of different phases: discovery and development; preclinical research; clinical trials in humans; regulatory review and approval; and post-marketing monitoring. However, the general population is unaware of most of these stages.

Applied in this sense, the latest trends in AI in medicine can accelerate the development of new drugs, mainly through two avenues:

• Through the creation of new drug designs
• Through the discovery of promising new combinations

Innovation in disease prevention and management

According to McKinsey, in the future, generative AI could anticipate outbreaks, identify high-risk patients, and predict healthcare system needs, as well as facilitate resource planning and forecasting. Along these lines, in October 2025 it was announced that work carried out by researchers at the European Molecular Biology Laboratory (EMBL) had developed a generative artificial intelligence model that, based on individual medical and lifestyle data, can predict the risk of suffering from more than a thousand diseases in the long term.

Automation of repetitive clinical tasks

In hospital management, AI can be a decisive factor in optimising resources and helping to distribute them more efficiently, reducing waiting times, predicting patient influx and planning operating theatres or healthcare workers’ shifts. It can also be very useful for managing medical supply inventory, ensuring that critical medicines and equipment are always in stock.

Applied to administrative tasks, it can automate processes such as billing, medical record management, and report generation.

However, for these AI trends in medicine to be effective, they must be complemented by another set of digital tools such as electronic signatures. This digital solution in the healthcare sector allows for the automation of the informed consent cycle, medical records, prescription signing, and employment contract management, eliminating paper and ensuring that processes are as fast as medical diagnoses.

Advantages of AI applied to hospitals and the healthcare sector

The integration of Artificial Intelligence in medicine or applied to the clinical environment not only optimises resource management, but also completely redefines the patient experience. Below, we detail the key benefits that are transforming the operations of modern healthcare centres:

• Improving patients’ quality of life. AI can make daily life easier and increase patients’ independence. Even virtual assistants or robots can provide emotional and social support, reducing loneliness and social isolation.
  Accurate and faster diagnoses. Deep learning algorithms can analyse medical images in a matter of seconds, detecting subtle patterns that might otherwise go unnoticed. This ability makes it possible to identify pathologies such as tumours or rare diseases at an early stage.
• Accurate and faster diagnoses. Deep learning algorithms can analyse medical images in a matter of seconds, detecting subtle patterns that might otherwise go unnoticed. This ability makes it possible to identify pathologies such as tumours or rare diseases at an early stage.
• It alleviates the workload of healthcare professionals. By automating routine tasks, healthcare professionals can devote more time to patient care, thereby improving its quality.
• Optimisation of research times. In laboratories, AI can help significantly accelerate the development of new drugs and vaccines by simulating how chemical compounds act at the molecular level, reducing years of experimentation. It also facilitates the analysis of large volumes of data in clinical trials, allowing the most effective therapies to be identified.
• Greater control through electronic devices. When it comes to monitoring individual patients, AI-equipped devices could assess and monitor patients’ vital signs at all times, recording parameters such as blood pressure, heart rate and glucose levels. Depending on the levels detected, they could send real-time alerts to doctors if problems are observed.

The future of AI in medicine and hospitals

The different use cases and advantages mentioned are just a few examples of how AI trends in medicine can have a positive impact. From accelerated drug development to innovation in disease prevention and management, to resource optimisation, easier scheduling of healthcare staff shifts and improved quality of patient care.

In short, AI in medicine is not a futuristic promise, but the current driver of more efficient and accurate healthcare. By freeing professionals from repetitive tasks and equipping them with advanced analysis tools, technology allows them to reclaim the value of time.

Is your healthcare centre ready for the next level of efficiency? Optimise your processes by integrating AI and electronic signature solutions to reduce bureaucracy and focus your efforts on what really matters: patient health.