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Artificial intelligence in healthcare, hospitals bid to lead the transformation

AI as a tool to optimise the National Health Service as long as there are trained professionals and equal access guarantees for citizens: the proposals and selection of best practices of the Federation of Healthcare and Hospital Companies

by Barbara Gobbi

14 May 2026

5' min read

Translated by AI

Versione italiana

5' min read

Translated by AI

Versione italiana

Artificial Intelligence as a consolidated reality, if not yet in the daily life of all companies and operators, certainly in the national strategies that are being implemented starting from experiments and best practices on the ground. Taking stock of this are the health and hospital companies themselves that are members of Fiaso, the Federation that last June in Syracuse launched a path to accompany the entry of artificial intelligence towards concrete, safe and sustainable applications for the National Health Service. And which in Rome completed its itinerant cycle of meetings and focuses with the Forum 'Next Health 2026 - AI for Health: from vision to reality', where the six experiences selected in the 'AI for Health' Call4Ideas were also awarded. From Nuoro and Palermo to Milan and Verbania, passing through Florence, projects dedicated to the concrete application of artificial intelligence in the National Health Service's healthcare and hospital companies.

A useful tool

'Artificial intelligence is not a technological shortcut, nor an abstract promise: it is a tool that, if guided with public vision, can help us to concretely improve healthcare,' stressed Fiaso President Giuseppe Quintavalle. Precisely because these tools are powerful, we need solid governance. Technology,' he added, 'does not replace the human being and does not take the place of the care relationship. With 'Next Health' Fiaso wants to help guide this evolution: selecting effective solutions, measuring their impact, and transforming artificial intelligence into public value'.

Lead the transformation

AI applied to healthcare is already today the lever that is radically changing the way in which services are planned, the patient's path is governed, professionals are supported, and the time of treatment is improved," warned Alessio Butti, Undersecretary to the Presidency of the Council of Ministers with responsibility for Innovation, in his speech to the Fiaso Forum. The point then is how to guide this transformation with responsibility, vision, and concreteness, and it is on this terrain that we have been working since the beginning of the legislature, focusing on three strategic axes: the development of the Electronic Health Record, telemedicine, and experiments with AI, which is a transversal guideline to the first two. The challenge today is to transform the experiments into a system,' he added, 'to move from isolated projects to a new culture of healthcare governance, making technological and organisational innovation walk together. A decisive part of the quality of our health service in the coming years will be played out in this field, and it will be important to build together a healthcare in which technology does not replace the care relationship but makes it stronger,' he concluded

Reducing inequalities

For Health Minister Orazio Schillaci, 'we must move from healthcare that manages illness to healthcare that is proactive, that builds health, with the citizen as an informed partner and not as a passive user'. And in this perspective, he explained, 'artificial intelligence can help us precisely to optimise processes, to make better use of resources, to have a better organisation and, very importantly, also to make our entire healthcare system more sustainable. But in this perspective, it is crucial to ensure fair access to technologies, to reduce territorial gaps, and to encourage the homogeneous spread of innovation throughout Italy. This is a decisive aspect: without fairness there can be no real progress'.

Improving the quality of life

'Alongside the opportunities offered by artificial intelligence,' the Health Minister stressed, 'there are also important challenges, starting with the protection of privacy and data security. This is why it is essential to build clear rules and governance capable of ensuring the safe, ethical and responsible use of new technologies, in the interests of citizens and the quality of our National Health Service. This is the task of the institutions: to transform the potential of innovation into concrete tools capable of improving the quality of life of all citizens'.

Training the operators

Still on the table is the issue of training doctors and health workers on technology and Ia, and the National Recovery and Resilience Plan had moved on this. 'Part of the resources of the NRP,' he explained, 'has been earmarked precisely for this objective. There are more than 225,000 NHS workers involved in the training courses and to these are added almost 10,000 general practitioners'. This is a necessary step because technological innovation "must always be at the service of the skills and responsibilities of healthcare professionals without ever replacing their role," Schillaci warned. "In this transformation process, we must therefore continue to invest in the training of healthcare workers so that they have the necessary skills to make the best use of new technologies

The 6 prizewinners

"Next Health 2026" represents the most advanced point of the path started by Fiaso in June 2025 with the "Logos & Téchne" forum in Syracuse and continued in Milan with the acceleration and selection phase of the projects developed within two national calls promoted with PwC Italia, P4B and Datapizza: the Call4Acceleration "AI for Patient Journey Innovation", addressed to start-ups and innovative companies, and the Call4Ideas "AI for Health", addressed to public health member companies.

Six winners of the 'Call4Ideas', awarded in Rome by Fiaso out of 48 applications from start-ups and 68 project proposals from healthcare companies. Projects born in health care and hospital companies, identified for their innovativeness, soundness and replicability, which will be developed, tested and transformed into useful models, prototypes, for the National Health Service.

- ARNAS OSPEDALI CIVICO DI CRISTINA BENFRATELLI PALERMO - Advanced communication and reduced operational ergonomics. An integrated platform with information systems in the emergency department to translate clinical data into clear and empathetic updates for caregivers, reducing the information burden on healthcare personnel, the stress of family members and the risk of conflict in emergency areas.

- ASST VALTELLINA E ALTO LARIO - Valtellina Data Lab: Prescriptive Appropriateness, Therapeutic Adherence and AI Telephone Assistant. A clinical governance model that uses data from the Assisted Data Bank to improve prescriptive appropriateness, therapeutic adherence and taking care of chronic patients. The project also includes a 24-hour multilingual AI telephone assistant.

- COQ, OMEGNA QUADRANT ORTHOPAEDIC CENTRE (VERBANIA) - ASL VCO. BI and machine learning for efficient scheduling of operating theatres. A system that integrates business intelligence and machine learning to predict surgical times, optimise the use of operating theatres, reduce downtime and increase the number of surgeries that can be scheduled.

- ASST GRANDE OSPEDALE METROPOLITANO MILANO NIGUARDA - Niguarda SmartCare. A single hospital app, powered by artificial intelligence, to centralise digital services, personalised information, bookings and communications with the facility, simplifying access for patients and carers.

- ASSL 3 DI NUORO - HealthFlow: redesigning healthcare logistics efficiency with AI. A solution for the dynamic and predictive management of waiting lists and outpatient and surgical resources, with the aim of saturating available slots, reducing no-shows and cancellations, and synchronising surgical activity with bed availability.

- AOU CAREGGI FLORENCE -Intelligent hospital inventory management, A platform that applies predictive, prescriptive and generative AI to departmental inventory management, forecasting requirements, suggesting orders, monitoring deadlines and reducing waste and stock-outs.