From intention to execution: how to use AI in hospital management

Everyone knows that interest in artificial intelligence (AI) in healthcare has never been more evident, but I want to propose a reflection on how it is actually used. I had some perceptions based on my professional experience, but now a survey confirms what might previously have been a partial or personal view: AI will only move beyond experimentation when it becomes a priority for organizations.

Making it official in hospitals depends on technological and organizational integration. It requires specialized engineers and professionals who master hospital operations to come together. Without harmony between technology and care practice, AI use tends to remain ad hoc and informal, as the survey by Instituto Opinion Box reveals: more than 90% of AI applications in hospital management happen unofficially.

Internalizing this transformation means aligning areas that have always operated with different priorities. It requires governance, a review of workflows, the creation of protocols, the definition of responsibilities and investment in training. It is a movement that demands scarce skills, especially professionals who can move between data engineering, building AI agents to automate tasks and hospital operations.

In this scenario, structured implementation models gain relevance. By integrating AI and hospital knowledge in a coordinated way, these models make feasible what would be complex for institutions to achieve with their own resources.

There is no magic formula, but there is method. Some are well known, such as putting professionals with different skills in the same room every day, drawing on the whiteboard and debating ways to include AI not as an experiment, but as the new official way to make the hospital more efficient. The results are starting to show. In tests conducted at more than 50 hospitals, the structured application of artificial intelligence showed the potential to recover between 5% and 8% of revenue — amounts lost to administrative failures, billing inconsistencies or operational inefficiency.

Once reintegrated, these resources go on to fund more beds, modernized equipment and stronger teams. It is about restoring financial efficiency to healthcare to expand its capacity to care for people and save lives. That is when AI truly creates value and brings benefits to those who need care.