PRECISION-AI: Chile's 5-billion-peso bet on AI oncology, and why the real challenge is clinical adoption

By Universidad de Chile · July 8, 2026.

Universidad de Chile and Universidad del Desarrollo have presented PRECISION-AI, a technology program awarded by Corfo with 5 billion Chilean pesos for five years of execution, aimed at developing artificial intelligence solutions that help prevent, diagnose, treat and forecast cancer. The project is co-directed by Dr. Arnaldo Marín, of the Department of Basic Clinical Oncology at the Faculty of Medicine of U. de Chile, together with Dr. Ricardo Armisén on behalf of UDD, and it involves the Hospital Clínico Universidad de Chile, the Hospital del Salvador and a network that brings together public, private and international institutions, including the backing of MIT and the London AI Centre for Value-Based Healthcare. One of its most relevant components is the construction of a federated, secure and ethically designed data infrastructure, conceived to train models without exposing patient privacy, and with the aim of later becoming available to the entire national and international ecosystem.

The context that justifies the investment is harsh: cancer is the second leading cause of death in the world and the first in Chile, with nearly 60,000 new cases a year and some 30,000 deaths, according to figures cited by UDD rector Federico Valdés at the presentation. The Minister of Health, May Chomalí, offered a figure that, broadly speaking, says more about the sector than the funding amount does: of the six technology programs that Corfo awarded in the AI-for-Chilean-industry call, three went to healthcare. That confirms that precision oncology —cross-referencing genomics, imaging and clinical data with AI models to tailor diagnosis and treatment to each patient— has become the terrain where governments and academia around the world are concentrating their bets, because it is where the return in lives is most tangible and where basic science already has decades of progress waiting for a computing layer to make it scalable.

That said, it is worth being honest about what this announcement is and what it is not yet. PRECISION-AI is, at this stage, a governance and funding framework to "organize and articulate" —in Dr. Marín's own words— research projects that already exist, not a clinical product ready to be used in a hospital. And Minister Chomalí herself put her finger on the most honest sore point of the whole day: the barrier is not only technological, but one of medical and legal responsibility. "Who is going to be responsible if it is the AI that is looking at the image? How am I going to take charge of the results?", she asked, and she added the most common risk of this kind of public-health initiative: getting stuck as an eternal pilot program without persistently integrating into the care process. It is exactly the pattern we have seen repeated in dozens of healthcare AI projects around the world —good science, good initial funding, but regulatory and organizational friction that prevents the leap to daily practice. That the health authority itself says so at the presentation, instead of selling the project without nuance, is an unusual sign of maturity and one worth acknowledging.

Our reading is that the value of PRECISION-AI lies not so much in the amount —modest compared with what the major cancer centers or AI labs move globally— as in the architecture it proposes: a federated and shared data infrastructure is, potentially, more valuable in the long term than any single model, because it is the asset that allows the next generation of diagnostic tools to be trained and validated without each hospital having to solve the data-privacy problem from scratch. It is the same pattern we are seeing in other geographies: the contest is no longer just over who has the best model, but over who controls the data and clinical-integration layer on which those models operate. If Chile manages to make that infrastructure real, interoperable and effectively used —and not a promise that dissolves once the Corfo funding ends—, the country positions itself with an asset of digital healthcare sovereignty that is rare in the region.

This connects to the underlying thesis we hold at Zendoric: AI-assisted precision oncology is exactly the kind of application where long-term optimism has solid foundations. Cross-referencing genomics, clinical history and imaging with models capable of detecting patterns that a human eye would take years to identify is, literally, part of the path toward reducing cancer from a death sentence to a manageable chronic disease, and over time toward its virtual eradication as a leading cause of death. But that horizon does not arrive by decree or by budget: it arrives when projects like this solve, one by one, the boring and difficult problems of clinical governance, legal responsibility and hospital adoption that Minister Chomalí named without mincing words. Chilean talent and basic science, endorsed here by MIT's backing, are not the bottleneck; the translation to the patient's bedside is, and that is where this program will have to prove, over the next five years, whether it lived up to its own diagnosis.