Author: Lidziya Tarasenka

GPS arrived, and at some point we stopped reading maps. There was no decision made — it just happened, almost imperceptibly, over a few months of simply not needing to. A similar shift is now underway in finance: AI is taking over tasks that until recently counted as skilled, hands-on work. According to Deloitte, 87% of CFOs say AI will be very or extremely important to the finance function in 2026. The age of paper maps, it seems, has passed here too.

Healthcare systems differ widely in financing models, access to high-end technologies and nearly every aspect of care with probably one exception. Paperwork. It is unavoidable and merciless, in the US resident physicians spend an average of 45.6 minutes on the health records per patient. While the average ambulatory encounter runs 15–18 minutes of actual face time.

Enterprise networks were not designed for what we’re asking of them now. AI infrastructure, geopolitical fragmentation, automation, massive data flows between facilities: these things are piling up faster than most organizations can deal with them. We found someone who knows where the bodies are buried.

Many promising companies fall apart not because of bad ideas, but because of growth. Once a team reaches a certain size, the informal agreements and goodwill that once kept things moving stop working. Decisions get lost, accountability blurs, and instead of results you get endless process reshuffling and work for the sake of work. The way out is clear, firm rules. Today we talk about the attempt to reconcile creativity and structure inside large companies. Not everyone likes it, but there’s no other way to build systems that last.

Have you ever heard a doctor say something like: “Didn’t this help you at all? Hmm. Ok, let’s try these pills instead”? How does it feel to be a lab rat? Of course it’s not human experimentation — but what if you could get the right therapy without all that trial and error? Imagine your doctor had an exact copy of you to test all their ideas on — not on you. Wouldn’t that be fantastic? Today, this isn’t entirely science fiction. You can give your doctor a digital twin to experiment on.

Artificial intelligence is beginning to outperform humans in narrow but economically consequential tasks, raising anxieties about job security and even agency. We are seriously discussing the possibility of losing control over AI. And one of the proposed ways of dealing with it is integration: linking the nervous system to digital tools through the brain-computer interfaces (BCIs).

Language models are widely capable of answering health-related questions — a topic that the media have covered extensively. These are truly remarkable advancements. However, the process of implementing them into real life rarely draws the same attention; it is accompanied by tedious paperwork and annoying safety issues.

A paperclip‑sized wireless sensor that tracks pressures inside the heart–lung circulation has been recommended by NICE for routine use across the NHS in England, in a move expected to shift heart‑failure management from hospital clinics to patients’ homes.

Medtronic announced on February 3, 2026, its intent to exercise its option to acquire CathWorks, an Israeli medical device company specializing in AI-driven coronary artery disease diagnostics, in a deal valued at up to $585 million plus potential undisclosed earn-out payments. The acquisition, pending U.S. Federal Trade Commission clearance, is expected to close by the end of Medtronic’s fiscal year 2026.

AI models for healthcare are proliferating, but most never leave the labs. Real-world deployment is far more complicated than any multiple-choice graduate exam – hospitals use different systems, data formats, and security protocols that resist standardization. Kaapana, an open-source platform developed at the German Cancer Research Center, addresses translation barriers by providing standardized infrastructure for medical AI research.