The Overlooked Stage of the AI ​​Revolution: 170,000 German Practices

By Corinna Niebling

In Germany, there are just under 100,000 outpatient medical and psychotherapy practices. Together, they handle around 600 million patient cases annually. Added to this are approximately 70,000 practices for therapeutic services—including physiotherapy, occupational therapy, speech therapy, and podiatry. This constitutes the largest segment of the German healthcare system. Yet, it remains the blind spot of the HealthTech debate.

Anyone who has followed conferences, pitch decks, or the trade press over the past two years is familiar with the typical landscape: AI-driven diagnostics in university hospitals, surgical robotics, nursing assistance tools, and ambient documentation systems in inpatient care settings. Media and investor attention tends to focus on areas where use cases are spectacular and budgets are substantial. When the spotlight does occasionally shift toward outpatient care, it typically lands on prominent VC-backed ventures—either vertically integrated practice chains like Avi Medical and Patient21, or the all-encompassing infrastructure of an ecosystem like Doctolib. These are visible, well-marketed stories, backed by the reach and momentum of Series B funding.

However, actual adoption is taking place elsewhere: within the tens of thousands of existing practices—the very ones that no one ever showcases on a stage.

Warum diese Bühne unsichtbar ist

Established practices do not issue press releases. They have no investor updates, no LinkedIn presence, and no marketing budget. When a physiotherapy practice in Hamburg has been generating its therapy reports for health insurers using AI for the past three months—thereby saving two hours a week—this remains invisible to the public and to investors. From an investor’s perspective, nothing is happening there. From the perspective of healthcare delivery, however, a great deal is happening.

I am intimately familiar with this reality, having spent 14 years in outpatient care—covering everything from managed care and public health insurance billing to integrated care contracts. What is changing today is the pace. In conversations with practice owners, I now regularly hear stories that would have been unthinkable just two years ago: therapy reports drafted in minutes rather than hours using custom GPTs; clinical assessment templates generated from voice memos; and AI-assisted text modules for justifying treatment prescriptions. Not all of these applications are immediately legally compliant—particularly when patient data is involved—but the willingness to engage with these technologies is certainly there.

Three reasons why the revolution is taking place right here.

The first reason is the sheer pressure of the burden. Documentation overload, staff shortages, time constraints—this combination has been a known issue for years, but it has now reached a new level of urgency. Those working in outpatient settings are not choosing between "efficiency gains" and the "status quo"; rather, they are choosing between "keeping things running" and "reaching a breaking point."

The second reason is structural agility. A practice owner can make a decision in a matter of days—something that, in a hospital setting, would have to wind its way through six different committees. There is no IT steering committee, no 18-month roadmap, and no corporate procurement department. Once convinced, the decision-maker often makes the fundamental choice immediately—even if the detailed, legally compliant implementation remains the actual task requiring expert consultation.

The third reason is the low barrier to entry. The current generation of tools is SaaS-based, offers monthly cancellation options, and does not constitute a major IT project. A ChatGPT Plus subscription costs less per month than a single hour of a medical assistant's wages. Even specialized medical documentation tools often come in at under 150 euros. This fundamentally alters the risk calculation.

What this means in practice

The most concrete use case of this silent wave is the AI-assisted generation of therapy reports and justifications for prescriptions. It is no radiology showcase for the next healthcare conference. Yet, it is effective every day in thousands of medical practices—and more relevant to the economic viability of those practices than any hospital pilot project.

Why This Is Not “Interesting,” but “Imperative”

The German Economic Institute has reported that there are over 46,000 unfilled skilled positions in the healthcare sector in 2024. The field with the highest demand is not nursing; it is physiotherapy, with just under 12,000 open positions.

This figure completely shifts the narrative. AI in outpatient care is not merely a matter of efficiency, nor is it a "business opportunity" in the traditional sense. It is about safeguarding the provision of care. Those waiting for new staff members will face a long wait—and in many regions, a futile one. By using AI to reduce the administrative burden, a standard 38-hour position can be transformed back into one where 30 hours remain dedicated to patient care.

That is the real market—not "AI for Health" as a buzzword in a pitch deck, but rather: tools that prevent medical practices from having to close their doors simply because there is no one left to write the reports.

What this means for founders and investors

Anyone approaching HealthTech solely from a hospital perspective is bound to miss this wave. The logic of distribution operates differently here: it relies not on enterprise sales, but on professional associations, practice management software vendors, and chains of recommendations among practice owners. Added to this is a compliance landscape that is truly formidable: the GDPR, the EU AI Act, and Section 203 of the German Criminal Code—all colliding with organizational structures that possess virtually no internal capacity for data protection management. Furthermore, the ROI is not driven by multi-million-euro deals, but rather by hundreds of euros per practice per month, multiplied across a six-figure number of locations.

It is not an easy market. But it is here. Real, massive, and hungry.

The AI ​​revolution in the German healthcare sector will not be decided within university hospitals. It will be decided within the approximately 170,000 outpatient practices that provide care to this country every single day. For those who turn their gaze in that direction, the stage is—quite literally—theirs alone.

Corinna Niebling is a TÜV-certified AI Consultant, a former strategy consultant at BCG, and a qualified mathematical economist. Drawing on 14 years of experience in the outpatient care sector, she now advises therapeutic and medical practices on the legally compliant implementation of AI technologies. For contact details and a free initial consultation, please visit www.corinnaniebling.de.