AI medical scribes are moving from pilots to nationwide rollout across Europe. Discover the latest developments and what 2026 could mean for healthcare.
For years, AI medical scribes have been discussed as a future solution to clinical documentation burden. That future has arrived. In 2025, several European countries shifted from small, local pilots to rolling things out nationwide, and 2026 may be the year that decides whether AI scribes truly embed into healthcare systems or remain standalone tools. Here we highlight some of the most recent developments in the space and discuss what we are expecting to see in the coming year!
European countries are already attempting to implement AI scribes on a national level, a tactic that allows to test these tools on a big scale simultaneously.
Norway offers a glimpse of where Europe is heading. At the end of 2025, Norway launched a single national tender worth approximately 15 million euros for AI medical scribing1, replacing the need for individual hospitals or clinics to run their own lengthy procurement processes. Instead of each hospital negotiating on its own, Norway is selecting 4–5 vendors through one national agreement that everyone can use.
The tender requires AI medical scribing solutions to be designed so they could later qualify as medical devices with CE marking under the Medical Device Regulation (MDR). This means vendors have to make sure their products meet strict safety, performance, and monitoring standards, including risk management, performance validation, and post-market surveillance. Achieving this also demands increased expertise in EU regulations such as MDR, GDPR, and the EU AI Act.
In most of Europe, ambient scribes, used for transcribing and summarizing patient visits, are considered administrative tools and therefore do not have to comply with the MDR. The Norwegian tender described earlier already signals that this may not be sufficient. The UK, which as a non-EU country can follow its own playbook, already considers AI scribes to be tools with a medical intended purpose2.
This shift hasn’t gone unnoticed by vendors. Several AI scribe providers, like Corti, Tortus, and Tandem, position their AI scribes as Class I medical devices. For providers that want to move into diagnostics down the line, this feels like a smart way to get ahead of the curve.
Even in a relatively small market like the Netherlands, more than 20 companies are already offering AI medical scribe solutions. This is typical for emerging technology fields: an initial wave of innovation attracts a large number of entrants, but over time the market inevitably consolidates. Simply put, there are too many players competing for the same space.
At the same time, the ambitions of these solutions are expanding. What started as “just” documentation support is evolving into broader clinical functionality. And as soon as scribe technology begins to cross into medical device territory, the requirements change significantly. Clinical validation, regulatory compliance, and quality management systems demand time, expertise, and, most importantly, capital. Deeper pockets become essential.
In that context, consolidation is not only expected, but logical.
A first clear signal of this shift appeared in late 2025 and at the start of 2026, when the Swedish Tandem Health acquired the Dutch company Juvoly3,marking Europe’s first acquisition in the AI medical scribe space. More than a simple growth move, this deal reflects a broader market reality: AI scribes are no longer viewed asstandalone productivity tools, but as the base layer for future AI medical assistants.
Not only is procurement happening more centrally, but the validation of these tools as well. An NHS England–sponsored study across nine London NHS sites tested an AI scribing tool, that transcribes consultations in real time and drafts clinical notes for clinicians to review4.
Clinicians described the tool as “transformative,” reporting a 35% reduction in feeling overwhelmed by notetaking. Patients and carers were just as positive. 92% were happy to have AI scribes in the room, satisfaction was high, and many even noticed clinicians seemed more engaged during consultations. Findings from the trial have informed national NHS guidance on AI-enabled scribes, supported the Government’s 10-year Health Plan, and helped shape national evaluation frameworks.
This momentum is also shown in NHS England’s recent release of national guidance on ambient AI and AI-enabled scribing, providing clearer direction on how these tools should be deployed responsibly at scale.
Similar findings have been reported in two large randomized controlled trials of AI scribes in the United States5. AI scribes were associated with a statistically significant reduction in clinician work exhaustion and interpersonal disengagement, while documentation quality remained high, billing accuracy improved, and no safety drift was observed. On the surface, the productivity gains appear modest: 1-2 minutes saved per visit in typical healthcare settings6, and around 22 minutes per day5 in best-case scenarios.
The takeaway is clear: what we choose to measure shapes how we judge their value. When burnout, cognitive load, and healthcare quality are considered alongside efficiency, the case for AI scribes becomes far more compelling. This is exactly why we need national coordinated validation and evaluation frameworks for responsible deployments, a movement we clearly see in the Netherlands with the RIGH:T Consortium7 and Digizo.nu8 initiatives.
As AI scribes are rapidly adopted in daily clinical practice, this also brings risks. Once AI scribes move into clinical decision support, their impact spreads across workflows and so do the risks. Despite rapid advancements in generative AI technology, hallucinations are still a known problem with large language models. However, clear validation frameworks for AI scribes are not established yet.
Right now, clinical validation is usually happening during implementation, through feedback loops, once the tool is already in the clinician’s office. On top of this, we see many AI vendors leave the creation of prompting and templates to healthcare professionals, raising questions about quality control and ensuring appropriate use. Besides concerns about safety, we foresee challenges in accountability and real‑world performance monitoring when these processes are not governed.
Key concerns about bias, generalizability, and local context aren’t yet fully addressed when AI moves from development into real-world practice. Clinicians and healthcare institutions still need to take ultimate responsibility, with clear transparency about the performance of the AI. Overall, it calls for better frameworks that combine technical and clinical validation with ethical, legal, and workflow considerations.
Data privacy becomes a bigger concern when you consider the patient data needed to validate these tools. AI scribes produce a continuous stream of audio recordings and detailed transcripts from clinical encounters. Rather than being treated as disposable “digital exhaust,” this information should be recognized as a high-value clinical asset9.
When handled responsibly, clinical data can support ongoing validation, post-deployment monitoring, and research into the safety and quality of AI scribes. At the same time, this richness introduces real risks around privacy, consent, and misuse, making explicit governance frameworks for secondary use of data not just helpful, but essential.
In the Netherlands, a large group of healthcare organizations are collaborating in the RIGH:T Consortium to develop a validation framework for the safe use of AI scribes in the local setting. With a main focus on the quality of AI-generated clinical notes, such as assessing the degree of hallucinations, missing information, and bias. Some vendors even implement extra security measures for detecting these mistakes to minimize the risk to patient safety.
While the adoption of AI scribes keeps moving fast, in 2026, we will see increased maturity from both from AI vendors and healthcare organizations in ensuring responsible deployment of AI scribes. Especially when the shift towards clinical decision support is around the corner and more MDR compliant AI scribes enter the European market, ask yourself this: Is my organization ready for large scale adoption of AI scribes?
Don’t worry if the answer to the previous question is no. Our team at Romion Health offers support through every step of this journey, providing expert guidance to ensure the responsible and effective adoption of health AI solutions.
We have, for example, critically assessed AI scribe vendors for the national collaboration between healthcare organizations and health insurance companies at Digizo.nu, and we actively support hospitals in developing and implementing GenAI policies that align technological innovation with clinical needs.
In the context of AI scribes, our support spans the full lifecycle:
By pairing rigorous validation with clear governance and education, we drive responsible AI adoption for futureproof care!
2 https://www.meddeviceonline.com/doc/the-u-k-now-classifies-ambient-voice-technology-as-samd-0001
5 Kim, E., Liu, V. X., & Singh, K. (2025). AI scribes are not productivity tools (YET). NEJM AI, 2(12). https://doi.org/10.1056/aie2501051
6https://www.medrxiv.org/content/10.64898/2025.12.06.25341757v1.full.pdf
8https://digizo.nu/proces/spraakgestuurd-rapporteren/
9 Goodman, K. E., & Morgan, D. J. (2025). Digital exhaust or digital Gold? The value of AI-Generated Clinical Visit Transcripts. New England Journal of Medicine, 394(2), 110–113. https://doi.org/10.1056/nejmp2514616
For years, AI medical scribes have been discussed as a future solution to clinical documentation burden. That future has arrived. In 2025, several European countries shifted from small, local pilots to rolling things out nationwide, and 2026 may be the year that decides whether AI scribes truly embed into healthcare systems or remain standalone tools. Here we highlight some of the most recent developments in the space and discuss what we are expecting to see in the coming year!
European countries are already attempting to implement AI scribes on a national level, a tactic that allows to test these tools on a big scale simultaneously.
Norway offers a glimpse of where Europe is heading. At the end of 2025, Norway launched a single national tender worth approximately 15 million euros for AI medical scribing1, replacing the need for individual hospitals or clinics to run their own lengthy procurement processes. Instead of each hospital negotiating on its own, Norway is selecting 4–5 vendors through one national agreement that everyone can use.
The tender requires AI medical scribing solutions to be designed so they could later qualify as medical devices with CE marking under the Medical Device Regulation (MDR). This means vendors have to make sure their products meet strict safety, performance, and monitoring standards, including risk management, performance validation, and post-market surveillance. Achieving this also demands increased expertise in EU regulations such as MDR, GDPR, and the EU AI Act.
In most of Europe, ambient scribes, used for transcribing and summarizing patient visits, are considered administrative tools and therefore do not have to comply with the MDR. The Norwegian tender described earlier already signals that this may not be sufficient. The UK, which as a non-EU country can follow its own playbook, already considers AI scribes to be tools with a medical intended purpose2.
This shift hasn’t gone unnoticed by vendors. Several AI scribe providers, like Corti, Tortus, and Tandem, position their AI scribes as Class I medical devices. For providers that want to move into diagnostics down the line, this feels like a smart way to get ahead of the curve.
Even in a relatively small market like the Netherlands, more than 20 companies are already offering AI medical scribe solutions. This is typical for emerging technology fields: an initial wave of innovation attracts a large number of entrants, but over time the market inevitably consolidates. Simply put, there are too many players competing for the same space.
At the same time, the ambitions of these solutions are expanding. What started as “just” documentation support is evolving into broader clinical functionality. And as soon as scribe technology begins to cross into medical device territory, the requirements change significantly. Clinical validation, regulatory compliance, and quality management systems demand time, expertise, and, most importantly, capital. Deeper pockets become essential.
In that context, consolidation is not only expected, but logical.
A first clear signal of this shift appeared in late 2025 and at the start of 2026, when the Swedish Tandem Health acquired the Dutch company Juvoly3,marking Europe’s first acquisition in the AI medical scribe space. More than a simple growth move, this deal reflects a broader market reality: AI scribes are no longer viewed asstandalone productivity tools, but as the base layer for future AI medical assistants.
Not only is procurement happening more centrally, but the validation of these tools as well. An NHS England–sponsored study across nine London NHS sites tested an AI scribing tool, that transcribes consultations in real time and drafts clinical notes for clinicians to review4.
Clinicians described the tool as “transformative,” reporting a 35% reduction in feeling overwhelmed by notetaking. Patients and carers were just as positive. 92% were happy to have AI scribes in the room, satisfaction was high, and many even noticed clinicians seemed more engaged during consultations. Findings from the trial have informed national NHS guidance on AI-enabled scribes, supported the Government’s 10-year Health Plan, and helped shape national evaluation frameworks.
This momentum is also shown in NHS England’s recent release of national guidance on ambient AI and AI-enabled scribing, providing clearer direction on how these tools should be deployed responsibly at scale.
Similar findings have been reported in two large randomized controlled trials of AI scribes in the United States5. AI scribes were associated with a statistically significant reduction in clinician work exhaustion and interpersonal disengagement, while documentation quality remained high, billing accuracy improved, and no safety drift was observed. On the surface, the productivity gains appear modest: 1-2 minutes saved per visit in typical healthcare settings6, and around 22 minutes per day5 in best-case scenarios.
The takeaway is clear: what we choose to measure shapes how we judge their value. When burnout, cognitive load, and healthcare quality are considered alongside efficiency, the case for AI scribes becomes far more compelling. This is exactly why we need national coordinated validation and evaluation frameworks for responsible deployments, a movement we clearly see in the Netherlands with the RIGH:T Consortium7 and Digizo.nu8 initiatives.
As AI scribes are rapidly adopted in daily clinical practice, this also brings risks. Once AI scribes move into clinical decision support, their impact spreads across workflows and so do the risks. Despite rapid advancements in generative AI technology, hallucinations are still a known problem with large language models. However, clear validation frameworks for AI scribes are not established yet.
Right now, clinical validation is usually happening during implementation, through feedback loops, once the tool is already in the clinician’s office. On top of this, we see many AI vendors leave the creation of prompting and templates to healthcare professionals, raising questions about quality control and ensuring appropriate use. Besides concerns about safety, we foresee challenges in accountability and real‑world performance monitoring when these processes are not governed.
Key concerns about bias, generalizability, and local context aren’t yet fully addressed when AI moves from development into real-world practice. Clinicians and healthcare institutions still need to take ultimate responsibility, with clear transparency about the performance of the AI. Overall, it calls for better frameworks that combine technical and clinical validation with ethical, legal, and workflow considerations.
Data privacy becomes a bigger concern when you consider the patient data needed to validate these tools. AI scribes produce a continuous stream of audio recordings and detailed transcripts from clinical encounters. Rather than being treated as disposable “digital exhaust,” this information should be recognized as a high-value clinical asset9.
When handled responsibly, clinical data can support ongoing validation, post-deployment monitoring, and research into the safety and quality of AI scribes. At the same time, this richness introduces real risks around privacy, consent, and misuse, making explicit governance frameworks for secondary use of data not just helpful, but essential.
In the Netherlands, a large group of healthcare organizations are collaborating in the RIGH:T Consortium to develop a validation framework for the safe use of AI scribes in the local setting. With a main focus on the quality of AI-generated clinical notes, such as assessing the degree of hallucinations, missing information, and bias. Some vendors even implement extra security measures for detecting these mistakes to minimize the risk to patient safety.
While the adoption of AI scribes keeps moving fast, in 2026, we will see increased maturity from both from AI vendors and healthcare organizations in ensuring responsible deployment of AI scribes. Especially when the shift towards clinical decision support is around the corner and more MDR compliant AI scribes enter the European market, ask yourself this: Is my organization ready for large scale adoption of AI scribes?
Don’t worry if the answer to the previous question is no. Our team at Romion Health offers support through every step of this journey, providing expert guidance to ensure the responsible and effective adoption of health AI solutions.
We have, for example, critically assessed AI scribe vendors for the national collaboration between healthcare organizations and health insurance companies at Digizo.nu, and we actively support hospitals in developing and implementing GenAI policies that align technological innovation with clinical needs.
In the context of AI scribes, our support spans the full lifecycle:
By pairing rigorous validation with clear governance and education, we drive responsible AI adoption for futureproof care!
2 https://www.meddeviceonline.com/doc/the-u-k-now-classifies-ambient-voice-technology-as-samd-0001
5 Kim, E., Liu, V. X., & Singh, K. (2025). AI scribes are not productivity tools (YET). NEJM AI, 2(12). https://doi.org/10.1056/aie2501051
6https://www.medrxiv.org/content/10.64898/2025.12.06.25341757v1.full.pdf
8https://digizo.nu/proces/spraakgestuurd-rapporteren/
9 Goodman, K. E., & Morgan, D. J. (2025). Digital exhaust or digital Gold? The value of AI-Generated Clinical Visit Transcripts. New England Journal of Medicine, 394(2), 110–113. https://doi.org/10.1056/nejmp2514616
