How AI Is Helping Healthcare Companies in Norway Cut Costs and Improve Efficiency

Norway's healthcare system is pivoting to AI because high digital maturity, an ageing population and staff shortages make efficiency more than a nice-to-have - it's essential.

National studies map the full implementation pathway for clinical AI, while reporting from Business Norway shows real gains: digital platforms such as CheckWare and Dignio cut administrative time drastically (57.4%) and enable safe home-based monitoring that reduces hospital stays; AI also accelerates diagnostics in areas like mammography, where roughly one million images are generated each year.

Regional projects such as Kontiki bring AI-powered remote follow-up to rural homes, cutting unnecessary travel and freeing clinical resources. For healthcare companies in Norway this adds up to lower costs, better triage and faster clinical trials - practical workplace AI skills can be learned through short courses like Nucamp's Nucamp AI Essentials for Work bootcamp, while deeper digital-health lessons are captured in Norway's implementation reports and case studies such as those from Business Norway digital healthcare case study and the Interreg Kontiki AI remote follow-up project.

Bootcamp	Length	Early bird cost	Register
AI Essentials for Work	15 Weeks	$3,582	Register for Nucamp AI Essentials for Work

“The goal is for patients with chronic conditions such as heart failure to feel safer and receive fast and targeted treatment.” - Finn Samuelsen

Norway's shift to AI is driven less by tech curiosity and more by structural need: Statistics Norway's 2024 projections warn that the 80+ cohort will more than double by 2050, while reporting shows roughly 250,000 more Norwegians over 80 in the next 20 years - a demographic tidal wave that meets a shrinking caregiver base and strained municipal services, especially in small municipalities where pressure on home care has been linked to higher mortality rates; these realities make automation, predictive triage and remote monitoring practical imperatives rather than optional upgrades.

At the same time, Norway's unusually high digital readiness - a strong Networked Readiness ranking and widespread internet use among older adults - and active innovation programmes like InnoMed and local housing-team pilots create fertile ground for pilots to scale.

For healthcare companies this means clear market demand, a policy-friendly ecosystem and a “now-or-wait” moment where AI can cut costs, avoid risky discharge bottlenecks and keep more people safely at home.

Driver	Figure / Implication
Population ageing	Statistics Norway 2024 national population projections - 80+ cohort to more than double by 2050
Caregiver shortfall & municipal pressure	Norwegian SciTech News - ~250,000 more 80+ in 20 years; many small municipalities under strain
Digital readiness & innovation	AARP International - Norway aging readiness, InnoMed and local pilot programmes

“Municipalities have every interest in promoting active aging and preventing the aging population from becoming a passive, care-receiving population.”

Norway's push to keep more people safely at home is already visible in concrete tools: CheckWare's digital patient participation platform turns patient-reported measures into remote monitoring, letting clinics follow 13 times more people and cutting administrative work dramatically - in one case contributing to a six‑week reduction in hospital time for premature newborns - while Dignio's home-care suite sends vitals (BP, oxygen, glucose, weight, lung function) straight to the MyDignio app for clinician review; virtual hospital programmes such as Vestre Viken extend home dialysis and digitally followed orthopaedic recoveries, and contactless sensors like Vitalthings' Somnofy add non-intrusive sleep and presence monitoring for nursing homes.

These real-world examples from Norway show how remote monitoring and simple patient self-reporting free up clinicians' time, prioritise the sickest patients and shrink waiting lists - read more in Business Norway's roundup of Norwegian digital solutions and CheckWare's platform overview for details.

Metric	Figure / Source
Reduction in administrative time	57.4% - Business Norway
Increase in follow-up capacity	13× more patients - CheckWare
CheckWare reach	928,000 patients across 250 clinics - CheckWare

“I love this solution, I feel like it is a great source of security! The patients also follow their own development, look at their graphs, and reflect on the situation themselves.” - Kaja Asbjörnsen Betin, Psychologist, Lovisenberg DPS

Contactless sensors are becoming a practical backbone for Norwegian care: VitalThings' Somnofy and its clinical derivatives (Guardian M10/H10) turn low‑power radar into continuous, bedside intelligence that tracks presence, sleep stages, movement and - crucially - respiratory rate with clinical‑grade accuracy, so nurses can prioritise the patient who's deteriorating instead of doing routine night checks; municipalities such as Volda and emergency units in Ålesund have used Somnofy to cut needless room visits, and elite sport and university validation studies from UiB and NTNU show Somnofy matches polysomnography closely enough for large‑scale monitoring.

These contactless systems feed morning reports and real‑time alerts to phones or dashboard screens, reduce alarm noise and free staff time for care tasks that need human judgement, and the company's Trondheim roots have already scaled deployments across municipalities and research partners.

For healthcare companies in Norway this means a proven sensor stack to pilot that lowers supervision costs, improves patient comfort and creates data streams for future AI triage or RTLS‑style presence services.

Product	Measures	Typical settings / deployments
Somnofy contactless sleep and respiratory monitoring device	Sleep stages, presence, movement, respiratory rate, sound, light, air quality	Nursing homes, home care, research (Volda kommune, Olympiatoppen; validated by UiB/NTNU)
Guardian M10/H10 continuous vital-sign monitoring (VitalThings)	Continuous vital signs, breathing patterns, presence, unrest; real‑time alerts	Emergency departments, orthopaedic wards, nursing homes, home care (medical approval case studies)

“This is the best alternative to PSG as I see it today.” - Ståle Pallesen, sleep scientist (validation study)

AI is moving from pilot to practical in Norway by taking the chaos out of rostering and logistics: projects and companies now use historical data to predict sick leave, set smarter shifts and cut dependence on temporary staff so permanent teams can work full-time and with fewer surprises.

Research projects such as OptiCare‑AI municipal AI scheduling project are testing AI-driven scheduling in municipalities to boost full‑time employment and better match tasks to competence, while startups like SynPlan AI staffing platform report pilots that reduce overtime, lower absenteeism and make staffing decisions faster and more confident.

At hospital scale, logistical tools already save millions and slash administrative burdens - Dossier Solutions reported roughly USD 10 million saved over three years and large cuts in paperwork - freeing clinicians to focus on patients rather than spreadsheets.

Combined with national guidance such as the Norwegian Joint AI Plan for safe and effective use of AI in health and care services (2024–2025), these workforce and logistics systems promise one tangible benefit: fewer last‑minute night calls and a schedule that feels less like firefighting and more like a reliable rhythm for care teams.

Project	Duration	Budget (NOK)	Main objective
OptiCare‑AI	2025–2029	15,800,000	AI‑based staffing optimisation in home‑based care; increase full‑time work and better task allocation

“AI is a key component in logistical technology. It helps us to orchestrate our healthcare resources, optimise scheduling, and predict staffing and budgetary needs.” - Sindre Holme, Norway Health Tech

Clinical AI is already sharpening diagnosis and speeding treatment across Norway: Ålesund Hospital's installation of a Discovery™ MI Gen 2 PET/CT brings deep‑learning reconstruction and AI‑based motion correction to regional care, improving image detail and letting more patients be scanned locally (tracer flown in from Oslo once a week; current throughput 6–8 patients/day with a target of 10), which spares many people long car or plane journeys for a precise cancer, cardiovascular or dementia work‑up - a clear “so what?” when a single scanner can keep a whole coastal region's diagnostics close to home.

At the same time, Norwegian imaging research on automated, texture‑based lung and lesion segmentation and newer multi‑organ CT segmentation methods reduce clinician workload by delivering fast, reliable masks and 3D models for planning and triage, creating tangible efficiency gains in reporting and downstream treatment decisions; see the Ålesund PET/CT overview and the Rikshospitalet segmentation study for technical and clinical details.

Item	Detail / Source
Scanner	Discovery™ MI Gen 2 PET/CT - GE Healthcare Discovery MI Gen 2 PET/CT overview
Funding & community	3,100 donors; 36 million NOK raised for scanner, building and training
Capabilities	30 cm digital coverage; TrueFidelity™ deep‑learning reconstruction; AI motion correction
Research on automation	Automated lung/lesion segmentation (Rikshospitalet) - Rikshospitalet automated lung and lesion segmentation PubMed study; multi‑organ CT segmentation preprint - medRxiv multi-organ CT segmentation preprint

“The quality and the degree of detail we get in the images is superior. The machine is easy to use, and we are happy with features like motion correction based on AI algorithms.” - Ida Fallmyr Jørgensen, Project Manager, Ålesund Hospital

As AI moves from pilots to everyday clinical tools, Norway's policy conversation has shifted from “can we?” to “how do we do it safely?” - balancing efficiency gains with privacy, equity and clinical responsibility.

National workstreams such as the Norway National AI Strategy report set out ethical principles (responsible, transparent, accountable) and practical levers like regulatory sandboxes and data‑infrastructure projects, while independent reviews such as Teknologirådet's “Artificial intelligence in the clinic” warn that choices in parliament and hospitals will shape patient journeys for a decade and raise concrete issues around consent, reuse and discrimination.

On the ground, research projects and hospital initiatives keep bumping into fragmented rules and GDPR‑driven data‑minimisation limits that slow model training and evaluation; national reforms (amendments to the Health Personnel and Health Records Acts) offer narrow exceptions, but experts urge broader, coordinated governance so raw clinical data can be used securely for validation, bias checks and continuous improvement.

For providers and health tech companies the pragmatic takeaway is clear: invest in model cards, explainability, representative datasets and formal governance plans now to turn ethical requirements into competitive advantages and trustworthy care.

“We were bounced around like a ping pong ball between various authorities with different interpretations of the regulations.”

Norway is not only digitising care at home - it's exporting governance know‑how and building the human capacity to do it right: a NOK 45 million grant backs HealthAI's three‑year strategy to help Low‑ and Middle‑Income Countries adopt global standards and a Community of Practice for responsible AI in health, while national calls and centres pump hundreds of millions into domestic research and networking that feed international cooperation.

The Research Council's AI Centres programme (NOK 75–200M per centre) and the wider “KI billion” investment have seeded long‑term competence hubs and cross‑border partnerships, and targeted funding like the NOK 69 million programme for medical AI at UiB explicitly encourages international collaborators and translational projects.

Smaller preparatory grants (NOK 100k–300k) and capacity schemes from health authorities round out a ladder from pilot to policy, turning Norway's registries, biobanks and research networks into practical levers for equitable, standards‑based AI deployments worldwide; see HealthAI's announcement, the Research Council AI Centres call, and UiB's Medical AI call for details.

Initiative	Scale / Detail
HealthAI Norway grant for global AI governance in healthcare	NOK 45 million grant to HealthAI's 3‑year strategy to build regulatory capacity in LMICs
Research Council of Norway AI Centres funding call	Centres funded in the NOK 75–200 million range; “KI billion” awarded ~1.3 billion to six centres
University of Bergen Medical AI research call (UiB)	Total NOK 69 million to strengthen medical AI research in Bergen (matched funding required)

“AI should be a public digital common good. Better regulation is essential to promote secure and ethical AI solutions. Within global health, AI provides a tremendous potential to increase access to health care, improve treatment, and overall play a role in strengthening health systems. Ensuring access to responsible AI solutions for low- and middle-income countries is essential to counteract the digital divide.” - Anne Beathe Kristiansen Tvinnereim

Norway's startup scene is sending a clear market signal: healthtech is maturing from clever pilots into exportable products that shave costs and free clinical time.

Cluster organisations like the HealthTech Nordic community (Norwegian healthtech network) and the Norway Health Tech cluster knit together scaleups, researchers and buyers, while homegrown firms - Vitalthings (contactless vital‑sign monitoring), SynPlan (AI workforce planning) and novel diagnostics companies - turn clinical pain points into commercial products; HTWorld highlights how vendors such as DNV Imatis and Deepinsight drive measurable gains (productivity lifts and shorter waiting lists) and Business Norway notes surgical‑planning and imaging innovators winning CE/UKCA traction.

Investors are following: Oslo's Journalia raised USD 1M to scale AI clinical documentation, a tidy example of capital backing automation that reduces admin burden and speeds patient-facing care.

For healthcare companies scouting partners, the takeaway is vivid: Norway offers a compact, well‑funded ecosystem where sensor firms, scheduling AI and imaging startups create interoperable building blocks - so a single municipality can pilot a contactless monitor, smarter rostering and an AI triage flow and see staffing calls and unnecessary admissions fall in weeks, not years.

Read the HealthTech Nordic community profile, the HTWorld article on Norwegian tech companies streamlining healthcare delivery, and Journalia's USD 1M funding announcement for concrete leads.

Startup / Cluster	Signal / Evidence
HealthTech Nordic community (Norwegian healthtech network)	World‑leading community linking healthtech vendors and buyers
Vitalthings	Norwegian contactless monitoring on market (ISO/MDR certifications)
SynPlan	AI staffing platform; reported savings and coverage for 10,000+ workers
HTWorld report on DNV Imatis and Deepinsight	Productivity up to ~20%; reduced waiting lists in pilots
Journalia USD 1M funding announcement to scale AI clinical documentation	Raised USD 1M to scale AI clinical note automation

“Norway is a highly technological society and has the money to invest in medtech solutions.” - Sindre Holme, Norway Health Tech

Practical first steps for Norwegian healthcare companies are simple, sequential and built on good governance: begin by tightly scoping the clinical problem and involving end users early so the solution truly answers a local need (the “prior to procurement” phase in the national guide), then map legal, CE‑marking and data requirements and check market maturity rather than buying hype; concrete resources such as the Tidsskriftet implementation guide on AI in health and the NTNU “AI Assistant Guide” translate these ideas into checklists and a fast, two‑ to three‑month starter path, while the Directorate of Health's quality‑assurance report explains how to design monitoring, bias checks and model‑drift plans for safe use.

Pilot small, validate on Norwegian data (language and population), integrate with existing workflows via an interdisciplinary team, and demand technical interoperability and clear contractual performance metrics so responsibility and liability are defined up front; early pilots can also show quick wins - for example, documentation assistants have reported time savings of up to two hours per clinician per day.

Treat procurement as an iterative lifecycle (procure → validate → monitor) and invest in staff competence and governance documents (model cards, monitoring plans) so safety and benefits scale together.

Phase	Key actions (source)
Prior to procurement	Define problem, involve end users, assess market & CE needs - Tidsskriftet guide
Procurement	Pilot small, require clinical documentation, check data residency & interoperability - Helsedirektoratet
Following procurement	Integrate, monitor performance/model drift, governance & training - Tidsskriftet / Helsedirektoratet

"It was important for us to develop a concrete and user-friendly guide that Norwegian organizations can actually use." - Jon Atle Gulla

The practical takeaway for Norway is clear: AI can deliver real savings and faster, safer care - but only when budgets, timelines and trust are built into the plan from day one.

Cost studies show AI's price tag extends beyond the model itself to infrastructure, integration, security and specialised teams, yet well‑targeted projects can automate large chunks of administration (estimates up to 45%) and quickly free clinical time; see a concise breakdown in Cleveroad's cost guide for healthcare AI implementation.

Equally important is clinician confidence and workflow fit - recent industry analysis argues that trusted, evidence‑based clinical intelligence must be embedded into everyday systems for organisations to capture value, not just novelty.

Norway's long experience with health IT warns that benefits don't appear automatically; a phased, modular rollout, rigorous governance (model cards, monitoring) and investment in staff skills will turn pilots into durable savings.

For teams ready to act, practical training - such as Nucamp's AI Essentials for Work - pairs short, workplace‑focused learning with the governance mindset needed to scale AI safely in Norwegian care settings.

Bootcamp	Length	Early bird cost	Register
AI Essentials for Work	15 Weeks	$3,582	AI Essentials for Work bootcamp registration - Nucamp

“With trusted, evidence-based clinical intelligence embedded across your health system, your teams can make care decisions confidently in the new era of healthcare.”