The Complete Guide to Using AI in the Healthcare Industry in Slovenia in 2025

Slovenia is treating AI in health as a national priority - its 2020–2025 programme explicitly targets

health and medicine

as a reference implementation area and has earmarked around EUR 110 million to turn strategy into pilots and production-ready systems, while investing in human capital, ethics and infrastructure like the VEGA EuroHPC supercomputer to support research and clinical models (see the Slovenia AI Strategy Report (EU AI Watch)).

The National Programme (NpAI) stresses education, data spaces, and trustworthy frameworks to build public confidence and speed adoption across hospitals and public health agencies - practical workforce training, from short upskilling to bootcamps, is highlighted as essential (read the Slovenia National Programme to Promote the Development and Use of AI (NpAI) - DIG Watch).

For busy healthcare teams wanting hands-on AI skills for workflows and prompts, an applied option is the Nucamp AI Essentials for Work bootcamp (registration), which maps directly to the

skills and lifelong learning

strand of Slovenia's plan.

Slovenia's AI policy framework for health is being built on clear public‑health goals rather than tech for its own sake: the WHO's mid‑term country profile highlights strengthened capacity in data and innovation, leadership and governance, and digital platforms as core outcomes that make trustworthy AI adoption possible (WHO country profile for Slovenia - Mid‑Term Results 2024–2025).

That foundation means regulation and strategy can focus on practical priorities - equitable access, workforce upskilling, pandemic preparedness and transparent decision‑making - so hospitals and public health agencies have common standards for validation, procurement and risk management.

Policy attention to analytics and health information systems also creates room for measurable pilots (think dashboards tied to the Triple Billion targets) that prove value - for example, pilots designed to show ROI through fewer avoidable admissions and lower sick leave (Measuring AI ROI in Slovenian healthcare: cost savings and efficiency), a concrete “why” that helps turn governance frameworks into clinical practice.

Slovenia's push to build human capital for healthcare AI is practical and systemic: the National Programme and related plans aim to update curricula at all levels, expand lifelong learning and short in‑service courses for clinicians and teachers, and make digital tools part of everyday practice (see the Slovenia AI Strategy Report - EU AI Watch).

On the ground, the 2021–27 Digital Education Action Plan and related laws back teacher training, distance‑learning platforms and infrastructure upgrades so educators can teach computational thinking, AI basics and ethics across subjects (Digital Education Action Plan and Technology Profile - Education Profiles).

Practical supports matter: national services like ARNES, the SIO distance‑learning portal and the eTorba “digital schoolbag” already reach hundreds of classrooms (coverage cited at 140+ schools in recent seminars) and the 2022 Act on Promotion of Digital Inclusion even provides a digital voucher (EUR 100–200) to lower the device barrier.

This combination - clearer curricula, teacher upskilling, classroom tools and modest hardware support - creates a realistic pathway for clinicians, health informaticians and hospital trainers to move from curiosity to competent, auditable AI use in everyday healthcare workflows.

"This year's expo closely aligns with the latest trends in technology and education, bringing together leading international scholars and guests to Hong Kong to exchange ideas and share their insights and experiences. With artificial intelligence now advancing to practical applications, the event aims to explore its broader integration into education. Particular emphasis is also being placed on language learning, using the expo as a platform to examine strategies for improving language acquisition and harnessing AI to support language education, with the goal of nurturing students with enhanced multilingual and cross-cultural competencies."

Data governance in Slovenia's healthcare is moving from patchwork to a governed, interoperable model that echoes the EU's push for a single, secure market for health data: the European Health Data Space is designed as a structured environment for both open and restricted health data, with pilots like HealthData@EU proving cross‑border sharing and reuse while preserving strict access controls (European Health Data Space (HealthData@EU) pilot - EU health data policy).

Domestically, the June 2025 draft Healthcare Digitalisation Act (ZDigZ) formalises that shift by centralising electronic records in the renamed CeZZ (formerly CRPP), tightening access via an access matrix, strengthening patient rights to view and block secondary uses of their pseudonymised data, and creating a public enterprise to operate core infrastructure under controller instruction (Healthcare Digitalisation Act (ZDigZ) draft - Government of Slovenia announcement).

Complementary pilots such as CEDAR aim to apply data analytics to procurement archives to detect fraud and boost transparency, showing how privacy-preserving analytics can also serve accountability (CEDAR transparent management pilot - Slovenian public healthcare procurement analytics).

Together these efforts reduce duplicated tests, ease clinician reporting burdens and strengthen continuity of care (ePrescription, patient summaries) - meaning safer, faster decisions at the bedside while giving citizens clearer control over their health data.

Slovenia's compute backbone for healthcare AI is now world‑class: the VEGA petascale system hosted by IZUM in Maribor supercharges research‑grade model training and large‑scale medical image analytics with a sustained 6.9 petaflops (6.9 million billion calculations per second) and a dense GPU partition built from NVIDIA A100s, while EuroHPC channels make multi‑disciplinary allocations available to academia, industry and the public sector through regular access calls - an important route for hospitals and national labs to bid for the CPU/GPU time needed for genomics, precision oncology pipelines and population‑level analytics (see the VEGA supercomputer at IZUM Maribor and the EuroHPC Regular Access call for supercomputing allocations).

Practical local entry is also supported: Slovenian teams can request SLING/VEGA accounts from IZUM or use Nordugrid ARC with SiGNET certificates and SSH keys for secure job submission, so hospital IT groups can move from pilots to production workflows without shipping patient data offsite.

"The Vega supercomputer will have indirect profound effects on our lives. It will enable scientists to invent new materials and components, it will help them model global phenomena, and develop new medicines and medical therapies in the fight against cancer or Alzheimer's disease. Furthermore, Vega will provide support to companies developing the most advanced products in the automotive, energy and health sectors. With this and similar steps the EU is resolutely following the path towards strategic information autonomy. I am convinced that the Vega supercomputer will enable everyone to always use the exceptional potential of new inventions to the benefit of individuals and all humanity."

Slovenia's regulatory roadmap for health AI is deliberately rights‑centred: the National Programme (NpUI) calls for an ethical and legal framework, a national supervisory mechanism and even certification pathways to ensure AI systems are human‑centred, transparent and auditable, while inviting humanities, legal experts and NGOs into the governance conversation to boost legitimacy (Slovenia AI Strategy Report - EU AI Watch).

That policy foundation aligns with attitudes in the medical community - regional research shows Slovenian faculty share ethical perspectives with international peers, an essential social licence for deploying clinical AI tools (Ethical attitudes of AI use in medicine - PLoS One / PubMed).

Practical transparency measures matter too: comparative research on algorithmic governance argues that governments must create clear public records about objectives and validation, require vendors to disclose development choices and treat trade‑secrecy claims narrowly so deployed systems are not mysterious “black boxes” but traceable decision tools; those steps turn abstract ethics into something a clinician or patient can follow in the medical record (Algorithmic Transparency for the Smart City - SSRN).

In short, building public trust in Slovenia will hinge on enforceable rules, visible validation and value‑proving pilots that show better outcomes and measurable ROI, not just technical promise.

Slovenia has set the building blocks to turn AI in health from experiments into scaled services by combining targeted public funding, strong national partners and open access research infrastructure: the National Programme (NpUI) has earmarked around EUR 110 million through 2025 for centres of excellence, co‑financing across TRLs, collaborative projects and support for EU programmes like Horizon Europe and Digital Europe (see the Slovenia AI Strategy Report - AI Watch).

Partnerships span industry and civil society (ICT Association of Slovenia / ZIT, CCIS), the Slovenian Artificial Intelligence Society (SLAIS), Strategic Research and Innovation Partnerships (SRIPs) and the Slovenian Digital Coalition, all designed to funnel ideas from pilots to production - backed by proposed national bodies such as a Digital Innovation Hub, a National AI Observatory (coordinated with SURS) and public co‑financing for reference implementations in priority areas like health and medicine.

Key institutions anchor the ecosystem: the Jožef Stefan Institute hosts the UNESCO‑backed IRCAI research centre that bridges policy and tools, national supercomputing and data platforms enable open‑science allocations for researchers, and existing health financing structures (including oversight by ZZZS) create a predictable funding environment; events such as ENNHRI's Co‑Lab in Ljubljana also show how human‑rights bodies are being woven into AI partnerships to safeguard trust and uptake (ENNHRI Co‑Lab: AI).

The net effect is a pragmatic pipeline - funding, national networks and world‑class compute - that helps hospitals and suppliers bid for grants, validate pilots and prove ROI in ways clinicians and procurement teams can act on.

Turning pilots into hospital‑grade services in Slovenia means treating validation and deployment as engineering and policy work: the National Programme explicitly funds projects across the full TRL spectrum - public co‑financing for basic AI research, support for collaborative mid‑TRL work, and targeted backing for TRL 5–8 reference implementations in priority areas like health and medicine - so a prototype can be stress‑tested, clinically validated and scaled under clear governance (see the Slovenia AI Strategy Report - EU AI Watch).

Practical paths to production are already visible: teams can leverage national supercomputing and EuroHPC allocations to run robust validation studies, align with the forthcoming supervisory and certification measures to prove safety and transparency, and link outcome metrics to procurement decisions (for example, measuring ROI through fewer avoidable admissions and lower sick leave helps make the business case) - detailed approaches to measuring impact are discussed in Nucamp's ROI summary on healthcare AI (measuring ROI through reduced avoidable admissions).

Deployment also requires unified IT and interoperability work so validated models actually plug into clinical workflows - a challenge Slovenia is tackling through centralized IT processes and digitalisation efforts highlighted in recent industry coverage (Slovenia embraces healthcare digitalization with centralized IT processes).

The “so what?” is simple: a funded TRL pipeline plus clear validation, certification and interoperable infrastructure turns promising AI prototypes into repeatable, auditable services that clinicians and procurement teams can trust and scale.

Slovenia's most visible healthcare AI wins from 2020–2025 span pandemic intelligence to early clinical decision support: the UNESCO‑backed IRCAI's Corona Virus Media Watch provided real‑time, multi‑language monitoring and visualisations that helped policy makers and journalists track outbreaks, while national projects such as the April–October 2020 COVID‑19 Prevalence Study and Jožef Stefan Institute models used Bayesian methods and machine‑learning to predict epidemiological workload and inform local responses (see the IRCAI Coronavirus Media Watch real-time monitoring coverage and the Slovenia AI Strategy Report - European AI Watch country report).

In parallel, emerging clinical pathways - precision oncology workflows that combine genomics and clinical data - and practical ROI‑focused pilots that measure value through fewer avoidable admissions have moved from concept to funded pilot, giving hospitals a tangible “why” for adoption (precision oncology pilot examples in Slovenian healthcare and Nucamp's ROI case notes).

The net effect: analytic tools that reduce reporting noise, targeted models that anticipate workload spikes, and pilot use cases with clear outcome metrics are proving AI's clinical and managerial value - turning promising algorithms into decision aids that clinicians can validate and procurement teams can budget for.

“Typically it is reported in individual countries how many infections, deaths and recoveries there are. The WHO collects this once a day and reports on its web page, from where we source the data,”

Final decisions about AI in Slovenian hospitals should be practical, auditable and tied to measurable outcomes: start by convening a cross‑disciplinary governance team, run a structured risk self‑assessment (for example, Protecht's AI project governance checklist helps identify gaps and strengthen oversight Protecht AI project governance checklist), lock down data and vendor controls with a healthcare‑specific GRC checklist (see Onspring's governance guide), and require clinical validation and ROI metrics - like reduced avoidable admissions - before procurement.

Pair those policies with tech steps (use VEGA/EuroHPC access for robust validation where appropriate) and a clear rollout plan: intake → clinical validation → certification → monitored deployment.

Invest in staff readiness: short, practical courses that teach prompt design, tool use and auditing workflows (for busy teams, the Nucamp Nucamp AI Essentials for Work bootcamp maps directly to upskilling needs).

Keep the loop closed with continuous monitoring, third‑party audits, and a public record of validation so clinicians and patients can trust decisions; small, well‑measured pilots that prove clinical and financial value make national regulation and certification meaningful rather than theoretical.

“At Nabla, our commitment to AI governance - rooted in transparency and trust - drives us to help shape a unified set of industry standards, empowering clinicians to confidently choose AI solutions that prioritize safety for all.”