Top 10 AI Prompts and Use Cases and in the Government Industry in Denmark

Denmark is fast becoming Europe's public‑sector AI laboratory: 28% of Danish companies used AI in 2024, the highest share in the EU, while coordinated programmes such as the national AI Kompetence Pagten and a dedicated Digital Taskforce are driving upskilling and safe roll‑out under the EU AI Act - backed by public investment for pilots and scaling in health, administration and the green transition.

Real-world pilots like the Børge assistant (supporting editors across roughly 1,200 borger.dk pages) show generative tools can lift productivity while keeping humans in charge; meanwhile practical training for civil‑servants and practitioners is critical - see Nucamp AI Essentials for Work bootcamp syllabus and registration for workplace prompt and prompt‑use skills.

Learn more about Denmark's AI momentum and the Børge case study from the national briefing and investment overview.

Bootcamp	Length	Early bird cost	Registration & Syllabus
AI Essentials for Work	15 Weeks	$3,582	AI Essentials for Work bootcamp syllabus and registration - Nucamp

“a good, helping hand during a busy workday,” - employees describing the Børge AI assistant

Selections were guided first and foremost by Denmark's own AI priorities: prompts and use cases that map directly to the National AI Strategy's goals (citizen‑centric services, research support, and public‑sector adoption) and the four priority sectors - healthcare, energy, agriculture and transport - outlined in the Denmark AI Strategy Report (Denmark AI Strategy Report - national AI priorities and priority sectors); criteria also weighed the practical levers the government has funded, from the ~EUR 27 million public investment fund for municipal and regional pilots to Digital Research Centre Denmark initiatives, plus the OECD dashboard's emphasis on a citizen‑centric, governance‑first approach (OECD AI Initiatives Dashboard - Denmark national governance and citizen-centric focus).

Priority was given to use cases that exploit Denmark's exceptional data assets - most notably the national health registries covering the whole population - and to ideas already compatible with ethical oversight (Data Ethics Council recommendations) and workforce upskilling programmes such as the AI Kompetence Pagten upskilling effort (AI Kompetence Pagten national upskilling programme for AI competency).

The net result: prompts chosen for policy alignment, scalability across municipalities, data readiness, and clear ethical and procurement pathways - so a hospital risk‑triage prompt, for example, isn't just clever, it can scale nationally because Danish registries let models learn across entire cohorts.

Danish hospitals are turning the country's superb registry backbone into clinical decision prompts that actually change bedside risk‑assessment: a Lancet Digital Health study used the Danish National Patient Registry and 23 years of disease history for more than 230,000 ICU admissions to train a neural network that substantially sharpened survival prediction (Lancet Digital Health ICU survival prediction study (PubMed)), while a follow‑up study showed that high‑frequency, hourly electronic‑record sampling makes mortality forecasts both more accurate and more explainable in real time (Dynamic hourly EHR mortality prediction study (PubMed)).

Complementing time‑series models, routine biomarkers can reclassify risk: a registry cohort of 17,312 acute medical patients found that adding suPAR to NEWS plus age/sex raised in‑hospital AUC from 0.87 to 0.92 and kept 30‑day NPV at 99%, helping spot patients with “low NEWS but high risk” who might otherwise be missed (suPAR plus NEWS risk stratification study (Critical Care Medicine)).

The practical takeaway is striking and memorable: an algorithm that “remembers” a decade‑old diagnosis can move a patient from routine care to lifesaving attention - a concrete example of how Denmark's linked registries can power scalable, ethically governed prompts for triage, discharge decisions and resource prioritisation.

Study	Cohort / Data	Key result
ICU neural network (Lancet Digital Health)	> 230,000 ICU admissions; 23 years disease history	Improved survival prediction using aggregated long‑term history and acute physiology (Lancet Digital Health ICU survival prediction study (PubMed))
Dynamic, explainable ML	High‑frequency EHR data, hourly sampling	1‑hour sampling improved 90‑day mortality prediction and explainability (Dynamic hourly EHR mortality prediction study (PubMed))
suPAR + NEWS	17,312 acute medical patients (registry)	AUC in‑hospital from 0.87 → 0.92 with age/sex/suPAR; 30‑day NPV 99% (suPAR plus NEWS risk stratification study (Critical Care Medicine))

“Excessive treatment is a serious risk among terminally ill patients treated in Danish intensive care units. Doctors and nurses have lacked a support tool capable of instructing them on who will benefit from intensive care.” - Professor Anders Perner

National pandemic forecasting in Denmark hinges on more than algorithms - it depends on a public service that can interpret, govern and act on model outputs, from Statens Serum Institut to municipal health desks; that's why workforce upskilling through programmes like the AI Kompetence Pagten upskilling is vital to turn raw forecasts into operational decisions.

Equally important are procurement and contract terms that protect IP, data rights and adaptability so models can be updated during a fast‑moving outbreak - see guidance on AI procurement best practices.

Finally, recent debates around analytics tenders highlight privacy and oversight as non‑negotiables; transparent procurement and civil‑service capability stop a forecast becoming a single opaque decision, meaning a model's uncertainty is surfaced and handled before it affects lives - a small governance fix can therefore be the difference between rough predictions and timely, targeted public‑health action.

Municipal buildings in Denmark are prime candidates for AI-driven predictive maintenance and energy optimisation: a 2024 open‑access review shows building digital twins can transform operations and maintenance to drive real energy savings (Open-access review: building digital twins for energy efficiency (Energy Informatics, 2024)), while complementary studies highlight that AI predictive‑maintenance programmes can cut unexpected downtime by roughly 40% and that AI demand‑forecasting can reach very high accuracy, improving budgeting and load‑shifting decisions (SCIRP study: Optimizing energy infrastructure with AI technology).

In practice this means Danish municipalities could move from reactive repairs to timed, low‑carbon interventions - imagine a school's heating system flagged days before a winter failure, avoiding last‑minute emergency fixes and saving both CO2 and cash - provided procurement and workforce skills are in place, which is where national upskilling like the AI Kompetence Pagten upskilling program for Danish government workforce and procurement and procurement best practices become essential to scale pilots into reliable, governed services.

Article	Authors	Journal / Published	Notes
A review of building digital twins to improve energy efficiency	Andres S. Cespedes-Cubides & Muhyiddine Jradi	Energy Informatics - 26 Feb 2024 (Open access)	Focus: digital twins for O&M; metrics: 13k accesses, 49 citations

Flood forecasting and emergency mapping in Denmark now blends high‑resolution terrain atlases, near‑real‑time satellite and drone imagery, and fast, approximate hydrodynamic models to give first responders usable maps when minutes matter: the Danish Meteorological Institute (DMI) has been tasked with national flood forecasting and is developing computationally efficient mapping - for example an approximate LISFLOOD‑FP approach tested on the Vejle River that matched drone and satellite observations from the March 2019 floods and helps forecasters identify areas at risk without waiting for full-scale simulations (Real‑time fluvial flood mapping study (EGU24)).

These operational products plug into web‑GIS portals and global tools such as the Copernicus GloFAS map viewer to give probabilistic flow forecasts and situational awareness (Copernicus GloFAS probabilistic flood map viewer), while national planning is already grounded in a digital terrain atlas that helped 99% of Danish municipalities produce flood‑risk maps for today and for 2100 - so emergency maps are not just about the next storm but about long‑term adaptation and clear lines to the Danish Emergency Management Agency (Beredskabsstyrelsen) and local responders (World Economic Forum article on keeping Danish cities above water).

The practical payoff is simple: precomputed scenarios and rapid, approximate mapping turn model uncertainty into actionable evacuation zones and targeted sandbagging plans instead of paralysis.

Denmark's Ministry of Transport and municipal operators are turning intelligent transport systems into everyday tools that cut congestion, lower emissions and prioritise people on bikes and buses: Copenhagen's upgrade of controllers at 380 intersections shows how ITS can shave 10% off cyclists' travel time, cut bus delays by up to 20% and reduce signal energy use by a third while smoothing the “green wave” for riders (Copenhagen smart traffic signals case study - Cities100); at the same time, data-driven platforms like MobiMaestro and apps such as GreenCatch use floating‑car and sensor feeds to give dynamic route advice and VMS displays that tell cyclists and drivers when they'll hit fewer lights.

New detection tech is arriving too: LiDAR‑based systems and AI controllers promise higher reliability in Nordic weather and multimodal awareness that prioritises safety for vulnerable road users, while pilots and vendor tests already report measurable drops in waiting times and emissions.

Partnerships bringing platforms like SIMPL into local integration pipelines mean municipalities can upgrade intersections without invasive works, converting everyday traffic signals into a resilient, climate‑friendly network that nudges people toward bikes, buses and smoother city streets (Seyond and ATKI LiDAR traffic detection partnership in Denmark).

“ATKI's proven track record in delivering smart traffic solutions makes them the ideal partner to accelerate SIMPL adoption in the Danish market,” said Philip Lassner, Head of Global ITS Business at Seyond.

Denmark is building a culturally grounded, privacy‑first large language model for public services via a broad public‑private effort: the Danish Language Model Consortium, led by the Alexandra Institute, IBM Denmark and the Danish Chamber of Commerce, pools datasets, use‑cases and governance principles so models reflect Danish legislation, language and practice (Danish Language Model Consortium - DLA Piper report).

Complementing the consortium, the state‑backed Danish Foundation Models (DFM) platform received DKK 30.7 million to create a secure R&D sandpit for training, fine‑tuning and open‑source release of smaller, task‑focused Danish models that comply with GDPR and the project's five transparency and data‑protection principles (SDU summary of the 30.7M DKK DFM grant).

The initiative is explicitly designed to be practical rather than a bid to outscale Big Tech: partners pledge datasets and use cases so the base model (built on research‑grade Munin variants) can be customised for tax processing, municipal chatbots and healthcare workflows while keeping data inside EU guardrails - and yes, the project has even toyed with friendly brand names like MyGPT or DanGPT as it readies a public‑service toolset (ComputerWeekly - Government backs Danish version of ChatGPT), making the effort feel both national and immediately useful to caseworkers and citizens alike.

Item	Detail
Total funding	30.7 million DKK (Ministry of Digital Affairs)
Allocation	20.7M DKK for platform (2024–2027); 10M DKK for research & innovation
Lead partners	Alexandra Institute, IBM Denmark, Danish Chamber of Commerce; DFM: Aarhus, KU, SDU, Alexandra

“By integrating stringent security protocols with collaborative and user‑driven flexibility, DFM aims to fully harness the potential of AI to meet Denmark's diverse societal needs and pave the way for a better future.” - Peter Schneider‑Kamp

Denmark has turned a modest reporting tweak into a powerful governance lever: an amendment to the Financial Statements Act now forces large companies to publish a clear account of their data‑ethics policy (or explain why none exists), a “comply‑or‑explain” rule that moves ethical AI from a back‑office memo into the annual management report and boardroom scrutiny - see the OECD overview of the Law on the Disclosure of Data Ethics Policy for details.

Complementing the legal duty, the independent Data Ethics Council (and its practical toolbox and risk‑assessment forms) helps organisations - including public bodies that must publish data‑risk results - translate obligations into checks, documentation and mitigation plans so hidden profiling or automated decisions are caught before they scale; the payoff is concrete: a single management‑report line can surface a decade‑old model that unfairly targets customers and force corrective action.

For practical guidance and public‑sector resources, the Agency of Digital Government's how-to guidance on data ethics in business makes it straightforward for firms and municipalities to start reporting responsibly.

Initiative	Key point
Financial Statements Act amendment (Law on disclosure)	Effective 1 Jan 2021 - large companies must report data‑ethics policies in management reports or explain absence (OECD overview of the Law on the Disclosure of Data Ethics Policy)
Data Ethics Council & toolbox	Established 2019; provides guidance, risk‑assessment forms and pushes transparency (public sector must publish risk assessments) (Data Ethics Council case study and toolbox)
Agency guidance	Practical how‑to resources for companies on starting data‑ethics reporting (Agency of Digital Government how-to materials on data ethics in business)

“Generally, data ethics is understood as the ethical dimension to the relationship between technology and the fundamental rights of individuals, rule of law and fundamental societal values that the technological development gives rise to. The term comprises ethical consideration in the use of data.”

Secure, privacy‑preserving analytics for research in Denmark starts with the country's extraordinary biological resource base - the Danish National Biobank stores millions of samples and provides a clear, six‑step access route for bona fide projects (Danish National Biobank - millions of samples and coordinated access).

To exploit that wealth without moving sensitive data, federated approaches show the way: projects like the FedX federated biobank network let algorithms visit data at its source and share only the learned model or aggregated counts, enabling federated cohort discovery, secure partner search and aggregated genotype/phenotype statistics without exposing personal records (FedX Biobank - national federated biobank network for federated learning and secure aggregation).

Scaling these pipelines across hospitals, research centres and regional registries also requires people who understand procurement, governance and secure ML operations - practical workforce training such as the Nucamp AI Essentials for Work bootcamp syllabus - practical workforce upskilling for AI in the workplace helps turn federated tech into responsibly governed, actionable research tools - imagine querying cross‑hospital cohorts for rare‑variant signals while every individual sample literally never leaves its home server.

For COI officers and municipal caseworkers, citizen‑facing automation starts with reliable OCR and blossoms into full intelligent document processing (IDP): OCR turns photos, scans and handwritten forms into searchable text so a tenancy contract or income statement is machine‑readable within seconds, while IDP layers NLP, rules and human‑in‑the‑loop checks to classify documents, extract benefits‑relevant fields and route cases to the right inbox - cutting days or even weeks from manual triage.

Practical wins are concrete: automated invoice pilots have slashed cycle times by up to 90% and OCR accuracy can reach enterprise‑grade levels when paired with preprocessing and validation, which directly translates into faster benefit decisions, fewer request‑for‑evidence cycles and better accessibility for applicants who submit phone photos instead of paper (see ABBYY's clear primer on ABBYY OCR vs IDP comparison guide and MST's hands‑on guide to MST OCR automation implementation guide).

Security and compliance are integral, not optional: OCR outputs can be redacted, encrypted and fed to DLP tools so sensitive PII never leaks from a mailbox into open systems - an operational design that keeps service fast and auditable while protecting citizen data (see Proofpoint's overview of Proofpoint OCR for secure digitization overview).

Technology	Key strength	Use cases
Simple OCR	Speed & consistency	Invoices, contracts, passports
ICR	Handwriting recognition, learning	Patient forms, handwritten affidavits
OMR	High accuracy for marks	Surveys, checkboxes, ballots

“OCR extracts text from scanned forms, medical images, screenshots of sensitive content, PDFs, and more. Once the text is extracted, you can use DLP (data loss prevention) detectors, dictionaries, and rules to identify and prevent exfiltration of that sensitive data,” - Itir Clarke, Proofpoint

Denmark's farms are a textbook in practical precision agriculture: RTK‑GPS now steers 71% of the country's cultivated land to 1–2 cm accuracy, while satellites, drones and on‑tractor sensors turn maps into real‑time input decisions that boost yield and cut waste (Danish farmers leading the way in precision agriculture).

Backed by a DKK 25 million Novo Nordisk Foundation grant, Aarhus University's System‑based Precision Agriculture project is marrying sensors, drone imagery and models to apply nitrogen “in the right amount, at the right time and in the right place,” aiming to measurably reduce nitrogen loss and greenhouse‑gas emissions without losing productivity (precision agriculture project at Aarhus University).

Practical tools already in use - like Yara's N‑Sensor - demonstrate the payoff: up to a 12% yield increase and a 14% reduction in fertiliser use, meaning fewer emissions, lower input bills and stronger sustainability credentials for Danish exporters; the vivid takeaway is simple: centimetre‑level guidance can turn a decade of blanket spreading into field‑by‑field stewardship that pays for itself.

Metric / Project	Key fact
RTK‑GPS adoption (2024)	71% of Denmark's agricultural land cultivated with 1–2 cm RTK‑GPS (Food Nation)
Aarhus University precision ag project	DKK 25 million Novo Nordisk Foundation grant to reduce agriculture's climate footprint via sensing and modelling
Yara N‑Sensor legacy	Up to 12% yield increase and ~14% reduction in fertiliser use (25 years of N‑Sensor development)

“This will quantitatively measure whether precision agriculture really reduces the environmental burden and to what extent.” - Davide Cammarano

Denmark's next steps are pragmatic: turn legal clarity into operational practice, invest the pilot funds already earmarked for public‑sector AI, and scale workforce skills so agencies can use models safely and confidently.

With the EU AI Act now in force, public bodies should follow the three compliance actions highlighted in the Decoding briefing - assess risk level, appoint an AI compliance officer and document decision‑making - so transparency and human oversight are baked into every rollout (Decoding: AI in public sector digitalisation).

At the same time, the national strategy's testing and scaling pool (≈EUR 27M) should be directed to high‑value, citizen‑facing pilots in health, energy, agriculture and transport that already show measurable wins (Denmark AI Strategy Report - priority sectors & investment).

Finally, scaleable upskilling - via the AI Kompetence Pagten and practical courses such as Nucamp's AI Essentials for Work - will turn forecasts and prompts into dependable services rather than experimental toys (Nucamp AI Essentials for Work syllabus & registration).

Priority	Action	Source
Governance	Risk assessment, AI compliance officer, documentation	Decoding: AI in public sector digitalisation
Pilots & Data	Direct EUR 27M fund to scalable public pilots in health, energy, agri, transport	Denmark AI Strategy Report - priority sectors & investment
Skills & Procurement	National upskilling (AI Kompetence Pagten) and practical courses for civil servants	Nucamp AI Essentials for Work syllabus & registration

“a good, helping hand during a busy workday,” - employees describing the Børge AI assistant

Get procurement, ethics and skills aligned, and the payoff is concrete: faster, fairer services that keep humans in charge.